Welcome to the GSFC Exoplanet Modeling and Analysis Center (EMAC)

EMAC serves as a catalog, repository and integration platform for modeling and analysis resources focused on the study of exoplanet characteristics and environments. EMAC is a key project of the GSFC Sellers Exoplanet Environments Collaboration (SEEC).

If you make use of tools linked or hosted on EMAC: please use the following statement in your publication acknowledgements: “This research made use of the NASA Exoplanet Modeling and Analysis Center (EMAC), which is funded by the NASA Planetary Science Division’s Internal Scientist Funding Model.”

Stay up to date with EMAC!
  • Subscribe to our monthly RSS messages on new updates and tools
  • Check out the (unofficial) Twitter account @ExoplanetModels, where new tools and features are highlighted

  • Help us improve EMAC!
  • Email us with general feedback at and tell us what you’d change or improve.
  • Click the icon in a resource box to provide suggestions for an individual tool or tools.

  • More Information on EMAC for first-time visitor...       
    • EMAC is intended as a clearinghouse for the whole research community interested in exoplanets, where any software or model developer can submit their tool/model or their model output as a contribution for others to use.
    • EMAC provides a searchable and sortable database for available source code and data output files - both resources hosted locally by EMAC as well as existing external tools and repositories hosted elsewhere.
    • The EMAC team also helps develop new web interfaces for tools that can be run “on-demand” or model grids that can be interpolated for more individualized results.
    • If you would like to submit a new tool/model to EMAC, please visit Submit a Resource page.
    • For help with tutorials for select resources/tools use the “Demo” button below and subscribe to our YouTube channel.
    • Watch this video for a walk-through of the whole EMAC site, including how to submit a new tool and how to access information for each resource.

    The P.I. is Avi Mandell, and the Deputy P.I. is Eric Lopez; more information on EMAC staffing and organization will be posted shortly.

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    PlanetPack: Command-line Tool for Radial Velocity and Transit Lightcurves Fitting

    R.V. Baluev

    PlanetPack is a software tool developed to facilitate the radial-velocity and transit data analysis for the goal of exoplanets detection, characterization, and basic dynamical simulations. The description of the main theoretic concepts, statistical methods and algorithms that PlanetPack implements, is given in the following refereed papers: R.V. Baluev 2013, Astronomy & Computing, V. 2, P. 18 (initial release); R.V. Baluev 2018, Astronomy & Computing, V. 25, P. 221 (update 3.0).

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    https://emac.gsfc.nasa.gov#?related_resource=b2dad54e-3da3-484e-a352-f89861c1fb1d

    PlanetPack: Command-line Tool for Radial Velocity and Transit Lightcurves Fitting

    R.V. Baluev

    PlanetPack is a software tool developed to facilitate the radial-velocity and transit data analysis for the goal of exoplanets detection, characterization, and basic dynamical simulations. The description of the main theoretic concepts, statistical methods and algorithms that PlanetPack implements, is given in the following refereed papers: R.V. Baluev 2013, Astronomy & Computing, V. 2, P. 18 (initial release); R.V. Baluev 2018, Astronomy & Computing, V. 25, P. 221 (update 3.0).

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    https://emac.gsfc.nasa.gov#2c240d5e-99cc-4542-ae2f-ceef82ccb9f5
    SMINT: Structure Model INTerpolator

    Caroline Piaulet, with models from several published papers (see documentation)

    Using mass-radius grids for water- or hydrogen-enveloped small planets, astronomers can infer the range of plausible compositions that a planet may have based on its mass, radius, age and/or level of insolation. In its present form, smint presents a tool to leverage in this way several published mass-radius grids in a Bayesian framework. The interface is user-friendly: the user can input the parameters of the planet of interest with specifications on the priors that should be used, and the tool returns publication-ready plots presenting the joint parameters constraints obtained from interpolating the interior models grid of interest as well as confidence intervals for each parameter.

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    https://emac.gsfc.nasa.gov#?related_resource=2c240d5e-99cc-4542-ae2f-ceef82ccb9f5

    SMINT: Structure Model INTerpolator

    Caroline Piaulet, with models from several published papers (see documentation)

    Using mass-radius grids for water- or hydrogen-enveloped small planets, astronomers can infer the range of plausible compositions that a planet may have based on its mass, radius, age and/or level of insolation. In its present form, smint presents a tool to leverage in this way several published mass-radius grids in a Bayesian framework. The interface is user-friendly: the user can input the parameters of the planet of interest with specifications on the priors that should be used, and the tool returns publication-ready plots presenting the joint parameters constraints obtained from interpolating the interior models grid of interest as well as confidence intervals for each parameter.

    About
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    https://emac.gsfc.nasa.gov#a4a4bf94-d97a-45ba-825e-fee555ec6ec2
    TRIPPy: Python based Trailed Source Photometry

    Wesley C. Fraser

    TRIPPy is a python package aimed to perform all the steps required to measure accurate photometry of both trailed and non-trailed (stationary) astronomical sources. This includes the ability to generate stellar and trailed point source functions, and to use circular and pill shaped apertures to measure photometry and estimate appropriate aperture corrections. Tools for source fitting with a model PSF (both MCMC and classical least-squares minimizers) are available. Citation: If you use TRIPPy in your science works, please cite Fraser, W. et al., 2016, Astronomical Journal, 151. DOI at Zenodo.

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    https://emac.gsfc.nasa.gov#?related_resource=a4a4bf94-d97a-45ba-825e-fee555ec6ec2

    TRIPPy: Python based Trailed Source Photometry

    Wesley C. Fraser

    TRIPPy is a python package aimed to perform all the steps required to measure accurate photometry of both trailed and non-trailed (stationary) astronomical sources. This includes the ability to generate stellar and trailed point source functions, and to use circular and pill shaped apertures to measure photometry and estimate appropriate aperture corrections. Tools for source fitting with a model PSF (both MCMC and classical least-squares minimizers) are available. Citation: If you use TRIPPy in your science works, please cite Fraser, W. et al., 2016, Astronomical Journal, 151. DOI at Zenodo.

    About
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    https://emac.gsfc.nasa.gov#c53cbd66-66c4-414f-b300-725079f84600
    PEP: The Planetary Ephemeris Program

    Developed by many; original: Michael Ash; most recent and longest- time-involved: John Chandler

    This Fortran computer program models orbital motion in the solar system, including almost 100 individual asteroids as well as all of the planets and some moons, along with a detailed model of our moon, and a model of pulsar motions and of distant radio sources. It takes as input diverse astrometric data: radio, radar, laser, timing of signal arrivals, and VLBI. The program can solve for well over 100 parameters, including orbital and (for some bodies) rotational initial conditions, sky coordinates for radio sources, plasma densities, the second harmonic of the Sun's gravitational field, and those related to tests of fundamental physics.

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    https://emac.gsfc.nasa.gov#?related_resource=c53cbd66-66c4-414f-b300-725079f84600

    PEP: The Planetary Ephemeris Program

    Developed by many; original: Michael Ash; most recent and longest- time-involved: John Chandler

    This Fortran computer program models orbital motion in the solar system, including almost 100 individual asteroids as well as all of the planets and some moons, along with a detailed model of our moon, and a model of pulsar motions and of distant radio sources. It takes as input diverse astrometric data: radio, radar, laser, timing of signal arrivals, and VLBI. The program can solve for well over 100 parameters, including orbital and (for some bodies) rotational initial conditions, sky coordinates for radio sources, plasma densities, the second harmonic of the Sun's gravitational field, and those related to tests of fundamental physics.

    About
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    https://emac.gsfc.nasa.gov#8818a2df-4629-4d4d-b7a5-eede5ca308fe
    DYNAMITE: DYNAmical Multi-planet [System Architecture] Injection [via Monte Carlo Integrations] TEster

    Dietrich, J. et al.

    We start with the specific (yet often incomplete) data on the orbital and physical parameters for the planets in any given system's architecture. We combine that with detailed statistical population models and a dynamical stability criterion to predict the likelihood for the parameters of one additional planet in the system. These predictions are given in the form of observable values (transit depth measurements, RV semi-amplitudes, or direct imaging separation and contrast) that can be tested by follow-up observations.

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    https://emac.gsfc.nasa.gov#?related_resource=8818a2df-4629-4d4d-b7a5-eede5ca308fe

    DYNAMITE: DYNAmical Multi-planet [System Architecture] Injection [via Monte Carlo Integrations] TEster

    Dietrich, J. et al.

    We start with the specific (yet often incomplete) data on the orbital and physical parameters for the planets in any given system's architecture. We combine that with detailed statistical population models and a dynamical stability criterion to predict the likelihood for the parameters of one additional planet in the system. These predictions are given in the form of observable values (transit depth measurements, RV semi-amplitudes, or direct imaging separation and contrast) that can be tested by follow-up observations.

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    https://emac.gsfc.nasa.gov#b1b38c3e-43c9-4b13-a35f-e2ba54db0acf
    VULCAN: Photochemical kinetics for planetary atmospheres

    Shang-Min (Shami) Tsai

    Photochemical kinetics for (exo-)planetary atmospheres, a fast and easy-to-use python code. The model has hierarchical C-H-N-O-S networks and treats thermochemistry, photochemistry, eddy diffusion, advection transport, condensation, and various boundary conditions.

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    https://emac.gsfc.nasa.gov#?related_resource=b1b38c3e-43c9-4b13-a35f-e2ba54db0acf

    VULCAN: Photochemical kinetics for planetary atmospheres

    Shang-Min (Shami) Tsai

    Photochemical kinetics for (exo-)planetary atmospheres, a fast and easy-to-use python code. The model has hierarchical C-H-N-O-S networks and treats thermochemistry, photochemistry, eddy diffusion, advection transport, condensation, and various boundary conditions.

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    https://emac.gsfc.nasa.gov#a5ae508b-b75d-4bd7-881f-e6f336633be2
    APOLLO: MCMC Exoplanet Atmosphere Retrieval Code

    Alex Howe & Arthur Adams

    APOLLO is an exoplanet atmosphere retrieval code designed for flexibility and comparison of models. The code computes 1-D forward models of exoplanet spectrum in transit or emission and fits them to observations using an MCMC method. APOLLO includes options for multiple radiative transfer algorithms, temperature-pressure profiles, and cloud parameterizations, allowing for comparison of models using different physics prescriptions. APOLLO can also generate synthetic spectra in the JWST spectroscopic modes, as well as compute photometric fluxes.

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    https://emac.gsfc.nasa.gov#?related_resource=a5ae508b-b75d-4bd7-881f-e6f336633be2

    APOLLO: MCMC Exoplanet Atmosphere Retrieval Code

    Alex Howe & Arthur Adams

    APOLLO is an exoplanet atmosphere retrieval code designed for flexibility and comparison of models. The code computes 1-D forward models of exoplanet spectrum in transit or emission and fits them to observations using an MCMC method. APOLLO includes options for multiple radiative transfer algorithms, temperature-pressure profiles, and cloud parameterizations, allowing for comparison of models using different physics prescriptions. APOLLO can also generate synthetic spectra in the JWST spectroscopic modes, as well as compute photometric fluxes.

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    https://emac.gsfc.nasa.gov#da73a312-9230-4ab9-b6ba-6c99e915828a
    IcyDwarf: IcyDwarf computes the coupled geophysical-chemical-orbital evolution of an icy dwarf planet or moon

    Neveu, M. from a geophysical evolution code initially developed by Desch, S. et al. (2009)

    IcyDwarf calculates:

    • The thermal evolution of one or more icy moon(s) or dwarf planet(s), with no chemistry, but with rock hydration, dehydration, hydrothermal circulation, core cracking, tidal heating, and porosity. The depth of cracking and a bulk water:rock ratio by mass in the rocky core are also computed, as well as moon orbital evolution.
    • Whether cryovolcanism is possible by the exsolution of volatiles from cryolavas.
    • Equilibrium fluid and rock chemistries resulting from water-rock interaction in subsurface oceans in contact with a rocky core, up to 200ºC and 1000 bar

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    https://emac.gsfc.nasa.gov#?related_resource=da73a312-9230-4ab9-b6ba-6c99e915828a

    IcyDwarf: IcyDwarf computes the coupled geophysical-chemical-orbital evolution of an icy dwarf planet or moon

    Neveu, M. from a geophysical evolution code initially developed by Desch, S. et al. (2009)

    IcyDwarf calculates:

    • The thermal evolution of one or more icy moon(s) or dwarf planet(s), with no chemistry, but with rock hydration, dehydration, hydrothermal circulation, core cracking, tidal heating, and porosity. The depth of cracking and a bulk water:rock ratio by mass in the rocky core are also computed, as well as moon orbital evolution.
    • Whether cryovolcanism is possible by the exsolution of volatiles from cryolavas.
    • Equilibrium fluid and rock chemistries resulting from water-rock interaction in subsurface oceans in contact with a rocky core, up to 200ºC and 1000 bar

    About
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    https://emac.gsfc.nasa.gov?related_resource=21ea436a-3c5a-477c-81d8-06549c7bb3b2
    Deep-Transit: Identify Transit Signals with Deep Learning Based Object Detection Algorithm

    Cui, K. et al.

    Deep-Transit is an open-source Python package designed for transit detection with a deep learning based 2D object detection algorithm. For simple usage, Deep-Transit can handle your light curve and then output the transiting candidates' bounding boxes and confidence scores. Deep-Transit has already been trained for Kepler and TESS data, but can be easily extended to other photometric surveys, even ground-based observations. Deep-Transit also provides the interface to train on your own datasets.

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    https://emac.gsfc.nasa.gov#?related_resource=21ea436a-3c5a-477c-81d8-06549c7bb3b2

    Deep-Transit: Identify Transit Signals with Deep Learning Based Object Detection Algorithm

    Cui, K. et al.

    Deep-Transit is an open-source Python package designed for transit detection with a deep learning based 2D object detection algorithm. For simple usage, Deep-Transit can handle your light curve and then output the transiting candidates' bounding boxes and confidence scores. Deep-Transit has already been trained for Kepler and TESS data, but can be easily extended to other photometric surveys, even ground-based observations. Deep-Transit also provides the interface to train on your own datasets.

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    https://emac.gsfc.nasa.gov#62d0814f-17bd-4103-80ad-f823a9fdf1d4
    ATES: ATmospheric EScape

    The ATES hydrodynamics code computes the temperature, density, velocity and ionization fraction profiles of highly irradiated planetary atmospheres, along with the current, steady-state mass loss rate. ATES solves the one-dimensional Euler, mass and energy conservation equations in radial coordinates through a finite-volume scheme. The hydrodynamics module is paired with a photoionization equilibrium solver that includes cooling via bremsstrahlung, recombination and collisional excitation/ionization for the case of an atmosphere of primordial composition (i.e., pure atomic hydrogen-helium), while also accounting for advection of the different ion species.

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    https://emac.gsfc.nasa.gov#?related_resource=62d0814f-17bd-4103-80ad-f823a9fdf1d4

    ATES: ATmospheric EScape

    The ATES hydrodynamics code computes the temperature, density, velocity and ionization fraction profiles of highly irradiated planetary atmospheres, along with the current, steady-state mass loss rate. ATES solves the one-dimensional Euler, mass and energy conservation equations in radial coordinates through a finite-volume scheme. The hydrodynamics module is paired with a photoionization equilibrium solver that includes cooling via bremsstrahlung, recombination and collisional excitation/ionization for the case of an atmosphere of primordial composition (i.e., pure atomic hydrogen-helium), while also accounting for advection of the different ion species.

    About
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    https://emac.gsfc.nasa.gov#8d046717-cbdd-4bf1-8dd1-48d99cc1b6c0
    EXOTIC (EXOplanet Transit Interpretation Code): A Python3 package for analyzing photometric data of transiting exoplanets

    The Exoplanet Watch Team

    A Python 3 package for analyzing photometric data of transiting exoplanets into lightcurves and retrieving transit epochs and planetary radii. EXOTIC can run on a Windows, Macintosh, or Linux/Unix computer. You can also use EXOTIC via the free Google Colab, which features cloud computing, many helpful plotting functions, and a simplified installation. However, if you are a user with many images or large images, we recommend running EXOTIC locally on your own computer.

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    https://emac.gsfc.nasa.gov#?related_resource=8d046717-cbdd-4bf1-8dd1-48d99cc1b6c0

    EXOTIC (EXOplanet Transit Interpretation Code): A Python3 package for analyzing photometric data of transiting exoplanets

    The Exoplanet Watch Team

    A Python 3 package for analyzing photometric data of transiting exoplanets into lightcurves and retrieving transit epochs and planetary radii. EXOTIC can run on a Windows, Macintosh, or Linux/Unix computer. You can also use EXOTIC via the free Google Colab, which features cloud computing, many helpful plotting functions, and a simplified installation. However, if you are a user with many images or large images, we recommend running EXOTIC locally on your own computer.

    About
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    GRIT: A package for structure-preserving simulations of gravitationally interacting rigid-bodies

    Chen, Renyi; Li, Gongjie and Tao, Molei

    This is a package dedicated to the simulation of N gravitationally interacting rigid/point mass bodies. Tidal forces and general relativity correction are supported. Multiscale splittings are included to boost the simulation speed. Multiple schemes with different orders of convergences and splitting strategies are available. Force evaluations can be parallelized. Floating-point format can be customized as float / double / long double globally.

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    https://emac.gsfc.nasa.gov#?related_resource=b5f1b190-4b8e-42b7-b340-0d2324677625

    GRIT: A package for structure-preserving simulations of gravitationally interacting rigid-bodies

    Chen, Renyi; Li, Gongjie and Tao, Molei

    This is a package dedicated to the simulation of N gravitationally interacting rigid/point mass bodies. Tidal forces and general relativity correction are supported. Multiscale splittings are included to boost the simulation speed. Multiple schemes with different orders of convergences and splitting strategies are available. Force evaluations can be parallelized. Floating-point format can be customized as float / double / long double globally.

    About
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    https://emac.gsfc.nasa.gov#11e28f8f-6028-4260-86a9-0fe8159f9ddd
    ExoPlaSim: Extending the Planet Simulator for Exoplanets

    Paradise, A. et al.

    A modified version of the PlaSim 3D climate model, designed to simulate planets with Earth-like atmospheric compositions across a wide parameter space, including tidally-locked rotation, 0.1-10 bars surface pressure, and a range of stellar spectra. ExoPlaSim has a Python API for configuring and running models, as well as utilities for interacting with and analyzing the netCDF output files. ExoPlaSim is also pip-installable. As an intermediate-complexity model, ExoPlaSim trades some complexity for speed, and is able to run on a range of hardware including personal laptops and high-performance computing clusters, with typical performance of 1 year of climate at T21 resolution in 1-5 minutes.

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    https://emac.gsfc.nasa.gov#?related_resource=11e28f8f-6028-4260-86a9-0fe8159f9ddd

    ExoPlaSim: Extending the Planet Simulator for Exoplanets

    Paradise, A. et al.

    A modified version of the PlaSim 3D climate model, designed to simulate planets with Earth-like atmospheric compositions across a wide parameter space, including tidally-locked rotation, 0.1-10 bars surface pressure, and a range of stellar spectra. ExoPlaSim has a Python API for configuring and running models, as well as utilities for interacting with and analyzing the netCDF output files. ExoPlaSim is also pip-installable. As an intermediate-complexity model, ExoPlaSim trades some complexity for speed, and is able to run on a range of hardware including personal laptops and high-performance computing clusters, with typical performance of 1 year of climate at T21 resolution in 1-5 minutes.

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    https://emac.gsfc.nasa.gov#c69b220a-eae8-4ccd-9b37-4e623d071262
    Hypatia Catalog: Database of stellar elemental abundances for solar neighborhood stars

    Hinkel, N.R. et al. (2014), https://www.hypatiacatalog.com/hypatia/default/credits

    The Hypatia Catalog is a comprehensive collection of literature data and the largest database of stellar abundances for stars near to the Sun (Hinkel et al. 2014}. The multidimensional database currently spans 78 unique elements and species in ~9400 stars, ~1300 of which are planet hosts, within 500 pc of the Sun, including all exoplanet host stars regardless of distance. Hypatia was compiled from ~215 literature source abundance measurements that were re-normalized to the same solar scale, so that all values were on a common baseline.

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    https://emac.gsfc.nasa.gov#?related_resource=c69b220a-eae8-4ccd-9b37-4e623d071262

    Hypatia Catalog: Database of stellar elemental abundances for solar neighborhood stars

    Hinkel, N.R. et al. (2014), https://www.hypatiacatalog.com/hypatia/default/credits

    The Hypatia Catalog is a comprehensive collection of literature data and the largest database of stellar abundances for stars near to the Sun (Hinkel et al. 2014}. The multidimensional database currently spans 78 unique elements and species in ~9400 stars, ~1300 of which are planet hosts, within 500 pc of the Sun, including all exoplanet host stars regardless of distance. Hypatia was compiled from ~215 literature source abundance measurements that were re-normalized to the same solar scale, so that all values were on a common baseline.

    About Demo
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    https://emac.gsfc.nasa.gov#05d618da-255f-4729-8cef-905448be606d
    KOBE: Kepler Observes Bern Exoplanets

    Lokesh Mishra

    KOBE adds the geometrical limitations and the physical detection biases of the transit method to a given population of theoretical planets. In addition, it also adds the completeness and reliability of a transit survey. For more details, click here.

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    https://emac.gsfc.nasa.gov#?related_resource=05d618da-255f-4729-8cef-905448be606d

    KOBE: Kepler Observes Bern Exoplanets

    Lokesh Mishra

    KOBE adds the geometrical limitations and the physical detection biases of the transit method to a given population of theoretical planets. In addition, it also adds the completeness and reliability of a transit survey. For more details, click here.

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    https://emac.gsfc.nasa.gov#7ff64682-ae19-40fb-9368-451bcbb9d6a3
    Pyratbay: A Forward-modeling and retrieval code to model exoplanet atmospheres and spectra

    Cubillos, P. E. and Blecic, J.

    The Pyrat Bay framework is an open-source pack for exoplanet atmospheric modeling, spectral synthesis, and Bayesian retrieval. The modular design of the code allows the users to generate atmospheric 1D parametric models of the temperature, abundances (equilibrium or constant profiles), and altitude profiles in hydrostatic equilibrium; sample ExoMol and HITRAN line-by-line cross sections with custom resolving power and line-wing cutoff values; compute emission or transmission spectra considering cross sections from molecular line transitions, collision-induced absorption, Rayleigh scattering, gray clouds, and alkali resonance lines; and perform Markov chain Monte Carlo atmospheric retrievals.

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    https://emac.gsfc.nasa.gov#?related_resource=7ff64682-ae19-40fb-9368-451bcbb9d6a3

    Pyratbay: A Forward-modeling and retrieval code to model exoplanet atmospheres and spectra

    Cubillos, P. E. and Blecic, J.

    The Pyrat Bay framework is an open-source pack for exoplanet atmospheric modeling, spectral synthesis, and Bayesian retrieval. The modular design of the code allows the users to generate atmospheric 1D parametric models of the temperature, abundances (equilibrium or constant profiles), and altitude profiles in hydrostatic equilibrium; sample ExoMol and HITRAN line-by-line cross sections with custom resolving power and line-wing cutoff values; compute emission or transmission spectra considering cross sections from molecular line transitions, collision-induced absorption, Rayleigh scattering, gray clouds, and alkali resonance lines; and perform Markov chain Monte Carlo atmospheric retrievals.

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    https://emac.gsfc.nasa.gov#a0bca239-433c-40a5-95f3-5928ef765cc5
    SparseBLS: Box-Fitting Least Squares implementation for sparse data

    Aviad Panahi, Shay Zucker

    A new implementation of the commonly used Box-fitting Least Squares (BLS) algorithm, for the detection of transiting exoplanets in photometric data. Unlike BLS, our new implementation—Sparse BLS, does not use binning of the data into phase bins, nor does it use any kind of phase grid. Thus, its detection efficiency does not depend on the transit phase, and is therefore slightly better than that of BLS. For sparse data, it is also significantly faster than BLS. It is therefore perfectly suitable for large photometric surveys producing unevenly-sampled sparse light curves, such as Gaia.

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    https://emac.gsfc.nasa.gov#?related_resource=a0bca239-433c-40a5-95f3-5928ef765cc5

    SparseBLS: Box-Fitting Least Squares implementation for sparse data

    Aviad Panahi, Shay Zucker

    A new implementation of the commonly used Box-fitting Least Squares (BLS) algorithm, for the detection of transiting exoplanets in photometric data. Unlike BLS, our new implementation—Sparse BLS, does not use binning of the data into phase bins, nor does it use any kind of phase grid. Thus, its detection efficiency does not depend on the transit phase, and is therefore slightly better than that of BLS. For sparse data, it is also significantly faster than BLS. It is therefore perfectly suitable for large photometric surveys producing unevenly-sampled sparse light curves, such as Gaia.

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    https://emac.gsfc.nasa.gov#1826ad69-1ae1-4f54-acbd-3f567bdb52b4
    RadVel: Radial Velocity Fitting Toolkit: General Toolkit for Modeling Radial Velocities

    BJ Fulton, Erik Petigura, Sarah Blunt, and Evan Sinukoff

    RadVel is a tool designed to fit Keplerian orbits to radial velocity datasets. Multiple planets, multiple instruments, and multiple sources of white and red noise are supported out of the box. RadVel is written in an extensible object-oriented framework which allows for custom models, priors, or samplers.

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    https://emac.gsfc.nasa.gov#?related_resource=1826ad69-1ae1-4f54-acbd-3f567bdb52b4

    RadVel: Radial Velocity Fitting Toolkit: General Toolkit for Modeling Radial Velocities

    BJ Fulton, Erik Petigura, Sarah Blunt, and Evan Sinukoff

    RadVel is a tool designed to fit Keplerian orbits to radial velocity datasets. Multiple planets, multiple instruments, and multiple sources of white and red noise are supported out of the box. RadVel is written in an extensible object-oriented framework which allows for custom models, priors, or samplers.

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    https://emac.gsfc.nasa.gov#d4c93b0a-546a-4a66-b181-8ab6d64181a1
    SpaceHub: A high-performance gravity integration toolkit for few-body problems in astrophysics

    Yihan Wang, Nathan Leigh, Bin Liu and Rosalba Perna

    SpaceHub uses unique algorithms for fast, precise and accurate computations for few-body problems, ranging from interacting black holes to planetary dynamics. This few-body gravity integration toolkit can treat black hole dynamics with extreme mass ratios, extreme eccentricities and very close encounters. SpaceHub offers a bulk of regularized integrator and other cutting edge few body methods and can handle extremely eccentric orbits and close approaches in long-term integrations.

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    https://emac.gsfc.nasa.gov#?related_resource=d4c93b0a-546a-4a66-b181-8ab6d64181a1

    SpaceHub: A high-performance gravity integration toolkit for few-body problems in astrophysics

    Yihan Wang, Nathan Leigh, Bin Liu and Rosalba Perna

    SpaceHub uses unique algorithms for fast, precise and accurate computations for few-body problems, ranging from interacting black holes to planetary dynamics. This few-body gravity integration toolkit can treat black hole dynamics with extreme mass ratios, extreme eccentricities and very close encounters. SpaceHub offers a bulk of regularized integrator and other cutting edge few body methods and can handle extremely eccentric orbits and close approaches in long-term integrations.

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    https://emac.gsfc.nasa.gov#d430aa23-4db8-4f3d-8558-67d110bdac2d
    Astronet-Triage: A Neural Network for TESS Light Curve Triage

    Yu, L. et al.

    Astronet-Triage is a deep learning model capable of performing triage on TESS candidates. It is trained and tested on real TESS light curves and can distinguish transit-like signals (planet candidates and eclipsing binaries) from stellar variability and instrumental noise with an average precision of 97.0% and an accuracy of 97.4%. For the vetting version of this model, see Astronet Vetting.

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    https://emac.gsfc.nasa.gov#?related_resource=d430aa23-4db8-4f3d-8558-67d110bdac2d

    Astronet-Triage: A Neural Network for TESS Light Curve Triage

    Yu, L. et al.

    Astronet-Triage is a deep learning model capable of performing triage on TESS candidates. It is trained and tested on real TESS light curves and can distinguish transit-like signals (planet candidates and eclipsing binaries) from stellar variability and instrumental noise with an average precision of 97.0% and an accuracy of 97.4%. For the vetting version of this model, see Astronet Vetting.

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    https://emac.gsfc.nasa.gov?related_resource=e430c5de-b542-4a2f-ace9-00333a3f03a4
    FALCO: Wavefront Estimation and Control Software for Coronagraphs

    Riggs, A J Eldorado

    The Fast Linearized Coronagraph Optimizer (FALCO) is an open-source, modular software collection for the design, modeling, or testbed operation of coronagraphic optical systems. Users can build PROPER models of their optical systems and then use FALCO as a wrapper for performing wavefront correction simulations. FALCO contains working examples of published wavefront estimation and control techniques. The software can be easily ported to different testbeds and is already being used to run benches at Caltech and JPL.

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    https://emac.gsfc.nasa.gov#?related_resource=e430c5de-b542-4a2f-ace9-00333a3f03a4

    FALCO: Wavefront Estimation and Control Software for Coronagraphs

    Riggs, A J Eldorado

    The Fast Linearized Coronagraph Optimizer (FALCO) is an open-source, modular software collection for the design, modeling, or testbed operation of coronagraphic optical systems. Users can build PROPER models of their optical systems and then use FALCO as a wrapper for performing wavefront correction simulations. FALCO contains working examples of published wavefront estimation and control techniques. The software can be easily ported to different testbeds and is already being used to run benches at Caltech and JPL.

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    https://emac.gsfc.nasa.gov#820ff968-92a2-4d8b-93ac-297978b2599a
    exoscene: A Python library for simulating direct images of exoplanetary systems

    Zimmerman, Neil

    exoscene is a library of classes and utility functions for simulating direct images of exoplanetary systems. The package was developed by Neil Zimmerman (NASA/GSFC), with source code contributions from Maxime Rizzo, Christopher Stark, and Ell Bogat. This work was funded in part by a WFIRST/Roman Science Investigation Team contract (PI: Margaret Turnbull).

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    https://emac.gsfc.nasa.gov#?related_resource=820ff968-92a2-4d8b-93ac-297978b2599a

    exoscene: A Python library for simulating direct images of exoplanetary systems

    Zimmerman, Neil

    exoscene is a library of classes and utility functions for simulating direct images of exoplanetary systems. The package was developed by Neil Zimmerman (NASA/GSFC), with source code contributions from Maxime Rizzo, Christopher Stark, and Ell Bogat. This work was funded in part by a WFIRST/Roman Science Investigation Team contract (PI: Margaret Turnbull).

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    https://emac.gsfc.nasa.gov#f0789a22-abf3-467e-8d74-503d14e677df
    ESO SkyCalc: Web and API interface to The Cerro Paranal Advanced Sky Model

    Noll et al. (2012, A&A 543, A92) and Jones et al. (2013, A&A 560, A91)

    SkyCalc is a web application based on the Cerro Paranal Advanced Sky Model, which was developed in particular to be used in the ESO Exposure Time Calculators, by a team of astronomers at the Institute for Astro- and Particle Physics at the University of Innsbruck, as part of an Austrian in-kind contribution to ESO. A command-line tool skycalc_cli is available to execute the SkyCalc backend engine through an API. The C source code is available to download.

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    https://emac.gsfc.nasa.gov#?related_resource=f0789a22-abf3-467e-8d74-503d14e677df

    ESO SkyCalc: Web and API interface to The Cerro Paranal Advanced Sky Model

    Noll et al. (2012, A&A 543, A92) and Jones et al. (2013, A&A 560, A91)

    SkyCalc is a web application based on the Cerro Paranal Advanced Sky Model, which was developed in particular to be used in the ESO Exposure Time Calculators, by a team of astronomers at the Institute for Astro- and Particle Physics at the University of Innsbruck, as part of an Austrian in-kind contribution to ESO. A command-line tool skycalc_cli is available to execute the SkyCalc backend engine through an API. The C source code is available to download.

    Demo
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    https://emac.gsfc.nasa.gov#1b3ed3dc-6b84-4717-9f7d-8519236bd12d
    pyLIMA: Microlensing Modeling and Simulation

    Bachelet, E. et al.

    The python Lightcurve Identification and Microlensing Analysis (pyLIMA) is the first microlensing software fully open-source. Motivated by the data deluge that the Roman telescope microlensing survey will collect, it is designed to allow easy and efficient modeling of microlensing data (including parallalization), but is also capable of simulations. It is mainly written in python and object oriented. The codes contains lot of examples, a complete documentation and is continuously developed.

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    https://emac.gsfc.nasa.gov#?related_resource=1b3ed3dc-6b84-4717-9f7d-8519236bd12d

    pyLIMA: Microlensing Modeling and Simulation

    Bachelet, E. et al.

    The python Lightcurve Identification and Microlensing Analysis (pyLIMA) is the first microlensing software fully open-source. Motivated by the data deluge that the Roman telescope microlensing survey will collect, it is designed to allow easy and efficient modeling of microlensing data (including parallalization), but is also capable of simulations. It is mainly written in python and object oriented. The codes contains lot of examples, a complete documentation and is continuously developed.

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    https://emac.gsfc.nasa.gov#50f4454d-7b16-44f0-ab53-f47810ac0a04
    RVLIN: A Fast Maximum Likelihood Method for Fitting Multiplanet Keplerian Curves to RV Data Coded in IDL

    Jason Wright and Andrew Howard

    An IDL routine for fitting multiple Keplerian curves (i.e. those that neglect planet-planet interactions) to radial velocity data. Handles heteroschedastic data, and constraints on P, e, phase, and transit timing. It is fast because it solves, via maximum likelihood, for all parameters other than P, e, and phase with a linear least-squares matrix inversion. It then determines the remaining 3*n parameters (where n is the number of planets) via a Levenberg-Marquardt optimization. The method is described in Wright & Howard ApJS 182, 205. Uncertainties in the fitted parameters can be determined via bootstrapping using BOOTTRAN (Wang et al. ApJ 761, 46).

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    https://emac.gsfc.nasa.gov#?related_resource=50f4454d-7b16-44f0-ab53-f47810ac0a04

    RVLIN: A Fast Maximum Likelihood Method for Fitting Multiplanet Keplerian Curves to RV Data Coded in IDL

    Jason Wright and Andrew Howard

    An IDL routine for fitting multiple Keplerian curves (i.e. those that neglect planet-planet interactions) to radial velocity data. Handles heteroschedastic data, and constraints on P, e, phase, and transit timing. It is fast because it solves, via maximum likelihood, for all parameters other than P, e, and phase with a linear least-squares matrix inversion. It then determines the remaining 3*n parameters (where n is the number of planets) via a Levenberg-Marquardt optimization. The method is described in Wright & Howard ApJS 182, 205. Uncertainties in the fitted parameters can be determined via bootstrapping using BOOTTRAN (Wang et al. ApJ 761, 46).

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    https://emac.gsfc.nasa.gov#02c2ff7c-e509-4914-8ca5-17be6c8c0c31
    ExoplAn3T: Exoplanet Analysis and 3D visualization Tool

    Zinzi, A.; Turrini, D.; Alei E.; Verrecchia F.

    ExoplAn3T is the SSDC scientific webtool providing access to several on-line exoplanet catalogues (i.e., NASA Exoplanetary Archive, The Extrasolar Planet Encyclopedia and ExoMerCat) and is designed and optimized for the study of exoplanetary systems as a whole, rather than to extract information on single planets. The tool applies a two step procedure: a "planetary query", aimed at finding exoplanets having the characteristics required by the user and a series of "system queries" (one query for every exosystem found in the first step) looking for all the planets belonging to each exosystem in which the exoplanets of the "planetary query" are found.

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    https://emac.gsfc.nasa.gov#?related_resource=02c2ff7c-e509-4914-8ca5-17be6c8c0c31

    ExoplAn3T: Exoplanet Analysis and 3D visualization Tool

    Zinzi, A.; Turrini, D.; Alei E.; Verrecchia F.

    ExoplAn3T is the SSDC scientific webtool providing access to several on-line exoplanet catalogues (i.e., NASA Exoplanetary Archive, The Extrasolar Planet Encyclopedia and ExoMerCat) and is designed and optimized for the study of exoplanetary systems as a whole, rather than to extract information on single planets. The tool applies a two step procedure: a "planetary query", aimed at finding exoplanets having the characteristics required by the user and a series of "system queries" (one query for every exosystem found in the first step) looking for all the planets belonging to each exosystem in which the exoplanets of the "planetary query" are found.

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    https://emac.gsfc.nasa.gov#7e7481e3-406e-430f-a476-0baac6e69f7e
    Gemini Planet Imager Data Reduction Pipeline: Official data reduction pipeline for the GPI instrument integral field spectrograph

    M. Perrin, J. Maire and the GPI Data Analysis Team (see: http://docs.planetimager.org/pipeline/developers/credits.html)

    The Gemini Planet Imager Data Pipeline allows transformation of raw data from GPI into calibrated spectral and polarimetric data cubes. It also provides some basic capabilities for PSF suppression through differential imaging, and for astrometry and spectrophotometry of detected sources. See complete documentation here.

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    https://emac.gsfc.nasa.gov#?related_resource=7e7481e3-406e-430f-a476-0baac6e69f7e

    Gemini Planet Imager Data Reduction Pipeline: Official data reduction pipeline for the GPI instrument integral field spectrograph

    M. Perrin, J. Maire and the GPI Data Analysis Team (see: http://docs.planetimager.org/pipeline/developers/credits.html)

    The Gemini Planet Imager Data Pipeline allows transformation of raw data from GPI into calibrated spectral and polarimetric data cubes. It also provides some basic capabilities for PSF suppression through differential imaging, and for astrometry and spectrophotometry of detected sources. See complete documentation here.

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    https://emac.gsfc.nasa.gov#1f2538dd-5c28-49d2-96ff-8ae4839dac12
    Habitable-exoplanets-visualisation: Visualization of the NASA Exoplanets Archive open data of exoplanets that are similar to the Earth.

    Ermishin Andrey

    Visualization of the open data from the NASA Exoplanets Archive of planets outside the solar system that are similar to the Earth and habitable. By means of NASA API exoplanets were parsed and stored to SQLite database: "content.sqlite". There are two visualizations of the parsed data: - Python 3 file "khistogram.py" samples data into "khistogram.js" which is used by "khistogram.htm" to visualize data with D3.js library; - Python 3 file"kbchart.py" samples data into "kbchart.js" which is used by "kbchart.htm" to visualize data with Google BubbleChart.

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    https://emac.gsfc.nasa.gov#?related_resource=1f2538dd-5c28-49d2-96ff-8ae4839dac12

    Habitable-exoplanets-visualisation: Visualization of the NASA Exoplanets Archive open data of exoplanets that are similar to the Earth.

    Ermishin Andrey

    Visualization of the open data from the NASA Exoplanets Archive of planets outside the solar system that are similar to the Earth and habitable. By means of NASA API exoplanets were parsed and stored to SQLite database: "content.sqlite". There are two visualizations of the parsed data: - Python 3 file "khistogram.py" samples data into "khistogram.js" which is used by "khistogram.htm" to visualize data with D3.js library; - Python 3 file"kbchart.py" samples data into "kbchart.js" which is used by "kbchart.htm" to visualize data with Google BubbleChart.

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    https://emac.gsfc.nasa.gov#88f2a333-d081-4bcd-908d-14c4d8cf702f
    HARDCORE Web Interface

    Yosef Miller

    The HARDCORE Web Interface tool is a user-friendly web-based application of HARDCORE. This tool allows users to easily calculate minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet based on mass and radius limits.

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    https://emac.gsfc.nasa.gov#?related_resource=88f2a333-d081-4bcd-908d-14c4d8cf702f

    HARDCORE Web Interface

    Yosef Miller

    The HARDCORE Web Interface tool is a user-friendly web-based application of HARDCORE. This tool allows users to easily calculate minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet based on mass and radius limits.

    Demo
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    https://emac.gsfc.nasa.gov#b58496a5-05ee-47d2-af17-2f6cbc45b9fc
    ARTES: Radiative transfer of polarized light in 3D exoplanet atmospheres

    Tomas Stolker

    ARTES is a 3D Monte Carlo radiative transfer code for polarized scattered light simulations of exoplanet atmospheres. The code can be used for post-processing of a pre-calculated or parametrized atmosphere structure. Multiple scattering, absorption, and polarization are fully treated and the output includes an image, spectrum, or phase curve of reflected stellar light or thermal photons. Several tools are included for calculating opacities and scattering matrices of molecules and clouds but the user can also adopt their own opacities.

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    https://emac.gsfc.nasa.gov#?related_resource=b58496a5-05ee-47d2-af17-2f6cbc45b9fc

    ARTES: Radiative transfer of polarized light in 3D exoplanet atmospheres

    Tomas Stolker

    ARTES is a 3D Monte Carlo radiative transfer code for polarized scattered light simulations of exoplanet atmospheres. The code can be used for post-processing of a pre-calculated or parametrized atmosphere structure. Multiple scattering, absorption, and polarization are fully treated and the output includes an image, spectrum, or phase curve of reflected stellar light or thermal photons. Several tools are included for calculating opacities and scattering matrices of molecules and clouds but the user can also adopt their own opacities.

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    https://emac.gsfc.nasa.gov#dae31f6b-a353-4ebf-ac2a-39d4ccb89a2d
    TTVFaster: First Order Eccentricity Transit Timing Variations (TTVs)

    Agol & Deck (2016)

    Analytic model for transit-timing variations which is accurate to first order in eccentricity and mass-ratio.

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    https://emac.gsfc.nasa.gov#?related_resource=dae31f6b-a353-4ebf-ac2a-39d4ccb89a2d

    TTVFaster: First Order Eccentricity Transit Timing Variations (TTVs)

    Agol & Deck (2016)

    Analytic model for transit-timing variations which is accurate to first order in eccentricity and mass-ratio.

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    https://emac.gsfc.nasa.gov#40ae4b41-5d95-4d54-a052-59fdcc9d026b
    Exorings: Python Tools for Displaying and Fitting Giant Extrasolar Planet Ring Systems

    M. Kenworthy

    Exorings is a Python 3 package that simulates giant Hill sphere ring systems, and generates the resultant light curve when a star passes behind the rings. The star and rings are modelled on a Cartesian grid with no optimisation for calculation speed. The module can create plots of the ring system using vector graphics in a PDF suitable for publications. There is an interactive ring fitting code that allows manual addition and removal of ring edges and optical depths, with Amoeba optimization for the ring transmissions. The rings are saved in a FITS table with ring system metadata.

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    https://emac.gsfc.nasa.gov#?related_resource=40ae4b41-5d95-4d54-a052-59fdcc9d026b

    Exorings: Python Tools for Displaying and Fitting Giant Extrasolar Planet Ring Systems

    M. Kenworthy

    Exorings is a Python 3 package that simulates giant Hill sphere ring systems, and generates the resultant light curve when a star passes behind the rings. The star and rings are modelled on a Cartesian grid with no optimisation for calculation speed. The module can create plots of the ring system using vector graphics in a PDF suitable for publications. There is an interactive ring fitting code that allows manual addition and removal of ring edges and optical depths, with Amoeba optimization for the ring transmissions. The rings are saved in a FITS table with ring system metadata.

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    https://emac.gsfc.nasa.gov?related_resource=bd857f5b-cc9a-4ae4-a7ad-b2e506e54740
    EDI-Vetter Unplugged: Transit Signal False Positive Vetting Tool

    Zink, J. K.

    This program was originally designed to identify false positive transit signals in K2 photometry, but has been modified to play nicely with the Transit Least Squares software package. It contains several thresholds which mimic visual inspection and help automate the transit detection process.

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    https://emac.gsfc.nasa.gov#?related_resource=bd857f5b-cc9a-4ae4-a7ad-b2e506e54740

    EDI-Vetter Unplugged: Transit Signal False Positive Vetting Tool

    Zink, J. K.

    This program was originally designed to identify false positive transit signals in K2 photometry, but has been modified to play nicely with the Transit Least Squares software package. It contains several thresholds which mimic visual inspection and help automate the transit detection process.

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    https://emac.gsfc.nasa.gov#0b8381f1-897c-40db-8aca-06b55541ccb5
    SWEET-Cat: A catalog of stellar parameters for stars with planets

    Planet team at the Instituto de Astrofísica e Ciências do Espaço

    A catalog of atmospheric parameters for planet-host stars. It compiles sets of atmospheric parameters previously published in literature (including Teff, logg, and [Fe / H]) and, whenever possible, derives them using the same uniform methodology.

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    https://emac.gsfc.nasa.gov#?related_resource=0b8381f1-897c-40db-8aca-06b55541ccb5

    SWEET-Cat: A catalog of stellar parameters for stars with planets

    Planet team at the Instituto de Astrofísica e Ciências do Espaço

    A catalog of atmospheric parameters for planet-host stars. It compiles sets of atmospheric parameters previously published in literature (including Teff, logg, and [Fe / H]) and, whenever possible, derives them using the same uniform methodology.

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    https://emac.gsfc.nasa.gov#067ca9ad-34f6-407c-9daf-afd686c6349b
    MCMCI: MCMC-based analysis of light curves or RV time series with interpolation within stellar isochrones

    Bonfanti A., Gillon M.

    The MCMCI tool offers the opportunity to perform an integrated analysis of an exoplanetary system without splitting it into the preliminary stellar characterisation through theoretical models.The MCMCI combines the Markov chain Monte Carlo approach of analysing photometric or radial velocity time series with a proper interpolation within stellar evolutionary isochrones and tracks, to be performed at each chain step, to retrieve stellar theoretical parameters such as age, mass, and radius. This approach favours a close interaction between lightcurve analysis and isochrones, so that the parameters recovered at each step of the MCMC enter as inputs for purposes of the isochrone placement.

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    https://emac.gsfc.nasa.gov#?related_resource=067ca9ad-34f6-407c-9daf-afd686c6349b

    MCMCI: MCMC-based analysis of light curves or RV time series with interpolation within stellar isochrones

    Bonfanti A., Gillon M.

    The MCMCI tool offers the opportunity to perform an integrated analysis of an exoplanetary system without splitting it into the preliminary stellar characterisation through theoretical models.The MCMCI combines the Markov chain Monte Carlo approach of analysing photometric or radial velocity time series with a proper interpolation within stellar evolutionary isochrones and tracks, to be performed at each chain step, to retrieve stellar theoretical parameters such as age, mass, and radius. This approach favours a close interaction between lightcurve analysis and isochrones, so that the parameters recovered at each step of the MCMC enter as inputs for purposes of the isochrone placement.

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    https://emac.gsfc.nasa.gov#e5536d0e-c784-4d4b-8999-da5add804a5a
    PlanetSlicer: Phase Curve Fitting for Emission and Reflection via the Orange Slice Model

    Thorngren, Daniel P.; Mayorga, Laura C.

    This is a small package for fitting brightness maps to phase curves using the "orange-slice" method. For self-luminous objects, this follows Cowan and Agol (2008) "Inverting Phase Functions to Map Exoplanets". We have extended this approach to diffuse reflected light assuming Lambertian reflectance, in Mayorga et. al (2020). In both cases, the model supposes that a spherical object can be divided into slices of constant brightness (or albedo) which may be integrated to yield the total flux observed, given the angles of observation.

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    https://emac.gsfc.nasa.gov#?related_resource=e5536d0e-c784-4d4b-8999-da5add804a5a

    PlanetSlicer: Phase Curve Fitting for Emission and Reflection via the Orange Slice Model

    Thorngren, Daniel P.; Mayorga, Laura C.

    This is a small package for fitting brightness maps to phase curves using the "orange-slice" method. For self-luminous objects, this follows Cowan and Agol (2008) "Inverting Phase Functions to Map Exoplanets". We have extended this approach to diffuse reflected light assuming Lambertian reflectance, in Mayorga et. al (2020). In both cases, the model supposes that a spherical object can be divided into slices of constant brightness (or albedo) which may be integrated to yield the total flux observed, given the angles of observation.

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    https://emac.gsfc.nasa.gov#9e864265-ebde-4354-9c02-025f64c28150
    kima: Exoplanet detection in RVs with DNest4 and GPs

    Faria et al. 2018, JOSS, 3, 487

    kima is a package for the detection and characterization of exoplanets using RV data. It fits a sum of Keplerian curves to a time series of RV measurements and calculates the evidence for models with a fixed number Np of Keplerian signals, or after marginalising over Np. A Gaussian process with a quasi-periodic kernel can be used as a noise model, to deal with activity-induced signals. The hyperparameters of the GP are inferred together with the orbital parameters. The code is written in C++ and includes a helper Python package, pykima, which facilitates the analysis of the results.

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    https://emac.gsfc.nasa.gov#?related_resource=9e864265-ebde-4354-9c02-025f64c28150

    kima: Exoplanet detection in RVs with DNest4 and GPs

    Faria et al. 2018, JOSS, 3, 487

    kima is a package for the detection and characterization of exoplanets using RV data. It fits a sum of Keplerian curves to a time series of RV measurements and calculates the evidence for models with a fixed number Np of Keplerian signals, or after marginalising over Np. A Gaussian process with a quasi-periodic kernel can be used as a noise model, to deal with activity-induced signals. The hyperparameters of the GP are inferred together with the orbital parameters. The code is written in C++ and includes a helper Python package, pykima, which facilitates the analysis of the results.

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    https://emac.gsfc.nasa.gov#417d1844-72d9-4614-b200-9d6f606c0b77
    ShellSpec: Lightcurves, spectra and images of binaries and exoplanets with moving circum-object material

    Jan Budaj

    Program SHELLSPEC is designed to calculate lightcurves, spectra and images of interacting binaries and extrasolar planets immersed in a moving circumstellar matter (CM). It solves a simple radiative transfer along the line of sight in 3D moving CM. Roche model with a reflection effect and synthetic spectra from the stellar atmosphere models can be used as a boundary condition for the radiative transfer. Dust, including non-isotropic Mie scattering, can also be taken into account. The assumptions include LTE and optional known state quantities and velocity fields in 3D.

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    https://emac.gsfc.nasa.gov#?related_resource=417d1844-72d9-4614-b200-9d6f606c0b77

    ShellSpec: Lightcurves, spectra and images of binaries and exoplanets with moving circum-object material

    Jan Budaj

    Program SHELLSPEC is designed to calculate lightcurves, spectra and images of interacting binaries and extrasolar planets immersed in a moving circumstellar matter (CM). It solves a simple radiative transfer along the line of sight in 3D moving CM. Roche model with a reflection effect and synthetic spectra from the stellar atmosphere models can be used as a boundary condition for the radiative transfer. Dust, including non-isotropic Mie scattering, can also be taken into account. The assumptions include LTE and optional known state quantities and velocity fields in 3D.

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    https://emac.gsfc.nasa.gov#45fa4b5c-c189-437a-b5ef-b312e982a32e
    EXOCROSS: A general program for generating spectra from molecular line lists

    ExoCross is a Fortran code for generating spectra (emission, absorption) and thermodynamic properties (partition function, specific heat etc.) from molecular line lists including ExoMol and HITRAN. Input is taken in several formats, including ExoMol and HITRAN formats. ExoCross can work with several line profiles such as Doppler, Lorentzian and Voigt and support several broadening schemes. ExoCross supports calculations of lifetimes, cooling functions, specific heats and other properties. It is capable of simulating non-LTE spectra using a two-temperature approach as well as custom-built models.

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    https://emac.gsfc.nasa.gov#?related_resource=45fa4b5c-c189-437a-b5ef-b312e982a32e

    EXOCROSS: A general program for generating spectra from molecular line lists

    ExoCross is a Fortran code for generating spectra (emission, absorption) and thermodynamic properties (partition function, specific heat etc.) from molecular line lists including ExoMol and HITRAN. Input is taken in several formats, including ExoMol and HITRAN formats. ExoCross can work with several line profiles such as Doppler, Lorentzian and Voigt and support several broadening schemes. ExoCross supports calculations of lifetimes, cooling functions, specific heats and other properties. It is capable of simulating non-LTE spectra using a two-temperature approach as well as custom-built models.

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    https://emac.gsfc.nasa.gov#b89cf8e5-d7a4-4669-af63-5156852d3b29
    Spotrod: A Semi-analytic Model for Transits of Spotted Stars

    Bence Béky; David M. Kipping; Matthew J. Holman

    A library for numerical simulation of transit lightcurves for a planet transiting a star with homogeneous, circular spots. Homogeneous umbra and homogeneous penumbra can be modelled using two concentric spots. Written in C, with Python bindings.

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    https://emac.gsfc.nasa.gov#?related_resource=b89cf8e5-d7a4-4669-af63-5156852d3b29

    Spotrod: A Semi-analytic Model for Transits of Spotted Stars

    Bence Béky; David M. Kipping; Matthew J. Holman

    A library for numerical simulation of transit lightcurves for a planet transiting a star with homogeneous, circular spots. Homogeneous umbra and homogeneous penumbra can be modelled using two concentric spots. Written in C, with Python bindings.

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    https://emac.gsfc.nasa.gov#2f8ed766-5614-4e70-a0e6-ff39fb2da8ea
    MAYONNAISE processing pipeline: A morphological components analysis pipeline for circumstellar disks and exoplanets imaging

    Pairet, B. et al.

    MAYO is a pipeline for exoplanet and disk high-contrast imaging from ADI datasets. For more information, please refer to Pairet, Benoît, Faustine Cantalloube, and Laurent Jacques. "MAYONNAISE: a morphological components analysis pipeline for circumstellar disks and exoplanets imaging in the near infrared.", Monthly Notices of the Royal Astronomical Society, 2021.

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    https://emac.gsfc.nasa.gov#?related_resource=2f8ed766-5614-4e70-a0e6-ff39fb2da8ea

    MAYONNAISE processing pipeline: A morphological components analysis pipeline for circumstellar disks and exoplanets imaging

    Pairet, B. et al.

    MAYO is a pipeline for exoplanet and disk high-contrast imaging from ADI datasets. For more information, please refer to Pairet, Benoît, Faustine Cantalloube, and Laurent Jacques. "MAYONNAISE: a morphological components analysis pipeline for circumstellar disks and exoplanets imaging in the near infrared.", Monthly Notices of the Royal Astronomical Society, 2021.

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    https://emac.gsfc.nasa.gov#8e7d903e-62c4-4b08-89dd-c890deaf0163
    VARTOOLS: Command-line program for analyzing astronomical time-series data

    Hartman, J.D. and Bakos, G.A.

    The VARTOOLS program is a command line utility that provides tools for processing and analyzing astronomical time series data, especially light curves. It includes methods for calculating variability/periodicity statistics of light curves; for filtering, transforming, and otherwise modifying light curves; and for modeling light curves. It is intended primarily for batch processing a large number of light curves. The program is run by issuing a sequence of commands to perform actions on light curves, each command is executed in turn with the resulting light curves passed to the next command. Statistics computed by each command are sent to stdout as an ascii table.

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    https://emac.gsfc.nasa.gov#?related_resource=8e7d903e-62c4-4b08-89dd-c890deaf0163

    VARTOOLS: Command-line program for analyzing astronomical time-series data

    Hartman, J.D. and Bakos, G.A.

    The VARTOOLS program is a command line utility that provides tools for processing and analyzing astronomical time series data, especially light curves. It includes methods for calculating variability/periodicity statistics of light curves; for filtering, transforming, and otherwise modifying light curves; and for modeling light curves. It is intended primarily for batch processing a large number of light curves. The program is run by issuing a sequence of commands to perform actions on light curves, each command is executed in turn with the resulting light curves passed to the next command. Statistics computed by each command are sent to stdout as an ascii table.

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    https://emac.gsfc.nasa.gov#9174d5cd-7064-4048-b321-b97d3ef46229
    Kepler DR25 Robovetter: Automatic vetting of Kepler DR25 TCEs into Planet Candidates and False Positives

    Thompson et al. 2018, ApJS, 235, 38

    The DR25 Kepler Robovetter is a robotic decision-making code that dispositions each Threshold Crossing Event (TCE) from the Kepler pipeline into Planet Candidates (PCs) and False Positives (FPs). The Robovetter also provides four major flags to designate each FP TCE as Not Transit-Like (NTL), a Stellar Eclipse (SS), a Centroid Offset (CO), and/or an Ephemeris Match (EM). It also produces a score ranging from 0.0 to 1.0 that indicates the Robovetter's disposition confidence, where 1.0 indicates strong confidence in PC, and 0.0 indicates strong confidence in FP. Finally, the Robovetter provides comments in a text string that indicate the specific tests each FP TCE fails.

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    https://emac.gsfc.nasa.gov#?related_resource=9174d5cd-7064-4048-b321-b97d3ef46229

    Kepler DR25 Robovetter: Automatic vetting of Kepler DR25 TCEs into Planet Candidates and False Positives

    Thompson et al. 2018, ApJS, 235, 38

    The DR25 Kepler Robovetter is a robotic decision-making code that dispositions each Threshold Crossing Event (TCE) from the Kepler pipeline into Planet Candidates (PCs) and False Positives (FPs). The Robovetter also provides four major flags to designate each FP TCE as Not Transit-Like (NTL), a Stellar Eclipse (SS), a Centroid Offset (CO), and/or an Ephemeris Match (EM). It also produces a score ranging from 0.0 to 1.0 that indicates the Robovetter's disposition confidence, where 1.0 indicates strong confidence in PC, and 0.0 indicates strong confidence in FP. Finally, the Robovetter provides comments in a text string that indicate the specific tests each FP TCE fails.

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    https://emac.gsfc.nasa.gov#58a2ed5a-3a57-4197-b8bf-40b06283616c
    ChromaStarPy: Transit light-curve modelling integrated with stellar atmosphere and surface intensity modeling

    Short, C. Ian and Bennett, Philip D.

    An approximate stellar atmosphere and spectrum modelling code in Python that includes in situ modelling of the transit light-curve due to a "small" exo-planet occulting the computed stellar surface intensity distribution.

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    https://emac.gsfc.nasa.gov#?related_resource=58a2ed5a-3a57-4197-b8bf-40b06283616c

    ChromaStarPy: Transit light-curve modelling integrated with stellar atmosphere and surface intensity modeling

    Short, C. Ian and Bennett, Philip D.

    An approximate stellar atmosphere and spectrum modelling code in Python that includes in situ modelling of the transit light-curve due to a "small" exo-planet occulting the computed stellar surface intensity distribution.

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    https://emac.gsfc.nasa.gov#d327f553-28a0-4a6a-86df-4898a6e04d76
    SPInS: Stellar Parameters INferred Systematically

    Reese, D. R. and Lebreton, Y.

    SPInS is a Python tool that takes in a set of photometric, spectroscopic, interferometric, and/or global asteroseismic observational constraints, and uses a Bayesian approach to find the probability distribution functions of stellar parameters, such as the age, mass, and radius of a star, as well as error bars and correlations between these parameters. At the heart of the code is a Markov chain Monte Carlo solver coupled with interpolation within a pre-computed grid of stellar models. Priors can be considered, such as the initial mass function or the stellar formation rate. SPInS can characterize single stars or coeval stars, such as members of binary systems or of stellar clusters.

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    https://emac.gsfc.nasa.gov#?related_resource=d327f553-28a0-4a6a-86df-4898a6e04d76

    SPInS: Stellar Parameters INferred Systematically

    Reese, D. R. and Lebreton, Y.

    SPInS is a Python tool that takes in a set of photometric, spectroscopic, interferometric, and/or global asteroseismic observational constraints, and uses a Bayesian approach to find the probability distribution functions of stellar parameters, such as the age, mass, and radius of a star, as well as error bars and correlations between these parameters. At the heart of the code is a Markov chain Monte Carlo solver coupled with interpolation within a pre-computed grid of stellar models. Priors can be considered, such as the initial mass function or the stellar formation rate. SPInS can characterize single stars or coeval stars, such as members of binary systems or of stellar clusters.

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    https://emac.gsfc.nasa.gov#9e3a6174-9a26-437a-a4f9-4fefa1687494
    VLT-sphere: Automatic VLT/SPHERE data reduction and analysis

    Arthur Vigan

    The high-contrast imager SPHERE at the Very Large Telescope combines extreme adaptive optics and coronagraphy to directly image exoplanets in the near-infrared. The vlt-sphere package enables easy reduction of the data coming from IRDIS and IFS, the two near-infrared subsystems of SPHERE. The package relies on the official ESO pipeline (ascl:1402.010), which must be installed separately.

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    https://emac.gsfc.nasa.gov#?related_resource=9e3a6174-9a26-437a-a4f9-4fefa1687494

    VLT-sphere: Automatic VLT/SPHERE data reduction and analysis

    Arthur Vigan

    The high-contrast imager SPHERE at the Very Large Telescope combines extreme adaptive optics and coronagraphy to directly image exoplanets in the near-infrared. The vlt-sphere package enables easy reduction of the data coming from IRDIS and IFS, the two near-infrared subsystems of SPHERE. The package relies on the official ESO pipeline (ascl:1402.010), which must be installed separately.

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    https://emac.gsfc.nasa.gov?related_resource=c9539dbb-fd84-4eeb-8606-3cb2440edffb
    ATMO: 1D-2D radiative/convective atmospheric code

    Tremblin P. et al. (see description)

    ATMO is a 1D-2D atmospheric code for the study of the atmosphere of brown dwarfs and exoplanets. The code has originally been developed at the University of Exeter (here) and is currently a collaboration between different groups across the globe. The main developers are: 1D and 2D newton solver: P. Tremblin Radiative transfer: D. Amundsen, P. Tremblin Opacities: D. Amundsen, M. Phillips, R. Ridgway, J. Goyal Equilibrium chemistry: P. Tremblin, B. Drummond, J. Goyal Condensation and rainouts: P. Tremblin, J. Goyal Out-of-equilibrium chemistry: O. Venot, E. Hebrard, B. Drummond Convection: P. Tremblin, M. Phillips Retrieval: D. Sing

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    https://emac.gsfc.nasa.gov#?related_resource=c9539dbb-fd84-4eeb-8606-3cb2440edffb

    ATMO: 1D-2D radiative/convective atmospheric code

    Tremblin P. et al. (see description)

    ATMO is a 1D-2D atmospheric code for the study of the atmosphere of brown dwarfs and exoplanets. The code has originally been developed at the University of Exeter (here) and is currently a collaboration between different groups across the globe. The main developers are: 1D and 2D newton solver: P. Tremblin Radiative transfer: D. Amundsen, P. Tremblin Opacities: D. Amundsen, M. Phillips, R. Ridgway, J. Goyal Equilibrium chemistry: P. Tremblin, B. Drummond, J. Goyal Condensation and rainouts: P. Tremblin, J. Goyal Out-of-equilibrium chemistry: O. Venot, E. Hebrard, B. Drummond Convection: P. Tremblin, M. Phillips Retrieval: D. Sing

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    https://emac.gsfc.nasa.gov#8d8f1412-bd94-44db-8b2c-748e9bbeb5c8
    The Joker: A custom Monte Carlo sampler for the two-body problem

    A. Price-Whelan, D. W. Hogg, D. Foreman-Mackey

    The Joker is a custom Monte Carlo sampler for the two-body problem that generates posterior samplings in Keplerian orbital parameters given radial velocity observations of stars. It is designed to deliver converged posterior samplings even when the radial velocity measurements are sparse or very noisy. It is therefore useful for constraining the orbital properties of binary star or star-planet systems. Though it fundamentally assumes that any system has two massive bodies (and only the primary is observed), The Joker can also be used for hierarchical systems in which the velocity perturbations from a third or other bodies are much longer than the dominant companion.

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    https://emac.gsfc.nasa.gov#?related_resource=8d8f1412-bd94-44db-8b2c-748e9bbeb5c8

    The Joker: A custom Monte Carlo sampler for the two-body problem

    A. Price-Whelan, D. W. Hogg, D. Foreman-Mackey

    The Joker is a custom Monte Carlo sampler for the two-body problem that generates posterior samplings in Keplerian orbital parameters given radial velocity observations of stars. It is designed to deliver converged posterior samplings even when the radial velocity measurements are sparse or very noisy. It is therefore useful for constraining the orbital properties of binary star or star-planet systems. Though it fundamentally assumes that any system has two massive bodies (and only the primary is observed), The Joker can also be used for hierarchical systems in which the velocity perturbations from a third or other bodies are much longer than the dominant companion.

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    https://emac.gsfc.nasa.gov#c4a1dacd-ccea-4949-a2c8-49f36ce12443
    EvapMass: Minimum mass of planets predictor

    Owen, James E. & Campos Estrada, Beatriz

    EvapMass predicts the minimum masses of planets in multi-planet systems using the photoevaporation-driven evolution model. The planetary system requires both a planet above and below the radius gap to be useful for this test. EvapMass includes an example Jupyter notebook for the Kepler-36 system. EvalMass can be used to identify TESS systems that warrant radial-velocity follow-up to further test the photoevaporation model.

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    https://emac.gsfc.nasa.gov#?related_resource=c4a1dacd-ccea-4949-a2c8-49f36ce12443

    EvapMass: Minimum mass of planets predictor

    Owen, James E. & Campos Estrada, Beatriz

    EvapMass predicts the minimum masses of planets in multi-planet systems using the photoevaporation-driven evolution model. The planetary system requires both a planet above and below the radius gap to be useful for this test. EvapMass includes an example Jupyter notebook for the Kepler-36 system. EvalMass can be used to identify TESS systems that warrant radial-velocity follow-up to further test the photoevaporation model.

    Demo
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    https://emac.gsfc.nasa.gov#d6c03807-8345-4a3b-9372-73210b586e66
    Lightkurve Web Interface: Easy to use Web Interface of the Lightkurve Python Package

    Yosef Miller

    The Lightkurve Web Interface tool is a user-friendly web-based application of the Lightkurve python package. This tool allows users to quickly produce light curves based on time series data obtained by NASA's Kepler, K2, and TESS missions.

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    https://emac.gsfc.nasa.gov#?related_resource=d6c03807-8345-4a3b-9372-73210b586e66

    Lightkurve Web Interface: Easy to use Web Interface of the Lightkurve Python Package

    Yosef Miller

    The Lightkurve Web Interface tool is a user-friendly web-based application of the Lightkurve python package. This tool allows users to quickly produce light curves based on time series data obtained by NASA's Kepler, K2, and TESS missions.

    About Demo
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    https://emac.gsfc.nasa.gov#50c94d49-ba15-490f-b741-b04aa50ede78
    Stella: Convolutional Neural Networks for Flare Identification in TESS 2-minute Data

    Feinstein et al. 2020a,b

    The purpose of stella is to identify flares in TESS short-cadence data with a convolutional neural network (CNN). In its simplest form, stella takes a pre-trained CNN (available on MAST: https://archive.stsci.edu/hlsp/stella) and a light curve (time, flux, and flux error) and returns a probability light curve. The cadences in the probability light curve are values between 0 and 1, where 1 means the CNN believes there is a flare there. It takes < 1 minute to predict flares on a single light curve. Users also have the ability the train their own customized CNN architecture. The stella software also includes modules to measure rotation periods and fit flares using simple exponential models.

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    https://emac.gsfc.nasa.gov#?related_resource=50c94d49-ba15-490f-b741-b04aa50ede78

    Stella: Convolutional Neural Networks for Flare Identification in TESS 2-minute Data

    Feinstein et al. 2020a,b

    The purpose of stella is to identify flares in TESS short-cadence data with a convolutional neural network (CNN). In its simplest form, stella takes a pre-trained CNN (available on MAST: https://archive.stsci.edu/hlsp/stella) and a light curve (time, flux, and flux error) and returns a probability light curve. The cadences in the probability light curve are values between 0 and 1, where 1 means the CNN believes there is a flare there. It takes < 1 minute to predict flares on a single light curve. Users also have the ability the train their own customized CNN architecture. The stella software also includes modules to measure rotation periods and fit flares using simple exponential models.

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    https://emac.gsfc.nasa.gov#694292a5-1059-4537-9458-126b7bac9a13
    RV Jitter prediction code: Predicting RV jitter due to stellar oscillations and granulation using stellar parameters

    Yu et al. 2018

    Radial-velocity jitter due to intrinsic stellar variability introduces challenges when characterizing exoplanet systems, particularly when studying small (sub-Neptune-sized) planets orbiting solar-type stars. This code will be valuable for anticipating the radial-velocity stellar noise level of exoplanet host stars, and hence be useful for their follow-up spectroscopic observations. Our prediction can be also used to set a prior for the jitter term as a component when modeling the Keplerian orbits of the exoplanets.

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    https://emac.gsfc.nasa.gov#?related_resource=694292a5-1059-4537-9458-126b7bac9a13

    RV Jitter prediction code: Predicting RV jitter due to stellar oscillations and granulation using stellar parameters

    Yu et al. 2018

    Radial-velocity jitter due to intrinsic stellar variability introduces challenges when characterizing exoplanet systems, particularly when studying small (sub-Neptune-sized) planets orbiting solar-type stars. This code will be valuable for anticipating the radial-velocity stellar noise level of exoplanet host stars, and hence be useful for their follow-up spectroscopic observations. Our prediction can be also used to set a prior for the jitter term as a component when modeling the Keplerian orbits of the exoplanets.

    About Demo
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    https://emac.gsfc.nasa.gov#a4e1297f-09eb-43ca-9d32-3fec8b322dda
    TRICERATOPS: Bayesian Vetting and Validation Tool for Transiting Exoplanet Candidates

    Giacalone, S. et al.

    TRICERATOPS is a Bayesian vetting and validation tool for TESS planet candidates. For a given planet candidate, the tool calculates the probabilities of several astrophysical transit-producing scenarios using the TESS light curve, information about nearby stars, and follow-up observations (e.g., high-resolution imaging, spectroscopy, and time-series photometry). Using these probabilities, TRICERATOPS calculates a false positive probability (the overall probability of the transit being caused by an astrophysical false positive) and a nearby false positive probability (the probability of the transit being caused by an off-target event around a nearby star).

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    https://emac.gsfc.nasa.gov#?related_resource=a4e1297f-09eb-43ca-9d32-3fec8b322dda

    TRICERATOPS: Bayesian Vetting and Validation Tool for Transiting Exoplanet Candidates

    Giacalone, S. et al.

    TRICERATOPS is a Bayesian vetting and validation tool for TESS planet candidates. For a given planet candidate, the tool calculates the probabilities of several astrophysical transit-producing scenarios using the TESS light curve, information about nearby stars, and follow-up observations (e.g., high-resolution imaging, spectroscopy, and time-series photometry). Using these probabilities, TRICERATOPS calculates a false positive probability (the overall probability of the transit being caused by an astrophysical false positive) and a nearby false positive probability (the probability of the transit being caused by an off-target event around a nearby star).

    About Demo
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    https://emac.gsfc.nasa.gov#3f453498-e936-40ec-abf3-f22375c72f2b
    xwavecal: A Blind Wavelength Calibration Algorithm for Echelle Spectrographs

    Brandt, G. M. et al.

    A library of routines for wavelength calibrating echelle spectrographs for high precision radial velocity work. Calibrates the instrument without any input for known emission line wavelengths and positions. A limited data-reduction pipeline is included.

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    https://emac.gsfc.nasa.gov#?related_resource=3f453498-e936-40ec-abf3-f22375c72f2b

    xwavecal: A Blind Wavelength Calibration Algorithm for Echelle Spectrographs

    Brandt, G. M. et al.

    A library of routines for wavelength calibrating echelle spectrographs for high precision radial velocity work. Calibrates the instrument without any input for known emission line wavelengths and positions. A limited data-reduction pipeline is included.

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    https://emac.gsfc.nasa.gov?related_resource=479f0b6c-d191-49b3-9066-910cca188e16
    Wotan: Remove Trends from Time-series Data

    Michael Hippke

    Wotan offers free and open source algorithms to automagically remove trends from time-series data. Python open source. Available detrending algorithms include: Time-windowed sliders with location estimates, splines, polynomials and sines, regressions, fitting a model that is a sum of Gaussian bases, Gaussian Processes. Available features: Filter lengths, break tolerances, edge cutoffs, tuning parameters, transit masks.

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    https://emac.gsfc.nasa.gov#?related_resource=479f0b6c-d191-49b3-9066-910cca188e16

    Wotan: Remove Trends from Time-series Data

    Michael Hippke

    Wotan offers free and open source algorithms to automagically remove trends from time-series data. Python open source. Available detrending algorithms include: Time-windowed sliders with location estimates, splines, polynomials and sines, regressions, fitting a model that is a sum of Gaussian bases, Gaussian Processes. Available features: Filter lengths, break tolerances, edge cutoffs, tuning parameters, transit masks.

    About Demo
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    https://emac.gsfc.nasa.gov#6733980c-060b-4ca5-8e1e-0b4e37d705e6
    Juliet: A Versatile Modeling tool for Transiting and Non-transiting Exoplanetary Systems

    Espinoza et al.

    Juliet is a versatile modelling tool for transiting and non-transiting exoplanetary systems that allows to perform quick-and-easy fits to data coming from transit photometry, radial velocity or both using bayesian inference and, in particular, using Nested Sampling in order to allow both efficient fitting and proper model comparison. This pip-installable python library (pip install juliet) also allows to model these time-series using either simple linear models and/or more involved correlated noise on both photometry and radial-velocities through Gaussian Processes. Full documentation is available here.

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    https://emac.gsfc.nasa.gov#?related_resource=6733980c-060b-4ca5-8e1e-0b4e37d705e6

    Juliet: A Versatile Modeling tool for Transiting and Non-transiting Exoplanetary Systems

    Espinoza et al.

    Juliet is a versatile modelling tool for transiting and non-transiting exoplanetary systems that allows to perform quick-and-easy fits to data coming from transit photometry, radial velocity or both using bayesian inference and, in particular, using Nested Sampling in order to allow both efficient fitting and proper model comparison. This pip-installable python library (pip install juliet) also allows to model these time-series using either simple linear models and/or more involved correlated noise on both photometry and radial-velocities through Gaussian Processes. Full documentation is available here.

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    https://emac.gsfc.nasa.gov#308c68d5-013b-401e-bac2-5b4035d1f76a
    THOR: Flexible Global Circulation Model to Explore Planetary Atmospheres

    Mendonça, J. et al. 2016; Deitrick, R., et al. 2020

    THOR is a GCM that solves the three-dimensional non-hydrostatic Euler equations on an icosahedral grid. THOR was designed to run on Graphics Processing Units (GPUs).

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    https://emac.gsfc.nasa.gov#?related_resource=308c68d5-013b-401e-bac2-5b4035d1f76a

    THOR: Flexible Global Circulation Model to Explore Planetary Atmospheres

    Mendonça, J. et al. 2016; Deitrick, R., et al. 2020

    THOR is a GCM that solves the three-dimensional non-hydrostatic Euler equations on an icosahedral grid. THOR was designed to run on Graphics Processing Units (GPUs).

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    https://emac.gsfc.nasa.gov#e866321d-1b17-47d5-9229-ffe9beba921a
    pyaneti: A multi-planet Radial Velocity and Transit fit software

    Barragán O., Gandolfi D. & Antoniciello G.

    pyaneti is a multi-planet radial velocity and transit fit software. The code uses Markov chain Monte Carlo (MCMC) methods with a Bayesian approach and a parallelized ensemble sampler algorithm in Fortran which makes the code fast. It creates posteriors, correlations, and ready-to-publish plots automatically, and handles circular and eccentric orbits. It is capable of multi-planet fitting and handles stellar limb darkening, systemic velocities for multiple instruments, and short and long cadence data, and offers additional capabilities.

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    https://emac.gsfc.nasa.gov#?related_resource=e866321d-1b17-47d5-9229-ffe9beba921a

    pyaneti: A multi-planet Radial Velocity and Transit fit software

    Barragán O., Gandolfi D. & Antoniciello G.

    pyaneti is a multi-planet radial velocity and transit fit software. The code uses Markov chain Monte Carlo (MCMC) methods with a Bayesian approach and a parallelized ensemble sampler algorithm in Fortran which makes the code fast. It creates posteriors, correlations, and ready-to-publish plots automatically, and handles circular and eccentric orbits. It is capable of multi-planet fitting and handles stellar limb darkening, systemic velocities for multiple instruments, and short and long cadence data, and offers additional capabilities.

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    https://emac.gsfc.nasa.gov#b335069c-b8fa-4bb2-8d87-d6e7e8c8c0f1
    Aeolus: Python Library for Object-Oriented Analysis of Atmospheric Model Output

    Sergeev, D. E.

    Aeolus is a library for analysis and plotting of a climate model output, primarily of the UK Met Office Unified Model when it is used to simulate various planetary atmospheres. Aeolus is built on top of iris and has various functions tailored to exoplanet research, e.g. in the context of tidally-locked exoplanets.

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    https://emac.gsfc.nasa.gov#?related_resource=b335069c-b8fa-4bb2-8d87-d6e7e8c8c0f1

    Aeolus: Python Library for Object-Oriented Analysis of Atmospheric Model Output

    Sergeev, D. E.

    Aeolus is a library for analysis and plotting of a climate model output, primarily of the UK Met Office Unified Model when it is used to simulate various planetary atmospheres. Aeolus is built on top of iris and has various functions tailored to exoplanet research, e.g. in the context of tidally-locked exoplanets.

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    https://emac.gsfc.nasa.gov#a9a6cd4f-1b59-4d4f-abf2-6c1382482af4
    POET: Planetary Orbital Evolution due to Tides - Calculate secular orbital evolution

    Kaloyan Penev, Luke Bouma, and Joshua Schussler

    Calculate secular orbital evolution for star-planet and star-star systems under the combined influence of:

    • Tides in one or both of the objects
    • Age dependent stellar structure
    • Stars losing angular momentum to wind
    • The internal redistribution of angular momentum between the surface and the interior of stars

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    https://emac.gsfc.nasa.gov#?related_resource=a9a6cd4f-1b59-4d4f-abf2-6c1382482af4

    POET: Planetary Orbital Evolution due to Tides - Calculate secular orbital evolution

    Kaloyan Penev, Luke Bouma, and Joshua Schussler

    Calculate secular orbital evolution for star-planet and star-star systems under the combined influence of:

    • Tides in one or both of the objects
    • Age dependent stellar structure
    • Stars losing angular momentum to wind
    • The internal redistribution of angular momentum between the surface and the interior of stars

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    https://emac.gsfc.nasa.gov#d0adfa74-8a23-407b-b271-bc07a917726c
    EMAC CKAN Data Repository: Comprehensive Knowledge Archive Network data portal software

    https://ckan.emac.gsfc.nasa.gov

    The EMAC Comprehensive Knowledge Archive Network (CKAN) data portal provides a resource to the exoplanet modeling and analysis community for hosting data sets related to exoplanet modeling and analysis. These datasets can either be input data (i.e. opacity tables, stellar flux models, etc) or output data (output grids or data sets from exoplanet modeling/analysis software). If you are interested in using this service, submit a request through the Feedback page.

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    https://emac.gsfc.nasa.gov#?related_resource=d0adfa74-8a23-407b-b271-bc07a917726c

    EMAC CKAN Data Repository: Comprehensive Knowledge Archive Network data portal software

    https://ckan.emac.gsfc.nasa.gov

    The EMAC Comprehensive Knowledge Archive Network (CKAN) data portal provides a resource to the exoplanet modeling and analysis community for hosting data sets related to exoplanet modeling and analysis. These datasets can either be input data (i.e. opacity tables, stellar flux models, etc) or output data (output grids or data sets from exoplanet modeling/analysis software). If you are interested in using this service, submit a request through the Feedback page.

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    https://emac.gsfc.nasa.gov#33f94adf-513f-4d79-8fec-476e6dfaa915
    ExoplanetsSysSim.jl: The SysSim Planet Population Simulator

    Eric B. Ford, Matthias He, Danley Hsu, Darin Ragozzine

    The ExoplanetsSysSim.jl package generates populations of planetary systems, simulates observations of those systems with a transit survey, and facilitates comparisons of simulated and observed catalogs of planetary systems. Critically, ExoplanetsSysSim accounts for intrinsic correlations in the sizes and orbital periods of planets within a planetary system.

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    https://emac.gsfc.nasa.gov#?related_resource=33f94adf-513f-4d79-8fec-476e6dfaa915

    ExoplanetsSysSim.jl: The SysSim Planet Population Simulator

    Eric B. Ford, Matthias He, Danley Hsu, Darin Ragozzine

    The ExoplanetsSysSim.jl package generates populations of planetary systems, simulates observations of those systems with a transit survey, and facilitates comparisons of simulated and observed catalogs of planetary systems. Critically, ExoplanetsSysSim accounts for intrinsic correlations in the sizes and orbital periods of planets within a planetary system.

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    https://emac.gsfc.nasa.gov#22905167-e23f-4941-a2c6-e3936724958c
    AAS - Timeseries: Read in and Manipulate Time Series in Astropy

    Thomas Robitaille, American Astronomical Society (AAS)

    The aas-timeseries package has been developed as part of a project between AAS Publishing and the Astropy Project. The goal of this project is to provide astronomers with all the tools needed to make it possible for astronomers to use Astropy to read in and manipulate time series data sets, such as exoplanet transit light curves, produce interactive figures, and easily embed these in a paper. The package is general enough to be usable in other contexts, for example to embed interactive time series figures in personal web pages, or for use in Jupyter notebooks and Jupyter Lab.

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    https://emac.gsfc.nasa.gov#?related_resource=22905167-e23f-4941-a2c6-e3936724958c

    AAS - Timeseries: Read in and Manipulate Time Series in Astropy

    Thomas Robitaille, American Astronomical Society (AAS)

    The aas-timeseries package has been developed as part of a project between AAS Publishing and the Astropy Project. The goal of this project is to provide astronomers with all the tools needed to make it possible for astronomers to use Astropy to read in and manipulate time series data sets, such as exoplanet transit light curves, produce interactive figures, and easily embed these in a paper. The package is general enough to be usable in other contexts, for example to embed interactive time series figures in personal web pages, or for use in Jupyter notebooks and Jupyter Lab.

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    https://emac.gsfc.nasa.gov#1aaeb409-f9e2-416f-a41e-b0b4349e6c83
    ARCHI: An expansion to the CHEOPS mission official pipeline

    André M.Silva et al

    ARCHI, An expansion to the CHEOPS mission official pipeline, is an additional open-source pipeline to analyse the background stars present in CHEOPS images that are not tracked by the official pipeline. This tool opens a potential for the use of CHEOPS to produce photometric time-series of several close-by targets at once, as well as to use different stars in the image to calibrate systematic errors. Furthermore, there might be cases where the study of the companion light curve can be important for the understanding of contaminations on the main target .

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    https://emac.gsfc.nasa.gov#?related_resource=1aaeb409-f9e2-416f-a41e-b0b4349e6c83

    ARCHI: An expansion to the CHEOPS mission official pipeline

    André M.Silva et al

    ARCHI, An expansion to the CHEOPS mission official pipeline, is an additional open-source pipeline to analyse the background stars present in CHEOPS images that are not tracked by the official pipeline. This tool opens a potential for the use of CHEOPS to produce photometric time-series of several close-by targets at once, as well as to use different stars in the image to calibrate systematic errors. Furthermore, there might be cases where the study of the companion light curve can be important for the understanding of contaminations on the main target .

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    https://emac.gsfc.nasa.gov#da0480c1-32c4-4e8c-9a42-7931d3f4b088
    VBBinaryLensing: Computation of Microlensing Light Curves and Astrometry

    Valerio Bozza, in collaboration with Etienne Bachelet, Fran Bartolic, Ava Hoagg, Thomas Heintz, Markus Hundertmark, Elahe Khalouei

    Library for the computation of microlensing light curves and astrometric centroid based on contour integration scheme. The code covers single-lens and binary-lens microlensing, includes finite size of the source, limb darkening, annual and satellite parallax, orbital motion.

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    https://emac.gsfc.nasa.gov#?related_resource=da0480c1-32c4-4e8c-9a42-7931d3f4b088

    VBBinaryLensing: Computation of Microlensing Light Curves and Astrometry

    Valerio Bozza, in collaboration with Etienne Bachelet, Fran Bartolic, Ava Hoagg, Thomas Heintz, Markus Hundertmark, Elahe Khalouei

    Library for the computation of microlensing light curves and astrometric centroid based on contour integration scheme. The code covers single-lens and binary-lens microlensing, includes finite size of the source, limb darkening, annual and satellite parallax, orbital motion.

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    https://emac.gsfc.nasa.gov#a4778a22-5b89-4903-aa57-3f8d415b31df
    CHIMERA: Exoplanet Emission/Transmission Atmospheric Retrieval Tool

    M. Line et al. (J. Lustig-Yaeger, N. Batalha, M. Marley, X. Zhang, A. Wolf)

    Flexible atmospheric retrieval tool for exoplanet atmospheres. Can be used for both transmission and emission geometries with options for both the "free" and "chemically consistent" abundance retrievals. Uses correlated-K opacities (R=100) with the random-overlap resort-rebin procedure (Amundsen et al. 2017). Includes full multiple scattering in emission (both planetary and stellar reflected light) using a two stream approximation variant (Toon et al. 1989). Various cloud parameterizations ranging from "grey+power-law" to the "Ackerman & Marley 2001" eddy-sed routine in both emission and transmission. Includes multiple Bayesian samplers, including PyMultiNest (recommended) and Dynesty.

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    https://emac.gsfc.nasa.gov#?related_resource=a4778a22-5b89-4903-aa57-3f8d415b31df

    CHIMERA: Exoplanet Emission/Transmission Atmospheric Retrieval Tool

    M. Line et al. (J. Lustig-Yaeger, N. Batalha, M. Marley, X. Zhang, A. Wolf)

    Flexible atmospheric retrieval tool for exoplanet atmospheres. Can be used for both transmission and emission geometries with options for both the "free" and "chemically consistent" abundance retrievals. Uses correlated-K opacities (R=100) with the random-overlap resort-rebin procedure (Amundsen et al. 2017). Includes full multiple scattering in emission (both planetary and stellar reflected light) using a two stream approximation variant (Toon et al. 1989). Various cloud parameterizations ranging from "grey+power-law" to the "Ackerman & Marley 2001" eddy-sed routine in both emission and transmission. Includes multiple Bayesian samplers, including PyMultiNest (recommended) and Dynesty.

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    https://emac.gsfc.nasa.gov#806d1fa8-c9a7-4e8b-ba8b-fbf3269473f4
    Forecaster: Empirical, Probabilistic Predictions of Exoplanet Masses & Radii

    Jingjing Chen, David Kipping

    Forecaster predicts a planet’s mass, based on its radius -OR- predicts a planet’s radius, based on its mass. Forecaster works with both summary statistics and posterior samples. What distinguishes forecaster from other codes is that it is empirical and probabilistic. This means that the algorithm has been trained using the masses and radii of over 300 worlds with precise measurements of their masses and radii. No theoretical relations are used or assumed, the mass-radius relation is simply learned from the data. This also means that the predictions are intrinsically probabilistic (and not deterministic). For a given planetary mass, there isn’t just one possible radius, but a range of radii.

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    https://emac.gsfc.nasa.gov#?related_resource=806d1fa8-c9a7-4e8b-ba8b-fbf3269473f4

    Forecaster: Empirical, Probabilistic Predictions of Exoplanet Masses & Radii

    Jingjing Chen, David Kipping

    Forecaster predicts a planet’s mass, based on its radius -OR- predicts a planet’s radius, based on its mass. Forecaster works with both summary statistics and posterior samples. What distinguishes forecaster from other codes is that it is empirical and probabilistic. This means that the algorithm has been trained using the masses and radii of over 300 worlds with precise measurements of their masses and radii. No theoretical relations are used or assumed, the mass-radius relation is simply learned from the data. This also means that the predictions are intrinsically probabilistic (and not deterministic). For a given planetary mass, there isn’t just one possible radius, but a range of radii.

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    https://emac.gsfc.nasa.gov#fd23da77-9a96-4854-96bf-03b116c3a556
    AstroBEAR: An Adaptive Mesh Refinement Code for Computational Astrophysics

    Jonathan Carroll-Nellenback, Adam Frank, Baowei Liu, Shule Li, Erica Fogerty, Andrew Cunningham, Sorin Mitran, Zhuo Chen, Kris Yirak, Eddie Hansen, Martin Huarte-Espinosa, Luke Chamandy, Alex Debrecht, Yangyuxin Zou, Atma Anand

    AstroBEAR is a parallelized hydrodynamic/MHD simulation code suitable for a variety of astrophysical problems. Derived from the BearCLAW package written by Sorin Mitran, AstroBEAR is designed for 2D and 3D adaptive mesh refinement (AMR), multi-physics simulations. Users write their own project modules by specifying initial conditions and continual processes (such as an inflow condition). In addition, AstroBEAR comes with a number of pre-built physical phenomena such as clumps and winds that can be loaded into a user module.

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    https://emac.gsfc.nasa.gov#?related_resource=fd23da77-9a96-4854-96bf-03b116c3a556

    AstroBEAR: An Adaptive Mesh Refinement Code for Computational Astrophysics

    Jonathan Carroll-Nellenback, Adam Frank, Baowei Liu, Shule Li, Erica Fogerty, Andrew Cunningham, Sorin Mitran, Zhuo Chen, Kris Yirak, Eddie Hansen, Martin Huarte-Espinosa, Luke Chamandy, Alex Debrecht, Yangyuxin Zou, Atma Anand

    AstroBEAR is a parallelized hydrodynamic/MHD simulation code suitable for a variety of astrophysical problems. Derived from the BearCLAW package written by Sorin Mitran, AstroBEAR is designed for 2D and 3D adaptive mesh refinement (AMR), multi-physics simulations. Users write their own project modules by specifying initial conditions and continual processes (such as an inflow condition). In addition, AstroBEAR comes with a number of pre-built physical phenomena such as clumps and winds that can be loaded into a user module.

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    https://emac.gsfc.nasa.gov#dab0da6f-8abb-4a67-9d59-a5e86f0152b2
    VIP: Vortex Image Processing package

    C. A. Gomez Gonzalez (founder and main contributor), V. Christiaens (current maintainer), R. Farkas, O. Absil, O. Wertz, J. Milli, F. Cantalloube, G. Ruane. More contributors here.

    VIP is a python package for angular, reference star and spectral differential imaging, for exoplanet and disk high-contrast imaging. It also contains a number of routines for image preprocessing, performance assessment and companion characterization. The goal of VIP is to integrate open-source, efficient, easy-to-use and well-documented implementations of high-contrast image processing algorithms. VIP started as the effort of Carlos Alberto Gomez Gonzalez, a former PhD student of the VORTEX team (ULiège, Belgium). VIP's development has been led by Dr. Gomez until 2018, and is currently maintained by Dr. Valentin Christiaens (UMonash, Australia). More info here: http://vip.readthedocs.io

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    https://emac.gsfc.nasa.gov#?related_resource=dab0da6f-8abb-4a67-9d59-a5e86f0152b2

    VIP: Vortex Image Processing package

    C. A. Gomez Gonzalez (founder and main contributor), V. Christiaens (current maintainer), R. Farkas, O. Absil, O. Wertz, J. Milli, F. Cantalloube, G. Ruane. More contributors here.

    VIP is a python package for angular, reference star and spectral differential imaging, for exoplanet and disk high-contrast imaging. It also contains a number of routines for image preprocessing, performance assessment and companion characterization. The goal of VIP is to integrate open-source, efficient, easy-to-use and well-documented implementations of high-contrast image processing algorithms. VIP started as the effort of Carlos Alberto Gomez Gonzalez, a former PhD student of the VORTEX team (ULiège, Belgium). VIP's development has been led by Dr. Gomez until 2018, and is currently maintained by Dr. Valentin Christiaens (UMonash, Australia). More info here: http://vip.readthedocs.io

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    https://emac.gsfc.nasa.gov?related_resource=6cb8ee25-4d3d-438a-aad6-29f0ddb011ac
    SVO Filter Profile Service: A repository of Filter information for the Virtual Observatory

    Carlos Rodrigo, Spanish Virtual Observatory, CAB, CSIC-INTA.

    The SVO Filter Profile Service provides standardized information, including transmission curves and calibration, about more than 6100 astronomical filters. The service is designed to be compliant to the Virtual Observatory Photometry Data Model and all the information is provided both as a web portal and VO services so that other services and applications can access the relevant properties of a filter in a simple way.

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    https://emac.gsfc.nasa.gov#?related_resource=6cb8ee25-4d3d-438a-aad6-29f0ddb011ac

    SVO Filter Profile Service: A repository of Filter information for the Virtual Observatory

    Carlos Rodrigo, Spanish Virtual Observatory, CAB, CSIC-INTA.

    The SVO Filter Profile Service provides standardized information, including transmission curves and calibration, about more than 6100 astronomical filters. The service is designed to be compliant to the Virtual Observatory Photometry Data Model and all the information is provided both as a web portal and VO services so that other services and applications can access the relevant properties of a filter in a simple way.

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    https://emac.gsfc.nasa.gov?related_resource=f56dff02-56b6-4374-84d6-cb59abf48602
    SVO Theoretical Spectra Server: A Server of Data for over 60 Collections of Theoretical Spectra and Observational Templates

    Carlos Rodrigo, Spanish Virtual Observatory, CAB, CSIC-INTA

    The SVO Theory Server provides data for more than 60 collections of theoretical spectra and observational templates. Using this web page you can search for spectra in each collection in terms of the corresponding grid parameter ranges, visualize the spectra and/or download them in ascii or VOTable format. You will be able to compare spectra from different collections too. Synthetic Photometry is also available for these spectra and all the filters in the SVO Filter Profile Service.

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    https://emac.gsfc.nasa.gov#?related_resource=f56dff02-56b6-4374-84d6-cb59abf48602

    SVO Theoretical Spectra Server: A Server of Data for over 60 Collections of Theoretical Spectra and Observational Templates

    Carlos Rodrigo, Spanish Virtual Observatory, CAB, CSIC-INTA

    The SVO Theory Server provides data for more than 60 collections of theoretical spectra and observational templates. Using this web page you can search for spectra in each collection in terms of the corresponding grid parameter ranges, visualize the spectra and/or download them in ascii or VOTable format. You will be able to compare spectra from different collections too. Synthetic Photometry is also available for these spectra and all the filters in the SVO Filter Profile Service.

    Demo
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    https://emac.gsfc.nasa.gov#3b373283-d917-4c1e-afcd-16006eb91de2
    ODUSSEAS: A Machine Learning Tool to Derive Effective Temperature and Metallicity for M Dwarf Stars

    A. Antoniadis-Karnavas, S. G. Sousa, E. Delgado-Mena, N. C. Santos, G. D. C. Teixeira, V. Neves

    ODUSSEAS is an automatic computational tool able to quickly and reliably derive the Teff and [Fe/H] of M dwarfs using optical spectra obtained by different spectrographs with different resolutions. It is based on the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and on the use of the machine learning Python package “scikit-learn” for predicting the stellar parameters. It is able to derive parameters accurately and with high precision, having precision errors of ~30 K for Teff and ~0.04 dex for [Fe/H]. The results are consistent for spectra with resolutions of between 48000 and 115000 and a signal-to-noise ratio above 20.

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    https://emac.gsfc.nasa.gov#?related_resource=3b373283-d917-4c1e-afcd-16006eb91de2

    ODUSSEAS: A Machine Learning Tool to Derive Effective Temperature and Metallicity for M Dwarf Stars

    A. Antoniadis-Karnavas, S. G. Sousa, E. Delgado-Mena, N. C. Santos, G. D. C. Teixeira, V. Neves

    ODUSSEAS is an automatic computational tool able to quickly and reliably derive the Teff and [Fe/H] of M dwarfs using optical spectra obtained by different spectrographs with different resolutions. It is based on the measurement of the pseudo equivalent widths for more than 4000 stellar absorption lines and on the use of the machine learning Python package “scikit-learn” for predicting the stellar parameters. It is able to derive parameters accurately and with high precision, having precision errors of ~30 K for Teff and ~0.04 dex for [Fe/H]. The results are consistent for spectra with resolutions of between 48000 and 115000 and a signal-to-noise ratio above 20.

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    https://emac.gsfc.nasa.gov#0411595b-6d94-480a-8abc-ebe814fa867f
    tpfplotter: TESS Target Pixel File Creator 0.4

    J. Lillo-Box (Aller et al., 2020, A&A, 635, 128)

    tpfplotter is a user-friendly tool to create the TESS Target Pixel Files of your favorite source overplotting the aperture mask used by the SPOC pipeline and the Gaia catalogue to check for possible contaminations within the aperture. Create paper-ready figures (1-column) overplotting the Gaia DR2 catalog to the TESS Target Pixel Files. You can create plots for any target observed by TESS! Even if you do not have a TIC number, you can search by coordinates now (see examples in Github)!

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    https://emac.gsfc.nasa.gov#?related_resource=0411595b-6d94-480a-8abc-ebe814fa867f

    tpfplotter: TESS Target Pixel File Creator 0.4

    J. Lillo-Box (Aller et al., 2020, A&A, 635, 128)

    tpfplotter is a user-friendly tool to create the TESS Target Pixel Files of your favorite source overplotting the aperture mask used by the SPOC pipeline and the Gaia catalogue to check for possible contaminations within the aperture. Create paper-ready figures (1-column) overplotting the Gaia DR2 catalog to the TESS Target Pixel Files. You can create plots for any target observed by TESS! Even if you do not have a TIC number, you can search by coordinates now (see examples in Github)!

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    https://emac.gsfc.nasa.gov#1b1705f7-bd20-4eaf-b210-fe59ab88f73b
    PEXO: A Tool for Precise Modeling and Fitting for Timing, Radial Velocity and Astrometry Data

    Fabo Feng, & timberhill. (2020, May 5)

    PEXO is a package for making precise exoplanetology. Compared with previous models and packages, PEXO is general enough to account for binary motion and stellar reflex motions induced by planetary companions. PEXO is precise enough to treat various relativistic effects both in the Solar System and in the target system (Roemer, Shapiro, and Einstein delays). PEXO is able to model timing to a precision of 1 ns, astrometry to a precision of 1 μas, and radial velocity to a precision of 1 μm/s. There are pdf and html versions of the manual available for instructions of how to use PEXO. The fitting mode and a python wrapper are in development and expected to be released soon.

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    https://emac.gsfc.nasa.gov#?related_resource=1b1705f7-bd20-4eaf-b210-fe59ab88f73b

    PEXO: A Tool for Precise Modeling and Fitting for Timing, Radial Velocity and Astrometry Data

    Fabo Feng, & timberhill. (2020, May 5)

    PEXO is a package for making precise exoplanetology. Compared with previous models and packages, PEXO is general enough to account for binary motion and stellar reflex motions induced by planetary companions. PEXO is precise enough to treat various relativistic effects both in the Solar System and in the target system (Roemer, Shapiro, and Einstein delays). PEXO is able to model timing to a precision of 1 ns, astrometry to a precision of 1 μas, and radial velocity to a precision of 1 μm/s. There are pdf and html versions of the manual available for instructions of how to use PEXO. The fitting mode and a python wrapper are in development and expected to be released soon.

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    https://emac.gsfc.nasa.gov#9e308fc6-7db1-4657-9692-238d44f2f793
    Exostriker: Transit and Radial velocity Interactive Fitting tool for Orbital analysis and N-body simulations

    Trifon Trifonov, MPIA Heidelberg;

    Exostriker analyzes exoplanet orbitals, performs N-body simulations, and models the RV stellar reflex motion caused by dynamically interacting planets in multi-planetary systems. It offers a broad range of tools for detailed analysis of transit and Doppler data, including power spectrum analysis for Doppler and transit data; Keplerian and dynamical modeling of multi-planet systems; MCMC and nested sampling; Gaussian Processes modeling; and a long-term stability check of multi-planet systems. The Exo-Striker can also perform Mean Motion Resonance (MMR) analysis, create fast fully interactive plots, and export ready-to-use LaTeX tables with best-fit parameters, errors, and statistics.

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    https://emac.gsfc.nasa.gov#?related_resource=9e308fc6-7db1-4657-9692-238d44f2f793

    Exostriker: Transit and Radial velocity Interactive Fitting tool for Orbital analysis and N-body simulations

    Trifon Trifonov, MPIA Heidelberg;

    Exostriker analyzes exoplanet orbitals, performs N-body simulations, and models the RV stellar reflex motion caused by dynamically interacting planets in multi-planetary systems. It offers a broad range of tools for detailed analysis of transit and Doppler data, including power spectrum analysis for Doppler and transit data; Keplerian and dynamical modeling of multi-planet systems; MCMC and nested sampling; Gaussian Processes modeling; and a long-term stability check of multi-planet systems. The Exo-Striker can also perform Mean Motion Resonance (MMR) analysis, create fast fully interactive plots, and export ready-to-use LaTeX tables with best-fit parameters, errors, and statistics.

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    https://emac.gsfc.nasa.gov#a87ea5c0-1647-4936-85ee-3f629fe3b6a5
    ExoCAM: Exoplanet Extension for the CAM GCM

    Wolf, E.T.

    ExoCAM is a model extension to the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) 3-D general circulation and climate system model, which facilitates simulations of exoplanetary atmospheres. This software contains system configuration files, source code, initial condition files, namelists, and some basic analysis scripts. Familiarity with CESM is prerequisite. CESM must be downloaded separately. The radiative transfer component of ExoCAM is stored in a separate GitHub link , and can be run independently or coupled with ExoCAM/CESM.

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    https://emac.gsfc.nasa.gov#?related_resource=a87ea5c0-1647-4936-85ee-3f629fe3b6a5

    ExoCAM: Exoplanet Extension for the CAM GCM

    Wolf, E.T.

    ExoCAM is a model extension to the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) 3-D general circulation and climate system model, which facilitates simulations of exoplanetary atmospheres. This software contains system configuration files, source code, initial condition files, namelists, and some basic analysis scripts. Familiarity with CESM is prerequisite. CESM must be downloaded separately. The radiative transfer component of ExoCAM is stored in a separate GitHub link , and can be run independently or coupled with ExoCAM/CESM.

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    https://emac.gsfc.nasa.gov#6580efe4-c73c-4e70-97ad-a0fd166fa142
    BEM: Beyond the Exoplanet Mass-radius Relation with Random Forest

    S. Ulmer-Moll, N.C Santos, P.Figueira, J. Brinchmann, J.P. Faria

    Bem allows you to predict the planetary radius based on several other planetary and stellar parameters. We worked with a database of confirmed exoplanets with known radii and masses, as well as the planets from our Solar System. Using random forests, a machine learning algorithm, we computed the radius of exoplanets and compared the results to the published radii. The estimated radii reproduces the spread in radius found for high mass planets better than previous mass-radius relations. The average radius error is 1.8R⊕ across the whole range of radii from 1–22R⊕. Bem is able to derive reliable radii, especially for planets between 4 R⊕ and 20 R⊕ for which the error is under 25%.

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    https://emac.gsfc.nasa.gov#?related_resource=6580efe4-c73c-4e70-97ad-a0fd166fa142

    BEM: Beyond the Exoplanet Mass-radius Relation with Random Forest

    S. Ulmer-Moll, N.C Santos, P.Figueira, J. Brinchmann, J.P. Faria

    Bem allows you to predict the planetary radius based on several other planetary and stellar parameters. We worked with a database of confirmed exoplanets with known radii and masses, as well as the planets from our Solar System. Using random forests, a machine learning algorithm, we computed the radius of exoplanets and compared the results to the published radii. The estimated radii reproduces the spread in radius found for high mass planets better than previous mass-radius relations. The average radius error is 1.8R⊕ across the whole range of radii from 1–22R⊕. Bem is able to derive reliable radii, especially for planets between 4 R⊕ and 20 R⊕ for which the error is under 25%.

    About Demo
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    https://emac.gsfc.nasa.gov#d25fc293-8ad8-49a3-af8e-ddf86dc34acc
    MulensModel: A Microlensing Event Fitting Tool

    Radek Poleski, Jennifer Yee

    MulensModel is a package for modelling gravitational microlensing events. It's written in Python3 and is object-oriented. MulensModel allows calculating goodness of fit statistics and plotting several kinds of plots. It's accurate enough to model data from the upcoming Nancy Grace Roman Telescope (formerly WFIRST). There are many examples, a few tutorials, and full documentation of every public function. The code is continuously developed.

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    https://emac.gsfc.nasa.gov#?related_resource=d25fc293-8ad8-49a3-af8e-ddf86dc34acc

    MulensModel: A Microlensing Event Fitting Tool

    Radek Poleski, Jennifer Yee

    MulensModel is a package for modelling gravitational microlensing events. It's written in Python3 and is object-oriented. MulensModel allows calculating goodness of fit statistics and plotting several kinds of plots. It's accurate enough to model data from the upcoming Nancy Grace Roman Telescope (formerly WFIRST). There are many examples, a few tutorials, and full documentation of every public function. The code is continuously developed.

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    https://emac.gsfc.nasa.gov#23d399b2-7f15-43dc-a597-6b22db3f436e
    JET: JWST Exoplanet Targeting Program

    Charles Fortenbach, Courtney Dressing, et al.

    JWST will devote significant observing time to the study of exoplanets. It will not be serviceable as was the Hubble, and therefore the spacecraft/instruments will have a relatively limited life. It is important to get as much science as possible out of this limited observing time. We provide a computer tool, JET, to optimize lists of exoplanet targets for atmospheric characterization. JET takes catalogs of planet detections; categorizes the targets by radius and equilibrium temp.; estimates planet masses; generates model spectra and simulated instrument spectra; performs a statistical analysis to confirm an atmospheric detection; and finally, ranks the targets by observation time required.

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    https://emac.gsfc.nasa.gov#?related_resource=23d399b2-7f15-43dc-a597-6b22db3f436e

    JET: JWST Exoplanet Targeting Program

    Charles Fortenbach, Courtney Dressing, et al.

    JWST will devote significant observing time to the study of exoplanets. It will not be serviceable as was the Hubble, and therefore the spacecraft/instruments will have a relatively limited life. It is important to get as much science as possible out of this limited observing time. We provide a computer tool, JET, to optimize lists of exoplanet targets for atmospheric characterization. JET takes catalogs of planet detections; categorizes the targets by radius and equilibrium temp.; estimates planet masses; generates model spectra and simulated instrument spectra; performs a statistical analysis to confirm an atmospheric detection; and finally, ranks the targets by observation time required.

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    https://emac.gsfc.nasa.gov#0e6e852b-8bfe-4213-98c5-4136cad15c98
    REBOUND: A Flexible Multi-Integrator N-body Code

    Hanno Rein, Dan Tamayo

    REBOUND is an N-body integrator, i.e. a software package that can integrate the motion of particles under the influence of gravity. The particles can represent stars, planets, moons, ring or dust particles. REBOUND is very flexible and can be customized to accurately and efficiently solve many problems in astrophysics. It includes symplectic integrators (WHFast, WHFastHelio, SEI, LEAPFROG), high order symplectic integrators (SABA, WH Kernel methods) as well as high accuracy non-symplectic integrator with adaptive timestepping (IAS15).

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    https://emac.gsfc.nasa.gov#?related_resource=0e6e852b-8bfe-4213-98c5-4136cad15c98

    REBOUND: A Flexible Multi-Integrator N-body Code

    Hanno Rein, Dan Tamayo

    REBOUND is an N-body integrator, i.e. a software package that can integrate the motion of particles under the influence of gravity. The particles can represent stars, planets, moons, ring or dust particles. REBOUND is very flexible and can be customized to accurately and efficiently solve many problems in astrophysics. It includes symplectic integrators (WHFast, WHFastHelio, SEI, LEAPFROG), high order symplectic integrators (SABA, WH Kernel methods) as well as high accuracy non-symplectic integrator with adaptive timestepping (IAS15).

    About Demo
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    https://emac.gsfc.nasa.gov#29f38110-d27d-43a3-b3d8-9b3553e4f436
    MRExo: Nonparametric Mass-radius Modelling for Exoplanets

    Shubham Kanodia, Gudmundur Stefansson , Angie Wolfgang, Bo Ning, Suvrath Mahadevan

    MRExo is a Python script for non-parametric fitting and analysis of the Mass-Radius (M-R) relationship for exoplanets. We translate Ning et al. (2018)'s R script into a publicly available Python package called MRExo. It offers tools for fitting the M-R relationship to a given data set. Along with the MRExo installation, the fit results from the M dwarf sample dataset from Kanodia et al. (2019) and the Kepler exoplanet sample from Ning et al. (2018) are included. The code also includes predicting functions (M->R, and R->M), and plotting functions to generate the plots used in the below manuscript. For detailed description of the code please see Kanodia et al. (2019)

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    https://emac.gsfc.nasa.gov#?related_resource=29f38110-d27d-43a3-b3d8-9b3553e4f436

    MRExo: Nonparametric Mass-radius Modelling for Exoplanets

    Shubham Kanodia, Gudmundur Stefansson , Angie Wolfgang, Bo Ning, Suvrath Mahadevan

    MRExo is a Python script for non-parametric fitting and analysis of the Mass-Radius (M-R) relationship for exoplanets. We translate Ning et al. (2018)'s R script into a publicly available Python package called MRExo. It offers tools for fitting the M-R relationship to a given data set. Along with the MRExo installation, the fit results from the M dwarf sample dataset from Kanodia et al. (2019) and the Kepler exoplanet sample from Ning et al. (2018) are included. The code also includes predicting functions (M->R, and R->M), and plotting functions to generate the plots used in the below manuscript. For detailed description of the code please see Kanodia et al. (2019)

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    Barycorrpy: Precise Barycentric Correction for Stellar and Solar Radial Velocities and Time-stamps

    Shubham Kanodia, Jason Wright, Joe Ninan

    Barycorrpy is an open source code written in Python based on Barycorr in IDL (Wright and Eastman 2014) to calculate the barycentric correction for any time series observations of stellar sources, and to convert JDUTC to BJDTDB time stamps (Kanodia and Wright 2018). Update August 2020: It can now also be used to calculate the barycentric correction for Solar observations, as well as reflected light observations of solar system objects (Wright and Kanodia 2020).

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    Barycorrpy: Precise Barycentric Correction for Stellar and Solar Radial Velocities and Time-stamps

    Shubham Kanodia, Jason Wright, Joe Ninan

    Barycorrpy is an open source code written in Python based on Barycorr in IDL (Wright and Eastman 2014) to calculate the barycentric correction for any time series observations of stellar sources, and to convert JDUTC to BJDTDB time stamps (Kanodia and Wright 2018). Update August 2020: It can now also be used to calculate the barycentric correction for Solar observations, as well as reflected light observations of solar system objects (Wright and Kanodia 2020).

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    Lightweight Space Coronagraph Simulator: Simulator of High-Contrast Space Telescopes

    Leonid Pogorelyuk

    Simulator of high-contrast space telescopes in a linear regime of small wavefront perturbations about the nominal dark hole. Used for testing high-order wavefront sensing and control as well as post-processing algorithms. Models broadband images with sensor noise, wavefront drift, actuators drift and residual effects from low-order wavefront sensing. Currently supports a model of the Roman Space Telescope Hybrid Lyot Coronagraph based on its FALCO model. Comes with and example of dark hole maintenance using an Extended Kalman Filter and Electric Field Conjugation.

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    https://emac.gsfc.nasa.gov#?related_resource=b4ed2732-f128-4962-84f2-9aab960140f0

    Lightweight Space Coronagraph Simulator: Simulator of High-Contrast Space Telescopes

    Leonid Pogorelyuk

    Simulator of high-contrast space telescopes in a linear regime of small wavefront perturbations about the nominal dark hole. Used for testing high-order wavefront sensing and control as well as post-processing algorithms. Models broadband images with sensor noise, wavefront drift, actuators drift and residual effects from low-order wavefront sensing. Currently supports a model of the Roman Space Telescope Hybrid Lyot Coronagraph based on its FALCO model. Comes with and example of dark hole maintenance using an Extended Kalman Filter and Electric Field Conjugation.

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    MESA: Modules for Experiments in Stellar Astrophysics

    MESA Team

    The Modules for Experiments in Stellar Astrophysics (MESA) source code is a set of software modules for stellar astrophysics that can be used on their own, or combined to solve the coupled equations governing 1D stellar evolution. MESA is described in MESA I, MESA II, MESA III , MESA IV, MESA V

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    MESA: Modules for Experiments in Stellar Astrophysics

    MESA Team

    The Modules for Experiments in Stellar Astrophysics (MESA) source code is a set of software modules for stellar astrophysics that can be used on their own, or combined to solve the coupled equations governing 1D stellar evolution. MESA is described in MESA I, MESA II, MESA III , MESA IV, MESA V

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    HARDCORE: A Core Radius Fractions Exoplanet Calculator

    Gabrielle Suissa, Jingjing Chen, David Kipping

    HARDCORE exploits boundary conditions on exoplanet internal composition to solve for the minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet based on mass and radius limits. The original source code was developed for the study by Suissa et al. 2018.

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    HARDCORE: A Core Radius Fractions Exoplanet Calculator

    Gabrielle Suissa, Jingjing Chen, David Kipping

    HARDCORE exploits boundary conditions on exoplanet internal composition to solve for the minimum, maximum, and marginal core radius fractions (CRFmin, CRFmax, CRFmarg) for a solid exoplanet based on mass and radius limits. The original source code was developed for the study by Suissa et al. 2018.

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    PynPoint: Pipeline for Processing and Analyzing High-Contrast Image Data of Exoplanets and Brown Dwarfs

    Tomas Stolker, Markus Bonse, Sascha Quanz, Adam Amara, et al.

    PynPoint is a generic, end-to-end pipeline for processing and analysis of high-contrast imaging data of exoplanets and brown dwarfs. The software architecture has a modular and scalable design. A variety of pipeline modules are available for pre-processing, PSF subtraction with principal component analysis (PCA), photometric and astrometric measurements, and estimation of detection limits. The package supports post-processing with ADI, RDI, and SDI techniques.

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    PynPoint: Pipeline for Processing and Analyzing High-Contrast Image Data of Exoplanets and Brown Dwarfs

    Tomas Stolker, Markus Bonse, Sascha Quanz, Adam Amara, et al.

    PynPoint is a generic, end-to-end pipeline for processing and analysis of high-contrast imaging data of exoplanets and brown dwarfs. The software architecture has a modular and scalable design. A variety of pipeline modules are available for pre-processing, PSF subtraction with principal component analysis (PCA), photometric and astrometric measurements, and estimation of detection limits. The package supports post-processing with ADI, RDI, and SDI techniques.

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    The Opacity Wizard: A Tool for Visualizations of Opacity and Abundance Data for Exoplanet and Brown Dwarf Atmospheres

    Caroline Morley

    This tool was developed to allow for easy and fast visualizations of opacity and abundance data for exoplanet and brown dwarf atmospheres. In particular, it was designed to be used by observers studying these substellar objects as an easy way of exploring which molecules are most important for a given planet and predict where the absorption features of those molecules will be. It is simple to use for non-python experts and requires only Python/NumPy/Matplotlib/Jupyter.

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    The Opacity Wizard: A Tool for Visualizations of Opacity and Abundance Data for Exoplanet and Brown Dwarf Atmospheres

    Caroline Morley

    This tool was developed to allow for easy and fast visualizations of opacity and abundance data for exoplanet and brown dwarf atmospheres. In particular, it was designed to be used by observers studying these substellar objects as an easy way of exploring which molecules are most important for a given planet and predict where the absorption features of those molecules will be. It is simple to use for non-python experts and requires only Python/NumPy/Matplotlib/Jupyter.

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    Haystacks: High-fidelity Planetary System Models for Simulating Exoplanet Imaging

    A. Roberge and the Haystacks Team

    Haystacks models are high-fidelity spatial and spectral models of complete planetary systems including star, planets, interplanetary dust, and astrophysical background sources. They are intended for use in simulations of direct imaging and spectroscopy with high-contrast instruments on exoplanet missions. The Haystacks Project will help prepare for future exoEarth observations by better defining the challenge, using the knowledge gained through decades of Solar System and extrasolar planetary studies.

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    Haystacks: High-fidelity Planetary System Models for Simulating Exoplanet Imaging

    A. Roberge and the Haystacks Team

    Haystacks models are high-fidelity spatial and spectral models of complete planetary systems including star, planets, interplanetary dust, and astrophysical background sources. They are intended for use in simulations of direct imaging and spectroscopy with high-contrast instruments on exoplanet missions. The Haystacks Project will help prepare for future exoEarth observations by better defining the challenge, using the knowledge gained through decades of Solar System and extrasolar planetary studies.

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    REPAST: Rocky ExoPlanet Albedo Spectra Tool

    Adam J. R. W. Smith, Avi Mandell, Geronimo Villanueva

    Here we present a database of albedo spectra for rocky, Earth-sized and Earth-mass exoplanets, as computed with the NASA Planetary Spectrum Generator tool (psg.gsfc.nasa.gov; Villanueva et al. 2018). The database is presented in two Python .pickle files containing pandas DataFrame objects. The DataFrame index values are wavelength, in micrometers; while the column name values contain the encoded parameters represented in the model object's albedo spectra contained with in that column. Each cell then gives the calculated geometric albedo value for the column-named model planet at the row-indicated wavelength.

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    REPAST: Rocky ExoPlanet Albedo Spectra Tool

    Adam J. R. W. Smith, Avi Mandell, Geronimo Villanueva

    Here we present a database of albedo spectra for rocky, Earth-sized and Earth-mass exoplanets, as computed with the NASA Planetary Spectrum Generator tool (psg.gsfc.nasa.gov; Villanueva et al. 2018). The database is presented in two Python .pickle files containing pandas DataFrame objects. The DataFrame index values are wavelength, in micrometers; while the column name values contain the encoded parameters represented in the model object's albedo spectra contained with in that column. Each cell then gives the calculated geometric albedo value for the column-named model planet at the row-indicated wavelength.

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    Allesfitter: Package for Modeling Photometric and RV Data

    Günther, M., and Daylan, T.

    Allesfitter (Günther & Daylan, 2019 and in prep.) is a public and user-friendly astronomy software package for modeling photometric and RV data. It can accommodate multiple exoplanets, multi-star systems, star spots, stellar flares, and various noise models. A graphical user interface allows definition of all input. Then, allesfitter automatically runs a nested sampling or MCMC fit, and produces ASCII tables, LaTeX tables, and plots. For all this, allesfitter constructs an inference framework that unites the versatile packages ellc (Maxted 2016), aflare (Davenport et al. 2014), dynesty (Speagle 2019), emcee (Foreman-Mackey et al. 2013) and celerite (Foreman-Mackey et al. 2017).

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    Allesfitter: Package for Modeling Photometric and RV Data

    Günther, M., and Daylan, T.

    Allesfitter (Günther & Daylan, 2019 and in prep.) is a public and user-friendly astronomy software package for modeling photometric and RV data. It can accommodate multiple exoplanets, multi-star systems, star spots, stellar flares, and various noise models. A graphical user interface allows definition of all input. Then, allesfitter automatically runs a nested sampling or MCMC fit, and produces ASCII tables, LaTeX tables, and plots. For all this, allesfitter constructs an inference framework that unites the versatile packages ellc (Maxted 2016), aflare (Davenport et al. 2014), dynesty (Speagle 2019), emcee (Foreman-Mackey et al. 2013) and celerite (Foreman-Mackey et al. 2017).

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    LAPS: The Live Atmosphere-of-Planets Simulator

    Martin Turbet (LMD), Cédric Schott (ESEP) and the LMD team

    LAPS was developed to easily simulate the climate of planets similar to Earth (i.e., terrestrial but not giant planets). This model is based on the LMD (Laboratoire de Météorologie Dynamique) Global Climate Model (GCM), a complex 3-D numerical model of climate solving equations of thermodynamics, radiative transfer and hydrodynamics. This complex 3-D model has been simplified to a 1-D code (Turbet et al. 2016, 2017), which is therefore much faster to run and can now be used online in an interactive fashion.

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    LAPS: The Live Atmosphere-of-Planets Simulator

    Martin Turbet (LMD), Cédric Schott (ESEP) and the LMD team

    LAPS was developed to easily simulate the climate of planets similar to Earth (i.e., terrestrial but not giant planets). This model is based on the LMD (Laboratoire de Météorologie Dynamique) Global Climate Model (GCM), a complex 3-D numerical model of climate solving equations of thermodynamics, radiative transfer and hydrodynamics. This complex 3-D model has been simplified to a 1-D code (Turbet et al. 2016, 2017), which is therefore much faster to run and can now be used online in an interactive fashion.

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    species: Toolkit for atmospheric characterization of directly imaged exoplanets

    Tomas Stolker

    The species toolkit provides a coherent framework for spectral and photometric analysis of directly imaged exoplanets which builds on publicly-available data and models from various resources. There are tools available for both grid retrievals and free retrievals with Bayesian inference, color-magnitude and color-color diagrams, empirical spectral analysis, spectral and photometric calibration, and synthetic photometry.

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    species: Toolkit for atmospheric characterization of directly imaged exoplanets

    Tomas Stolker

    The species toolkit provides a coherent framework for spectral and photometric analysis of directly imaged exoplanets which builds on publicly-available data and models from various resources. There are tools available for both grid retrievals and free retrievals with Bayesian inference, color-magnitude and color-color diagrams, empirical spectral analysis, spectral and photometric calibration, and synthetic photometry.

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    Planetary Spectrum Generator: An Online Tool for Synthesizing Planetary Spectra

    Villanueva et al.

    The Planetary Spectrum Generator (PSG) is an online tool for synthesizing planetary spectra (atmospheres and surfaces) for a broad range of wavelengths (100 nm to 100 mm, UV/Vis/near-IR/IR/far-IR/THz/sub-mm/Radio) from any observatory (e.g., JWST, ALMA, Keck, SOFIA).

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    https://emac.gsfc.nasa.gov#?related_resource=f476b21b-8365-49f3-97ab-0f19785affef

    Planetary Spectrum Generator: An Online Tool for Synthesizing Planetary Spectra

    Villanueva et al.

    The Planetary Spectrum Generator (PSG) is an online tool for synthesizing planetary spectra (atmospheres and surfaces) for a broad range of wavelengths (100 nm to 100 mm, UV/Vis/near-IR/IR/far-IR/THz/sub-mm/Radio) from any observatory (e.g., JWST, ALMA, Keck, SOFIA).

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    ATMO Generic Grid @ ExoCTK: A Generic Model Grid of Planetary Transmission Spectra

    Jayesh Goyal et al.

    A generic model grid of planetary transmission spectra, scalable to a wide range of H2/He dominated atmospheres. The grid is computed using the 1D/2D atmosphere model ATMO for two different chemical scenarios, first considering local condensation only, secondly considering global condensation and removal of species from the atmospheric column (rainout). Using the model grid as a framework, we allow you to rescale your models with custom temperature, gravity, and radius values. The web interface is hosted and maintained by the STScI Exoplanet Characterization ToolKit.

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    ATMO Generic Grid @ ExoCTK: A Generic Model Grid of Planetary Transmission Spectra

    Jayesh Goyal et al.

    A generic model grid of planetary transmission spectra, scalable to a wide range of H2/He dominated atmospheres. The grid is computed using the 1D/2D atmosphere model ATMO for two different chemical scenarios, first considering local condensation only, secondly considering global condensation and removal of species from the atmospheric column (rainout). Using the model grid as a framework, we allow you to rescale your models with custom temperature, gravity, and radius values. The web interface is hosted and maintained by the STScI Exoplanet Characterization ToolKit.

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    https://emac.gsfc.nasa.gov#4ad1c9f8-8f65-4e35-9da7-a312fccc8866
    CGP: Reflection Spectra Repository for Cool Giant Planets 2

    Ryan J. MacDonald; Mark S. Marley; Jonathan J. Fortney; Nikole K. Lewis

    We present an extensive parameter space survey of the prominence of H2O in reflection spectra of cool giant planets. We explore the influence of a wide range of effective temperatures, gravities, metallicities, and sedimentation efficiencies, providing a grid of >50,000 models for the community. Our models range from Teff = 150 → 400 K, log(g) = 2.0–4.0 (cgs), fsed = 1–10, and log(m) = 0.0–2.0 ́ solar. We discretize this parameter space into intervals of ΔTeff = 10 K, Δlog(g) = 0.1 dex, Δfsed = 1, and Δlog(m) = 0.5 dex, generating reflection spectra both with and without H2O opacity.

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    https://emac.gsfc.nasa.gov#?related_resource=4ad1c9f8-8f65-4e35-9da7-a312fccc8866

    CGP: Reflection Spectra Repository for Cool Giant Planets 2

    Ryan J. MacDonald; Mark S. Marley; Jonathan J. Fortney; Nikole K. Lewis

    We present an extensive parameter space survey of the prominence of H2O in reflection spectra of cool giant planets. We explore the influence of a wide range of effective temperatures, gravities, metallicities, and sedimentation efficiencies, providing a grid of >50,000 models for the community. Our models range from Teff = 150 → 400 K, log(g) = 2.0–4.0 (cgs), fsed = 1–10, and log(m) = 0.0–2.0 ́ solar. We discretize this parameter space into intervals of ΔTeff = 10 K, Δlog(g) = 0.1 dex, Δfsed = 1, and Δlog(m) = 0.5 dex, generating reflection spectra both with and without H2O opacity.

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    EightBitTransit: Cython Code that can Calculate the Light Curve of any Pixelated Image

    Emily Sandford, David Kipping

    EightBitTransit is an MIT-licensed Cython code that can calculate the light curve of any pixelated image transiting a star, and invert a light curve to recover the "shadow image" that produced it. The methodology behind the code is available in Sandford & Kipping 2018 (here).

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    https://emac.gsfc.nasa.gov#?related_resource=dbaed46a-2357-4fa4-b584-7b1467475f7f

    EightBitTransit: Cython Code that can Calculate the Light Curve of any Pixelated Image

    Emily Sandford, David Kipping

    EightBitTransit is an MIT-licensed Cython code that can calculate the light curve of any pixelated image transiting a star, and invert a light curve to recover the "shadow image" that produced it. The methodology behind the code is available in Sandford & Kipping 2018 (here).

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    https://emac.gsfc.nasa.gov#179279ca-2627-4ccc-9cd3-4e260b412966
    EqTide: Tidal Evolution Simulator

    Rory Barnes

    EqTide simulates the tidal evolution of two bodies using the equilibrium tide theory. Six ordinary differential equations for the semi-major axis, eccentricity, both rotation rates, and both obliquities are integrated for a user-specified amount of time. Additionally the tidal power generated in each body is calculated. EqTide specifically simulates the constant-phase-lag model of Ferraz-Mello et al. (2008) and the constant-time-lag model of Leconte et al. (2010).

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    https://emac.gsfc.nasa.gov#?related_resource=179279ca-2627-4ccc-9cd3-4e260b412966

    EqTide: Tidal Evolution Simulator

    Rory Barnes

    EqTide simulates the tidal evolution of two bodies using the equilibrium tide theory. Six ordinary differential equations for the semi-major axis, eccentricity, both rotation rates, and both obliquities are integrated for a user-specified amount of time. Additionally the tidal power generated in each body is calculated. EqTide specifically simulates the constant-phase-lag model of Ferraz-Mello et al. (2008) and the constant-time-lag model of Leconte et al. (2010).

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    PLATON: PLanetary Atmospheric Tool for Observer Noobs

    Michael Zhang, Yayaati Chachan, Eliza Kempton, Heather Knutson

    PLATON is a Python package that can calculate transmission and emission spectra for exoplanets, as well as retrieve atmospheric characteristics based on observed spectra. PLATON is easy to install and use, with common use cases taking no more than a few lines of code. It is also fast, with the forward model taking less than 100 ms and a typical retrieval finishing in ~10 min on an ordinary desktop. PLATON supports the most common atmospheric parameters, such as temperature, metallicity, C/O ratio, cloud-top pressure, and scattering slope. It also has less commonly included features, such as a Mie scattering cloud model and unocculted starspot corrections.

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    PLATON: PLanetary Atmospheric Tool for Observer Noobs

    Michael Zhang, Yayaati Chachan, Eliza Kempton, Heather Knutson

    PLATON is a Python package that can calculate transmission and emission spectra for exoplanets, as well as retrieve atmospheric characteristics based on observed spectra. PLATON is easy to install and use, with common use cases taking no more than a few lines of code. It is also fast, with the forward model taking less than 100 ms and a typical retrieval finishing in ~10 min on an ordinary desktop. PLATON supports the most common atmospheric parameters, such as temperature, metallicity, C/O ratio, cloud-top pressure, and scattering slope. It also has less commonly included features, such as a Mie scattering cloud model and unocculted starspot corrections.

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    PyATMOS NExSci Repository: A Dataset of ~125,000 Simulated 1-D Exoplanet Atmospheres

    William Fawcett et al.

    The PyATMOS NExSci dataset comprises ~125,000 simulated 1-D exoplanet atmospheres. All of these exoplanets are based around an Earth-like planet that orbits a star similar to the Sun, but with different gas mixtures in their atmospheres. The atmospheres were generated using the PyATMOS code. The parameter space was created by incrementally varying the concentrations of carbon dioxide, oxygen, water vapour, methane, hydrogen, and nitrogen; and for each point in the parameter space an atmosphere was simulated. Other gases with negligible concentrations, such as ozone, were not varied. The planet's composition, orbital parameters and stellar parameters were also not varied.

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    https://emac.gsfc.nasa.gov#?related_resource=4d826f7c-9ec5-4efe-9121-6b1a3880a77a

    PyATMOS NExSci Repository: A Dataset of ~125,000 Simulated 1-D Exoplanet Atmospheres

    William Fawcett et al.

    The PyATMOS NExSci dataset comprises ~125,000 simulated 1-D exoplanet atmospheres. All of these exoplanets are based around an Earth-like planet that orbits a star similar to the Sun, but with different gas mixtures in their atmospheres. The atmospheres were generated using the PyATMOS code. The parameter space was created by incrementally varying the concentrations of carbon dioxide, oxygen, water vapour, methane, hydrogen, and nitrogen; and for each point in the parameter space an atmosphere was simulated. Other gases with negligible concentrations, such as ozone, were not varied. The planet's composition, orbital parameters and stellar parameters were also not varied.

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    Multipolator: Model Grid Interpolator

    Carlos E. Munoz Romero

    The multipolator package is a fast routine written in C that performs N-dimensional interpolation on a grid of astronomical models. The code finds the two closest neighbors to the input parameters in each dimension, constructs an N-dimensional hypercube, and interpolates the nearest models through inverse distance weighting.

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    Multipolator: Model Grid Interpolator

    Carlos E. Munoz Romero

    The multipolator package is a fast routine written in C that performs N-dimensional interpolation on a grid of astronomical models. The code finds the two closest neighbors to the input parameters in each dimension, constructs an N-dimensional hypercube, and interpolates the nearest models through inverse distance weighting.

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    petitRADTRANS: Tool for Calculating Transmission and Emission Spectra of Exoplanets with Clear and Cloudy Atm.

    Paul Mollière

    PetitRADTRANS (pRT) is a Python package for calculating transmission and emission spectra of exoplanets, at low (𝜆/Δ𝜆=1000) and high (𝜆/Δ𝜆=106) resolution, for clear and cloudy atmospheres. pRT offers a large variety of atomic and molecular gas opacities, cloud cross-sections from optical constants, or parametrized cloud models using either opacity power laws or grey cloud decks. The code also calculation of emission and transmission contribution functions, and contains a PHOENIX/ATLAS9 spectral library for host stars to calculate planet-to-star contrasts. Implemented examples for MCMC retrievals with pRT can be found on the code website.

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    petitRADTRANS: Tool for Calculating Transmission and Emission Spectra of Exoplanets with Clear and Cloudy Atm.

    Paul Mollière

    PetitRADTRANS (pRT) is a Python package for calculating transmission and emission spectra of exoplanets, at low (𝜆/Δ𝜆=1000) and high (𝜆/Δ𝜆=106) resolution, for clear and cloudy atmospheres. pRT offers a large variety of atomic and molecular gas opacities, cloud cross-sections from optical constants, or parametrized cloud models using either opacity power laws or grey cloud decks. The code also calculation of emission and transmission contribution functions, and contains a PHOENIX/ATLAS9 spectral library for host stars to calculate planet-to-star contrasts. Implemented examples for MCMC retrievals with pRT can be found on the code website.

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    https://emac.gsfc.nasa.gov#254de159-1880-4f91-9432-34fe093db452
    Atmos: Packaged Photochemical and Climate Model

    Claire et al.

    Atmos is a packaged photochemical model and climate model used to understand the vertical structure of various terrestrial atmospheres. Its photochemical model calculates the profiles of various chemicals in the atmosphere, including both gaseous and aerosol phases. Its climate model calculates the temperature profile of the atmosphere. While individually these models may be run for useful information, when coupled they offer a detailed analysis of atmospheric steady-state structures.

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    https://emac.gsfc.nasa.gov#?related_resource=254de159-1880-4f91-9432-34fe093db452

    Atmos: Packaged Photochemical and Climate Model

    Claire et al.

    Atmos is a packaged photochemical model and climate model used to understand the vertical structure of various terrestrial atmospheres. Its photochemical model calculates the profiles of various chemicals in the atmosphere, including both gaseous and aerosol phases. Its climate model calculates the temperature profile of the atmosphere. While individually these models may be run for useful information, when coupled they offer a detailed analysis of atmospheric steady-state structures.

    About
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    https://emac.gsfc.nasa.gov#9f58a740-de43-4c49-b50c-592c1a709ae8
    AstroImageJ: Image Display Environment and Tools for Calibration and Data Reduction

    Collins, K., Kielkopf, J., Stassun, K., and Hessman, F.

    AstroImageJ (AIJ) provides an astronomy-focused image display environment and tools for image calibration and data reduction. AIJ maintains the general purpose image processing capabilities of ImageJ, but AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to astrometry.net for plate solving images.

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    https://emac.gsfc.nasa.gov#?related_resource=9f58a740-de43-4c49-b50c-592c1a709ae8

    AstroImageJ: Image Display Environment and Tools for Calibration and Data Reduction

    Collins, K., Kielkopf, J., Stassun, K., and Hessman, F.

    AstroImageJ (AIJ) provides an astronomy-focused image display environment and tools for image calibration and data reduction. AIJ maintains the general purpose image processing capabilities of ImageJ, but AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to astrometry.net for plate solving images.

    About
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    https://emac.gsfc.nasa.gov#1c1c1140-9e52-4d89-b4d9-77846b350568
    Exoplanet Composition Interpolator: Interpolation of Pre-Computed Planet Evolution Models to Explore Structures of Transiting Exoplanets 1

    Eric Lopez, NASA GSFC

    This tool allows the user to load pre-computed planet evolution models and interpolate between those models to explore the possible structures of transiting exoplanets. Select a planet mass, radius, age, and irradiation and this tool will estimate its possible present-day gaseous envelope mass, rocky core mass, and thermal brightness.

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    https://emac.gsfc.nasa.gov#?related_resource=1c1c1140-9e52-4d89-b4d9-77846b350568

    Exoplanet Composition Interpolator: Interpolation of Pre-Computed Planet Evolution Models to Explore Structures of Transiting Exoplanets 1

    Eric Lopez, NASA GSFC

    This tool allows the user to load pre-computed planet evolution models and interpolate between those models to explore the possible structures of transiting exoplanets. Select a planet mass, radius, age, and irradiation and this tool will estimate its possible present-day gaseous envelope mass, rocky core mass, and thermal brightness.

    Demo
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    https://emac.gsfc.nasa.gov#59b5409c-cff1-49d3-b031-fc57d664a847
    StaggerGrid: A Grid of 3D stellar spectra with StaggerCode

    Chiavassa, A.; Casagrande, L.; Collet, R.; Magic, Z.; Bigot, L.; Thévenin, F.; Asplund, M.

    StaggerCode is a 3D radiation-hydrodynamic (RHD) simulation code for convection at the surface of late-type stars. The code solves the full set of hydrodynamical equations for the conservation of mass, momentum, and energy coupled to an accurate treatment of the radiative transfer. StaggerCode uses a realistic equation-of-state that accounts for ionization, recombination, and dissociation and both continuous and line opacities. Model atmosphere grids, which we call StaggerGrid, were performed with the StaggerCode for a range of temperature from 4000 to 7000 K; log(g) from 1.5 to +5.0; and metallicity of [Fe/H] = +0.5 to -4.0.
    The grid is available online at the Pollux database.

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    https://emac.gsfc.nasa.gov#?related_resource=59b5409c-cff1-49d3-b031-fc57d664a847

    StaggerGrid: A Grid of 3D stellar spectra with StaggerCode

    Chiavassa, A.; Casagrande, L.; Collet, R.; Magic, Z.; Bigot, L.; Thévenin, F.; Asplund, M.

    StaggerCode is a 3D radiation-hydrodynamic (RHD) simulation code for convection at the surface of late-type stars. The code solves the full set of hydrodynamical equations for the conservation of mass, momentum, and energy coupled to an accurate treatment of the radiative transfer. StaggerCode uses a realistic equation-of-state that accounts for ionization, recombination, and dissociation and both continuous and line opacities. Model atmosphere grids, which we call StaggerGrid, were performed with the StaggerCode for a range of temperature from 4000 to 7000 K; log(g) from 1.5 to +5.0; and metallicity of [Fe/H] = +0.5 to -4.0.
    The grid is available online at the Pollux database.

    About Demo
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    https://emac.gsfc.nasa.gov#316ff307-8a1f-4f00-ad06-e4d505e73cce
    Agatha: A Framework of Periodograms to Disentangle Periodic Signals from Correlated Noise

    Feng, F., Tuomi, M., Jones, H. R. A.