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!
  • Visit our Feedback page or email us at and tell us what you’d change or improve
  • help us determine the best tools for new web interfaces by voting on our Vote page

  • 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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    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#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#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#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#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.

    Agatha is a framework of periodograms used to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. Agatha is based on the Bayes factor periodogram (BFP) and the marginalized likelihood periodogram (MLP). Agatha outperforms other periodograms in terms of removing correlated noise and assessing the significances of signals with more robust metrics, and has been used successfully to identify planetary signals in high-precision radial velocity (RV) data. Moreover, it can be used to select the optimal noise model and to test the consistency of signals in time.

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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.

    Agatha is a framework of periodograms used to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. Agatha is based on the Bayes factor periodogram (BFP) and the marginalized likelihood periodogram (MLP). Agatha outperforms other periodograms in terms of removing correlated noise and assessing the significances of signals with more robust metrics, and has been used successfully to identify planetary signals in high-precision radial velocity (RV) data. Moreover, it can be used to select the optimal noise model and to test the consistency of signals in time.

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    https://emac.gsfc.nasa.gov#6e4f684a-cfa0-45db-90fa-23f2a38f582f
    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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    https://emac.gsfc.nasa.gov#6e4f684a-cfa0-45db-90fa-23f2a38f582f

    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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    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#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#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#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#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#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#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 (http://exoclimatology.com) 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#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 (http://exoclimatology.com) 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#8ef3e9d0-05a4-4e6a-ba0b-c0139b186676
    ATMO Exoplanet-Specific Grid: A Grid of Forward Model Transmission Spectra

    Jayesh Goyal et al.

    A grid of forward model transmission spectra, adopting an isothermal temperature-pressure profile, alongside corresponding equilibrium chemical abundances for 117 observationally significant hot exoplanets (equilibrium temperatures of 547–2710 K). This model grid has been developed using a 1D radiative–convective–chemical equilibrium model termed ATMO, with up-to-date high-temperature opacities.

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    https://emac.gsfc.nasa.gov#8ef3e9d0-05a4-4e6a-ba0b-c0139b186676

    ATMO Exoplanet-Specific Grid: A Grid of Forward Model Transmission Spectra

    Jayesh Goyal et al.

    A grid of forward model transmission spectra, adopting an isothermal temperature-pressure profile, alongside corresponding equilibrium chemical abundances for 117 observationally significant hot exoplanets (equilibrium temperatures of 547–2710 K). This model grid has been developed using a 1D radiative–convective–chemical equilibrium model termed ATMO, with up-to-date high-temperature opacities.

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    https://emac.gsfc.nasa.gov#6fdbe6b7-ea6c-4ad3-8c16-8cf4a5fa97ca
    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#6fdbe6b7-ea6c-4ad3-8c16-8cf4a5fa97ca

    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#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#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#100028c0-a2a3-42ac-a8da-5364dc9de264
    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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    https://emac.gsfc.nasa.gov#100028c0-a2a3-42ac-a8da-5364dc9de264

    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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    https://emac.gsfc.nasa.gov#4d53d561-4052-4723-ae83-1968e2bec563
    BATMAN: A Python Package for Fast Calculation of Exoplanet Transit Light Curves

    Laura Kreidberg

    BATMAN is a Python package for fast calculation of exoplanet transit light curves. The package supports calculation of light curves for any radially symmetric stellar limb darkening law, using a new integration algorithm for models that cannot be quickly calculated analytically. In typical use, BATMAN can calculate a million model light curves in well under 10 minutes for any limb darkening profile.

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    https://emac.gsfc.nasa.gov#4d53d561-4052-4723-ae83-1968e2bec563

    BATMAN: A Python Package for Fast Calculation of Exoplanet Transit Light Curves

    Laura Kreidberg

    BATMAN is a Python package for fast calculation of exoplanet transit light curves. The package supports calculation of light curves for any radially symmetric stellar limb darkening law, using a new integration algorithm for models that cannot be quickly calculated analytically. In typical use, BATMAN can calculate a million model light curves in well under 10 minutes for any limb darkening profile.

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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#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#4ad1c9f8-8f65-4e35-9da7-a312fccc8866
    CGP: Reflection Spectra Repository for Cool Giant Planets 2.0

    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#4ad1c9f8-8f65-4e35-9da7-a312fccc8866

    CGP: Reflection Spectra Repository for Cool Giant Planets 2.0

    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#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#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#0aaf653f-89a8-487d-8ca8-a3db957f9380
    Coronagraphic Mission Simulator: Simplified Coronagraph Simulator Tool

    Arney et al.

    This simplified coronagraph simulator tool is based on the coronagraph noise model in Robinson et al. 2016, adapted by J. Lustig-Yaeger, G. Arney and J. Tumlinson. The tool was developed for the LUVOIR mission concept, but can be used to simulated observations for any exoplanet coronagraphy mission.

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    https://emac.gsfc.nasa.gov#0aaf653f-89a8-487d-8ca8-a3db957f9380

    Coronagraphic Mission Simulator: Simplified Coronagraph Simulator Tool

    Arney et al.

    This simplified coronagraph simulator tool is based on the coronagraph noise model in Robinson et al. 2016, adapted by J. Lustig-Yaeger, G. Arney and J. Tumlinson. The tool was developed for the LUVOIR mission concept, but can be used to simulated observations for any exoplanet coronagraphy mission.

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    https://emac.gsfc.nasa.gov#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 (https://arxiv.org/pdf/1812.01618.pdf).

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    https://emac.gsfc.nasa.gov#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 (https://arxiv.org/pdf/1812.01618.pdf).

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    https://emac.gsfc.nasa.gov#75bf269d-e90d-4caf-a2eb-c823a495543f
    eleanor: Python Package that Extracts TESS Target Pixel Files and Produces Systematics-Corrected Light Curves

    Feinstein, A. D., Montet, B. T., Foreman-Mackey, D., et al.

    Eleanor is a Python package that extracts target pixel files from TESS Full Frame Images and produces systematics-corrected light curves for any star observed by the TESS mission. In its simplest form, eleanor takes a TIC ID, a Gaia source ID, or (RA, Dec) coordinates of a star observed by TESS and returns, as a single object, a light curve and accompanying target pixel data. Paper: Feinstein et al., eleanor: An open-source tool for extracting light curves from the TESS Full-Frame Images, 2019

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    https://emac.gsfc.nasa.gov#75bf269d-e90d-4caf-a2eb-c823a495543f

    eleanor: Python Package that Extracts TESS Target Pixel Files and Produces Systematics-Corrected Light Curves

    Feinstein, A. D., Montet, B. T., Foreman-Mackey, D., et al.

    Eleanor is a Python package that extracts target pixel files from TESS Full Frame Images and produces systematics-corrected light curves for any star observed by the TESS mission. In its simplest form, eleanor takes a TIC ID, a Gaia source ID, or (RA, Dec) coordinates of a star observed by TESS and returns, as a single object, a light curve and accompanying target pixel data. Paper: Feinstein et al., eleanor: An open-source tool for extracting light curves from the TESS Full-Frame Images, 2019

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    https://emac.gsfc.nasa.gov#6fbc34ae-f888-488b-81f2-64aa7083ff0f
    EPOS: The Exoplanet Population Observation Simulator

    Gijs Mulders

    The Exoplanet Population Observation Simulator is a software package to simulate observations of exoplanet populations. It provides an interface between planet formation simulations and exoplanet surveys such as Kepler, accounting for detection biases in transit and radial velocity surveys.

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    https://emac.gsfc.nasa.gov#6fbc34ae-f888-488b-81f2-64aa7083ff0f

    EPOS: The Exoplanet Population Observation Simulator

    Gijs Mulders

    The Exoplanet Population Observation Simulator is a software package to simulate observations of exoplanet populations. It provides an interface between planet formation simulations and exoplanet surveys such as Kepler, accounting for detection biases in transit and radial velocity surveys.

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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#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#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#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#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#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#0b8dc9b7-f9bc-410b-a968-d7a3d3c33acf
    EXOFAST: Fitting Tool for RV and Astrometric Datasets Observed with any Combination of Wavelengths

    Jason Eastman et al.

    EXOFASTv2 can fit an arbitrary number of planets, radial velocity datasets, astrometric datasets, and/or transits observed with any combination of wavelengths. We model the star simultaneously in the fit and provide several state-of-the-art ways to constrain its properties, including taking advantage of the now-ubiquitous all-sky catalog photometry and Gaia parallaxes. EXOFASTv2 can model the star by itself, too. Multi-planet systems are modeled self-consistently with the same underlying stellar mass that defines their semi-major axes through Kepler's law and the planetary period. Transit timing, duration, and depth variations can be modeled with a simple command line option.

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    https://emac.gsfc.nasa.gov#0b8dc9b7-f9bc-410b-a968-d7a3d3c33acf

    EXOFAST: Fitting Tool for RV and Astrometric Datasets Observed with any Combination of Wavelengths

    Jason Eastman et al.

    EXOFASTv2 can fit an arbitrary number of planets, radial velocity datasets, astrometric datasets, and/or transits observed with any combination of wavelengths. We model the star simultaneously in the fit and provide several state-of-the-art ways to constrain its properties, including taking advantage of the now-ubiquitous all-sky catalog photometry and Gaia parallaxes. EXOFASTv2 can model the star by itself, too. Multi-planet systems are modeled self-consistently with the same underlying stellar mass that defines their semi-major axes through Kepler's law and the planetary period. Transit timing, duration, and depth variations can be modeled with a simple command line option.

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    https://emac.gsfc.nasa.gov#ae3cf01e-f27d-4e19-a59c-95fa8da44d8d
    Exoplanet Boundaries Calculator: An Online Condensations Boundary Calculator 1.1

    Kopparapu et al.

    The Exoplanet Boundaries Calculator (EBC) is an online calculator that provides condensation boundaries (in stellar fluxes) for ZnS, H2O, CO2 and CH4 for the following planetary radii that represent transition to different planet regimes: 0.5, 1, 1.75, 3.5, 6, and 14.3 RE. The purpose is to classify planets into different categories based on a species condensing in a planet's atmosphere. These boundaries are applicable only for G-dwarf stars.

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    https://emac.gsfc.nasa.gov#ae3cf01e-f27d-4e19-a59c-95fa8da44d8d

    Exoplanet Boundaries Calculator: An Online Condensations Boundary Calculator 1.1

    Kopparapu et al.

    The Exoplanet Boundaries Calculator (EBC) is an online calculator that provides condensation boundaries (in stellar fluxes) for ZnS, H2O, CO2 and CH4 for the following planetary radii that represent transition to different planet regimes: 0.5, 1, 1.75, 3.5, 6, and 14.3 RE. The purpose is to classify planets into different categories based on a species condensing in a planet's atmosphere. These boundaries are applicable only for G-dwarf stars.

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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 1.0

    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#1c1c1140-9e52-4d89-b4d9-77846b350568

    Exoplanet Composition Interpolator: Interpolation of Pre-Computed Planet Evolution Models to Explore Structures of Transiting Exoplanets 1.0

    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#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#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#29cbd804-9b28-4fcf-8a44-c1b9bceb3bdd
    EXOSIMS: Python Based Framework for the Simulation and Analysis of Exoplanet Imaging Space Missions

    Savransky et al.

    EXOSIMS is a modular, open source, Python-based framework for the simulation and analysis of exoplanet imaging space missions. The base code is highly extensible and allows for the end-to-end simulation of imaging missions, taking into account details about the spacecraft, its orbit, the instrumentation, the assumed population of exoplanets, and the mission operating rules.

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    https://emac.gsfc.nasa.gov#29cbd804-9b28-4fcf-8a44-c1b9bceb3bdd

    EXOSIMS: Python Based Framework for the Simulation and Analysis of Exoplanet Imaging Space Missions

    Savransky et al.

    EXOSIMS is a modular, open source, Python-based framework for the simulation and analysis of exoplanet imaging space missions. The base code is highly extensible and allows for the end-to-end simulation of imaging missions, taking into account details about the spacecraft, its orbit, the instrumentation, the assumed population of exoplanets, and the mission operating rules.

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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#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#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#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#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#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#2266c18c-f059-40e3-9c54-960cb423f4ac
    HARDCORE: A Core Radius Fractions Exoplanet Online Calculator

    Gabrielle Suissa, Jingjing Chen, David Kipping; Yosef Miller

    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, and the web interface was developed independently by Yosef Miller.

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    https://emac.gsfc.nasa.gov#2266c18c-f059-40e3-9c54-960cb423f4ac

    HARDCORE: A Core Radius Fractions Exoplanet Online Calculator

    Gabrielle Suissa, Jingjing Chen, David Kipping; Yosef Miller

    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, and the web interface was developed independently by Yosef Miller.

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    https://emac.gsfc.nasa.gov#282689a8-72a3-4fb5-8223-f3d01365ee58
    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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    https://emac.gsfc.nasa.gov#282689a8-72a3-4fb5-8223-f3d01365ee58

    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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    https://emac.gsfc.nasa.gov#058599b8-7ba0-4e39-a1aa-65d80e9f84cf
    HELIOS: Open-Sourced RT Code to Study Exoplanetary Astrmopsheres

    Malik et al.

    HELIOS is an open-source radiative transfer code designed to study exoplanetary atmospheres, from rocky terrestrial planets to ultra-hot Jupiters. For given opacities and planetary parameters, HELIOS finds the atmospheric temperature profile in radiative-convective equilibrium and the synthetic planetary emission spectrum. HELIOS is written in Python, with the core computations parallelized to run on a GPU. HELIOS is part of the Exoclimes Simulation Platform.

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    https://emac.gsfc.nasa.gov#058599b8-7ba0-4e39-a1aa-65d80e9f84cf

    HELIOS: Open-Sourced RT Code to Study Exoplanetary Astrmopsheres

    Malik et al.

    HELIOS is an open-source radiative transfer code designed to study exoplanetary atmospheres, from rocky terrestrial planets to ultra-hot Jupiters. For given opacities and planetary parameters, HELIOS finds the atmospheric temperature profile in radiative-convective equilibrium and the synthetic planetary emission spectrum. HELIOS is written in Python, with the core computations parallelized to run on a GPU. HELIOS is part of the Exoclimes Simulation Platform.

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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#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#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 at https://juliet.readthedocs.io/en/latest/.

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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 at https://juliet.readthedocs.io/en/latest/.

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    https://emac.gsfc.nasa.gov#d04ccd95-80f9-4e14-985b-e00436644e19
    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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    https://emac.gsfc.nasa.gov#d04ccd95-80f9-4e14-985b-e00436644e19

    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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    https://emac.gsfc.nasa.gov#16158121-c49b-4f61-b918-4222fe0d4076
    Lightkurve: Python Package that Analyzes Astronomical Flux Time Series Data

    Vinícius, Barentsen, Hedges, et al.

    The lightkurve Python package offers a beautiful and user-friendly way to analyze astronomical flux time series data, in particular the pixels and lightcurves obtained by NASA’s Kepler, K2, and TESS missions.

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    https://emac.gsfc.nasa.gov#16158121-c49b-4f61-b918-4222fe0d4076

    Lightkurve: Python Package that Analyzes Astronomical Flux Time Series Data

    Vinícius, Barentsen, Hedges, et al.

    The lightkurve Python package offers a beautiful and user-friendly way to analyze astronomical flux time series data, in particular the pixels and lightcurves obtained by NASA’s Kepler, K2, and TESS missions.

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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#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#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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    https://emac.gsfc.nasa.gov#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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    https://emac.gsfc.nasa.gov#6602dbe5-e5d8-43e2-8816-2e062bc7f033
    MESA: Modules for Experiments in Stellar Astrophysics

    MESA Team (Paxton et al.)

    The 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 with an implicit finite volume scheme. The MESA source code is one part of the larger MESA project.

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    https://emac.gsfc.nasa.gov#6602dbe5-e5d8-43e2-8816-2e062bc7f033

    MESA: Modules for Experiments in Stellar Astrophysics

    MESA Team (Paxton et al.)

    The 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 with an implicit finite volume scheme. The MESA source code is one part of the larger MESA project.

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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#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#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#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#894bdb18-f942-4b88-8501-0f8c29cda04c
    Multiplanet Yield Tool: A Tool to Visualize Exoplanet Mission Yield Simulations

    Christopher Stark, Jason Tumlinson, et al.

    This tool visualizes the results of detailed exoplanet mission yield simulations, calculated using the planet classifications from Kopparapu et al. (in preparation). The methodology is described in Stark et al. (2014), ApJ, 795, 122 and Stark et al. (2015), ApJ, 808, 149. The Python code to render the results was written by Jason Tumlinson. This tool was developed to support the LUVOIR Mission Concept Study Report, pending submission to the Astro2020 Decadal Survey.

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    https://emac.gsfc.nasa.gov#894bdb18-f942-4b88-8501-0f8c29cda04c

    Multiplanet Yield Tool: A Tool to Visualize Exoplanet Mission Yield Simulations

    Christopher Stark, Jason Tumlinson, et al.

    This tool visualizes the results of detailed exoplanet mission yield simulations, calculated using the planet classifications from Kopparapu et al. (in preparation). The methodology is described in Stark et al. (2014), ApJ, 795, 122 and Stark et al. (2015), ApJ, 808, 149. The Python code to render the results was written by Jason Tumlinson. This tool was developed to support the LUVOIR Mission Concept Study Report, pending submission to the Astro2020 Decadal Survey.

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    https://emac.gsfc.nasa.gov#c90543b9-3469-43a5-b92a-96ee6797120b
    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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    https://emac.gsfc.nasa.gov#c90543b9-3469-43a5-b92a-96ee6797120b

    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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    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#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#cc7ee729-edca-42e5-922a-39943e2536f0
    orbitize!: Package for Orbit-Fitting of Directly Imaged Objects

    Sarah Blunt, Jason Wang, Henry Ngo, Isabel Angelo, et al. Full list here.

    Orbitize! is a package for orbit-fitting of directly imaged objects (anything with relative astrometric measurements). It packages the OFTI algorithm and two flavors of MCMC into a consistent API. It’s written to be fast, extensible, and easy-to-use. Extensive tutorials are available here. Up-to-date documentation is available at orbitize.info.

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    https://emac.gsfc.nasa.gov#cc7ee729-edca-42e5-922a-39943e2536f0

    orbitize!: Package for Orbit-Fitting of Directly Imaged Objects

    Sarah Blunt, Jason Wang, Henry Ngo, Isabel Angelo, et al. Full list here.

    Orbitize! is a package for orbit-fitting of directly imaged objects (anything with relative astrometric measurements). It packages the OFTI algorithm and two flavors of MCMC into a consistent API. It’s written to be fast, extensible, and easy-to-use. Extensive tutorials are available here. Up-to-date documentation is available at orbitize.info.

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    https://emac.gsfc.nasa.gov#8ec7054b-ae60-4874-aa33-fee77dd5dc53
    PandExo: JWST/HST Simulator

    Batalha et al.

    PandExo is both an online tool and a Python package for generating instrument simulations of JWST's NIRSpec, NIRCam, NIRISS and NIRCam and HST WFC3. It uses throughput calculations from STScI's Exposure Time Calculator, Pandeia.

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    https://emac.gsfc.nasa.gov#8ec7054b-ae60-4874-aa33-fee77dd5dc53

    PandExo: JWST/HST Simulator

    Batalha et al.

    PandExo is both an online tool and a Python package for generating instrument simulations of JWST's NIRSpec, NIRCam, NIRISS and NIRCam and HST WFC3. It uses throughput calculations from STScI's Exposure Time Calculator, Pandeia.

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    https://emac.gsfc.nasa.gov#aad6314c-60f2-43be-b1cf-b4951fd9d3a9
    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#aad6314c-60f2-43be-b1cf-b4951fd9d3a9

    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#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#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#8fd58a04-ef00-48d1-8e37-548771472b21
    PICASO: Open-Source RT Model for Computing Reflected Exoplanet Light at any Phase Geometry

    Natasha Batalha, Mark Marley, Nikole Lewis, Jonathon Fortney

    IN PROGRESS — The Planetary Intensity Code for Atmospheric Scattering Observations (PICASO) is an open-source radiative transfer model for computing the reflected light of exoplanets at any phase geometry. This code, written in Python, has heritage from a decades old, well-known Fortran model used for several studies of planetary objects within the Solar System and beyond. We have adopted it to include several methodologies for computing both direct and diffuse scattering phase functions, and have added several updates including the ability to compute Raman scattering spectral features.

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    https://emac.gsfc.nasa.gov#8fd58a04-ef00-48d1-8e37-548771472b21

    PICASO: Open-Source RT Model for Computing Reflected Exoplanet Light at any Phase Geometry

    Natasha Batalha, Mark Marley, Nikole Lewis, Jonathon Fortney

    IN PROGRESS — The Planetary Intensity Code for Atmospheric Scattering Observations (PICASO) is an open-source radiative transfer model for computing the reflected light of exoplanets at any phase geometry. This code, written in Python, has heritage from a decades old, well-known Fortran model used for several studies of planetary objects within the Solar System and beyond. We have adopted it to include several methodologies for computing both direct and diffuse scattering phase functions, and have added several updates including the ability to compute Raman scattering spectral features.

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    https://emac.gsfc.nasa.gov#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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    https://emac.gsfc.nasa.gov#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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    https://emac.gsfc.nasa.gov#0a1ca53d-2b61-46d1-81a1-4bbb4fc07fb8
    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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    https://emac.gsfc.nasa.gov#0a1ca53d-2b61-46d1-81a1-4bbb4fc07fb8

    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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    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#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#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#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#a6b3d1ae-9c2c-4e84-9f82-8a30ffcc6d9b
    PyATMOS: Software Package to Configure and Run the Virtual Planetary Laboratories' ATMOS Software

    William Fawcett et al.

    PyATMOS is a software package able to configure and run the Virtual Planetary Laboratories' ATMOS software, which is an exoplanetary atmosphere simulator. PyATMOS is written in Python, allowing easy user configuration and running, and is optionally configurable with Docker and therefore can be used on any machine with Docker and Python installed, regardless of the operating system. PyATMOS can be used in "single-use" mode, simulating a single exoplanet atmosphere with a given set of atmospheric parameters, but also in a parallel mode, whereby a grid of possible parameters for many atmospheres is supplied. PyATMOS will explore this parameter space and produce a database of the results.

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    https://emac.gsfc.nasa.gov#a6b3d1ae-9c2c-4e84-9f82-8a30ffcc6d9b

    PyATMOS: Software Package to Configure and Run the Virtual Planetary Laboratories' ATMOS Software

    William Fawcett et al.

    PyATMOS is a software package able to configure and run the Virtual Planetary Laboratories' ATMOS software, which is an exoplanetary atmosphere simulator. PyATMOS is written in Python, allowing easy user configuration and running, and is optionally configurable with Docker and therefore can be used on any machine with Docker and Python installed, regardless of the operating system. PyATMOS can be used in "single-use" mode, simulating a single exoplanet atmosphere with a given set of atmospheric parameters, but also in a parallel mode, whereby a grid of possible parameters for many atmospheres is supplied. PyATMOS will explore this parameter space and produce a database of the results.

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    https://emac.gsfc.nasa.gov#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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    https://emac.gsfc.nasa.gov#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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    https://emac.gsfc.nasa.gov#c37c4b80-07f8-4ad2-9b60-a4686b4084d9
    pyKLIP: Tool for the Characterization of Directly-Imaged Exoplanets and Circumstellar Disk

    Wang, J. et al.

    pyKLIP subtracts out the stellar PSF to search for and characterize directly-imaged exoplanets and circumstellar disks using a Python implementation of the Karhunen-Loève Image Projection (KLIP) algorithm. pyKLIP supports using ADI, SDI, and RDI observing techniques and parallelizes the KLIP algorithm to speed up the reduction. pyKLIP supports data from most high-contrast imaging instruments and provides libraries to both detect and characterize astrophysical sources in the data.

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    https://emac.gsfc.nasa.gov#c37c4b80-07f8-4ad2-9b60-a4686b4084d9

    pyKLIP: Tool for the Characterization of Directly-Imaged Exoplanets and Circumstellar Disk

    Wang, J. et al.

    pyKLIP subtracts out the stellar PSF to search for and characterize directly-imaged exoplanets and circumstellar disks using a Python implementation of the Karhunen-Loève Image Projection (KLIP) algorithm. pyKLIP supports using ADI, SDI, and RDI observing techniques and parallelizes the KLIP algorithm to speed up the reduction. pyKLIP supports data from most high-contrast imaging instruments and provides libraries to both detect and characterize astrophysical sources in the data.

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    https://emac.gsfc.nasa.gov#82c8344a-f845-4b4d-9b79-7a28b668d736
    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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    https://emac.gsfc.nasa.gov#82c8344a-f845-4b4d-9b79-7a28b668d736

    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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    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#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#e6b635b8-53c3-43ac-9ff4-63c47b8fe19c
    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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    https://emac.gsfc.nasa.gov#e6b635b8-53c3-43ac-9ff4-63c47b8fe19c

    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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    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#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#517bf2ca-4143-4c3e-9045-5c937ca769e1
    species: Python Package for Spectral and Photometric Analysis of Self-Luminous, Planetary and Substellar Atm.

    Tomas Stolker

    The species toolkit is a Python package for spectral and photometric analysis of self-luminous, planetary and substellar atmospheres. It provides a coherent framework for atmospheric characterization which builds on publicly-available data from various resources such as spectral and photometric libraries, atmospheric models, evolutionary models, photometry of directly imaged planets, and filter transmission profiles. All data are stored in a central database and there are tools available for extracting, inspecting, analyzing, and plotting of data, models, and results.

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    https://emac.gsfc.nasa.gov#517bf2ca-4143-4c3e-9045-5c937ca769e1

    species: Python Package for Spectral and Photometric Analysis of Self-Luminous, Planetary and Substellar Atm.

    Tomas Stolker

    The species toolkit is a Python package for spectral and photometric analysis of self-luminous, planetary and substellar atmospheres. It provides a coherent framework for atmospheric characterization which builds on publicly-available data from various resources such as spectral and photometric libraries, atmospheric models, evolutionary models, photometry of directly imaged planets, and filter transmission profiles. All data are stored in a central database and there are tools available for extracting, inspecting, analyzing, and plotting of data, models, and results.

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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#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#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#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#5130a84a-aa30-4b7e-bda9-300a5a77c306
    STARRY: Analytic Occultation Light Curves

    Rodrigo Luger, Eric Agol, Daniel Foreman-Mackey, David P. Fleming, Jacob Lustig-Yaeger, Russell Deitrick

    IN PROGRESS — The STARRY code package enables the computation of light curves for various applications in astronomy: transits and secondary eclipses of exoplanets, light curves of eclipsing binaries, rotational phase curves of exoplanets, light curves of planet-planet and planet-moon occultations, and more. By modeling celestial body surface maps as sums of spherical harmonics, STARRY does all this analytically and is therefore fast, stable, and differentiable. Coded in C++ but wrapped in Python, STARRY is easy to install and use.

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    https://emac.gsfc.nasa.gov#5130a84a-aa30-4b7e-bda9-300a5a77c306

    STARRY: Analytic Occultation Light Curves

    Rodrigo Luger, Eric Agol, Daniel Foreman-Mackey, David P. Fleming, Jacob Lustig-Yaeger, Russell Deitrick

    IN PROGRESS — The STARRY code package enables the computation of light curves for various applications in astronomy: transits and secondary eclipses of exoplanets, light curves of eclipsing binaries, rotational phase curves of exoplanets, light curves of planet-planet and planet-moon occultations, and more. By modeling celestial body surface maps as sums of spherical harmonics, STARRY does all this analytically and is therefore fast, stable, and differentiable. Coded in C++ but wrapped in Python, STARRY is easy to install and use.

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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#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#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#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#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#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#7d08589f-b654-47e8-be3a-ebad9aca2640
    THAI: TRAPPIST Habitable Atmosphere Intercomparison GCM Data Repository

    THAI Team (T. Fauchez, I. Boutle , M. Turbet, M. Way, E. Wolf, et al.)

    The TRAPPIST Habitable Atmosphere Intercomparison (THAI) project is a model inter-comparison effort between four GCMs: ROCKE3D, ExoCAM, LMD-G and UM – examining a single interesting test case (TRAPPIST-1e) under several different atmosphere scenarios. The data repository provides NetCDF files for each case, allowing for examination and intercomparison of results from the different models. The protocol of the intercomparison is published in Fauchez et al. 2019, GMD (https://doi.org/10.5194/gmd-13-707-2020)

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    https://emac.gsfc.nasa.gov#7d08589f-b654-47e8-be3a-ebad9aca2640

    THAI: TRAPPIST Habitable Atmosphere Intercomparison GCM Data Repository

    THAI Team (T. Fauchez, I. Boutle , M. Turbet, M. Way, E. Wolf, et al.)

    The TRAPPIST Habitable Atmosphere Intercomparison (THAI) project is a model inter-comparison effort between four GCMs: ROCKE3D, ExoCAM, LMD-G and UM – examining a single interesting test case (TRAPPIST-1e) under several different atmosphere scenarios. The data repository provides NetCDF files for each case, allowing for examination and intercomparison of results from the different models. The protocol of the intercomparison is published in Fauchez et al. 2019, GMD (https://doi.org/10.5194/gmd-13-707-2020)

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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#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#0d601575-94ac-4be9-8b70-c0f43cc27ae8
    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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    https://emac.gsfc.nasa.gov#0d601575-94ac-4be9-8b70-c0f43cc27ae8

    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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    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#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#0411595b-6d94-480a-8abc-ebe814fa867f
    tpfplotter: TESS Target Pixel File Creator

    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#0411595b-6d94-480a-8abc-ebe814fa867f

    tpfplotter: TESS Target Pixel File Creator

    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#765ab561-a499-45b2-862c-7f5b6d0f6fa0
    Transit Least Squares: A Least Square Algorithm to Detect Planetary Transits from Time-Series Photometry

    Michael Hippke, René Heller

    The Transit Least Squares (TLS) algorithm is a method to detect planetary transits from time-series photometry. While the commonly used Box Least Squares (BLS, Kovács et al. 2002) algorithm searches for rectangular signals in stellar light curves, TLS searches for transit-like features with stellar limb-darkening and including the effects of planetary ingress and egress. Moreover, TLS analyses the entire, unbinned data of the phase-folded light curve. These improvements yield a ~10 % higher detection efficiency (and similar false alarm rates) compared to BLS.

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    https://emac.gsfc.nasa.gov#765ab561-a499-45b2-862c-7f5b6d0f6fa0

    Transit Least Squares: A Least Square Algorithm to Detect Planetary Transits from Time-Series Photometry

    Michael Hippke, René Heller

    The Transit Least Squares (TLS) algorithm is a method to detect planetary transits from time-series photometry. While the commonly used Box Least Squares (BLS, Kovács et al. 2002) algorithm searches for rectangular signals in stellar light curves, TLS searches for transit-like features with stellar limb-darkening and including the effects of planetary ingress and egress. Moreover, TLS analyses the entire, unbinned data of the phase-folded light curve. These improvements yield a ~10 % higher detection efficiency (and similar false alarm rates) compared to BLS.

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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#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#6591c1f5-d392-4550-80a3-5d8eda34c1e6
    TROPF: Tidal Response Of Planetary Fluids

    Robert Tyler

    The TROPF (Tidal Response Of Planetary Fluids) software package is a MATLAB/Octave package that enables efficient terrestrial fluid tidal studies across a wide range of parameter space. TROPF includes several different solutions to the governing equations in classical tidal theory, and can calculate millions of such solutions on several-minute-long timescales. A comprehensive manual is included in the distribution directory. To help improve the development of TROPF, or become involved in future releases, please send feedback to rtyler@umbc.edu.

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    https://emac.gsfc.nasa.gov#6591c1f5-d392-4550-80a3-5d8eda34c1e6

    TROPF: Tidal Response Of Planetary Fluids

    Robert Tyler

    The TROPF (Tidal Response Of Planetary Fluids) software package is a MATLAB/Octave package that enables efficient terrestrial fluid tidal studies across a wide range of parameter space. TROPF includes several different solutions to the governing equations in classical tidal theory, and can calculate millions of such solutions on several-minute-long timescales. A comprehensive manual is included in the distribution directory. To help improve the development of TROPF, or become involved in future releases, please send feedback to rtyler@umbc.edu.

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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#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#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#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#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#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#848882ca-0360-49cc-bea1-00f462b6259b
    VPLanet: Planetary System Evolution Simulator

    Rory Barnes et al.

    VPLanet simulates numerous aspects of planetary system evolution with a single executable: 1) thermal and magnetic evolution of terrestrial planets, 2) magma oceans, 3) radiogenic heating of interiors, 4) tidal effects, 5) rotational axis evolution, 6) stellar evolution, including pre-MS, XUV, and spin-down, 7) climate via a 1-D EBM, 8) atmospheric escape, including water photolysis and H escape, 9) approximate orbital evolution, 10) exact orbital evolution, 11) circumbinary planet orbits, and 12) galactic perturbations on planetary systems. The code is validated by reproducing selected Solar System, exoplanet, and binary star properties. Documentation and numerous examples are provided.

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    https://emac.gsfc.nasa.gov#848882ca-0360-49cc-bea1-00f462b6259b

    VPLanet: Planetary System Evolution Simulator

    Rory Barnes et al.

    VPLanet simulates numerous aspects of planetary system evolution with a single executable: 1) thermal and magnetic evolution of terrestrial planets, 2) magma oceans, 3) radiogenic heating of interiors, 4) tidal effects, 5) rotational axis evolution, 6) stellar evolution, including pre-MS, XUV, and spin-down, 7) climate via a 1-D EBM, 8) atmospheric escape, including water photolysis and H escape, 9) approximate orbital evolution, 10) exact orbital evolution, 11) circumbinary planet orbits, and 12) galactic perturbations on planetary systems. The code is validated by reproducing selected Solar System, exoplanet, and binary star properties. Documentation and numerous examples are provided.

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