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've used EMAC in any part of your research, please cite our RNAAS paper either in your methods section or in the "Software used" portion of any manuscripts; see the FAQ for more information.
More Information on EMAC for first-time visitors...
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!
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Help us improve EMAC!
-
Email us with general feedback at
and tell us what you'd change or improve.
- Click the
icon in a resource box to provide suggestions for an individual tool or tools.
Other EMAC info!
- 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 our Submit a Resource page.
- For help with tutorials for select resources/tools use the “Demo” buttons 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.
EMAC co-leads are Joe P. Renaud and Eric Lopez; more information on EMAC staffing and organization can be found on Our Team page.
EMAC has launched a new community-supported curator program, and we need your help! Check out our
curator page to learn how exoplanet experts like yourself can support EMAC's mission, and help us spread the word about this new initiative!
Eureka! is a data reduction and analysis pipeline for exoplanet time-series observations, with a particular focus on James Webb Space Telescope (JWST) data. The goal of Eureka! is to provide an end-to-end pipeline that starts with raw, uncalibrated FITS files and ultimately yields precise exoplanet transmission and/or emission spectra. The pipeline has a modular structure with six stages, each with intermediate figures and outputs that allow users to compare Eureka!’s performance using different parameter settings or to compare Eureka! with an independent pipeline.
Code Language(s): Python3
Last updated: May. 6, 2025
Version: v1.2.1
Subcategories:
Spectroscopy Data Red.
Lightcurve Fitting
Eclipsoid provides a general framework allowing rotational deformation to be modeled in transits, occultations, phase curves, transmission spectra and more of bodies in orbit around each other, such as an exoplanet orbiting a host star.
Code Language(s):
Last updated: Apr. 8, 2025
Subcategories:
Spectroscopy Data Red.
Lightcurve Fitting
Transit/Eclipse RT
StellarSpectraObservationFitting.jl is a Julia package for measuring Doppler shifts and creating data-driven models (with fast, physically-motivated Gaussian Process regularization) for the time-variable spectral features for both the telluric transmission and stellar spectrum, while accounting for the wavelength-dependent instrumental line-spread function.
Code Language(s): Julia
Last updated: Apr. 8, 2025
Version: v0.1.3
Subcategories:
Spectroscopy Data Red.
RV Fitting
Stellar Models and Spectra
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.
Code Language(s): Python3
Last updated: Mar. 24, 2025
Version: v1.8
Subcategories:
Direct Imaging Data Red.
Tiberius is a Python library for reducing time series spectra and fitting exoplanet transit light curves. This can be used to extract spectra from JWST (all 4 instruments), along with ground-based long-slit spectrographs and Keck/NIRSPEC echelle spectra (beta).
The light curve fitting routines can be used as as standalone to fit, for example, HST light curves extracted with other methods.
Code Language(s): Python
Last updated: Mar. 24, 2025
Version: v1.0.4
Subcategories:
Spectroscopy Data Red.
Lightcurve Fitting
A Python 3 package for analyzing photometric data of transiting exoplanets into lightcurves and retrieving transit epochs and planetary radii.
EXOTIC can run on a Windows, Macintosh, or Linux/Unix computer. You can also use EXOTIC via the free Google Colab, which features cloud computing, many helpful plotting functions, and a simplified installation. However, if you are a user with many images or large images, we recommend running EXOTIC locally on your own computer.
Code Language(s): Python3
Last updated: Mar. 24, 2025
Version: 4.3.1
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Lightcurve Fitting
VIP is a Python package for high-contrast imaging of exoplanets and circumstellar disks. The goal of VIP is to integrate open-source, efficient, easy-to-use and well-documented implementations of state-of-the-art high-contrast image processing algorithms. In addition, it also contains a number of routines for image preprocessing, performance assessment and the characterization of both point and extended sources.
VIP started as the effort of Carlos Alberto Gomez Gonzalez, a former PhD student of the VORTEX team (ULiège, Belgium). Since 2020, Dr. Valentin Christiaens (ULiège) has been in charge of VIP's maintenance and development lead.
Code Language(s): Python3
Last updated: Mar. 24, 2025
Version: v1.6.6
Subcategories:
Direct Imaging Data Red.
excalibuhr is a Python package for data reduction of high-resolution spectroscopy of exoplanets and brown dwarfs. It has an end-to-end pipeline for VLT/CRIRES+.
Code Language(s): Python3
Last updated: Feb. 18, 2025
Version: v0.1.1
Subcategories:
Spectroscopy Data Red.
The Generic data Reduction for nulling Interferometry Package (GRIP) aims to provide a universal pipeline to all existing and future nullers. GRIP aims to provide self-calibrated null depth measurements by fitting a model of the instrumental perturbations to histograms of data. The model is generated using a simulator of the instrument, which can be provided by the user or is built into the package for the main operating nullers
Code Language(s): Python
Last updated: Feb. 18, 2025
Version: v1.5.1
Subcategories:
Data Reduction Tools
Model-Fitting Tools
TESS-Gaia Light Curve (TGLC) is a PSF-based TESS full-frame image (FFI) light curve product. Using Gaia DR3 as priors, the team forward models the FFIs with the effective point spread function to remove contamination from nearby stars. The resulting light curves show a photometric precision closely tracking the pre-launch prediction of the noise level: TGLC's photometric precision consistently reaches ≲2% at 16th TESS magnitude even in crowded fields, demonstrating excellent decontamination and deblending power.
Code Language(s): Python3
Last updated: Oct. 25, 2024
Version: 0.6.6
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Photometry Instr. Models
The Time Series Helper & Integration Reduction Tool tshirt is a general-purpose tool for time series science. Its main application is to process raw data on exoplanet systems. tshirt can:
- Reduce raw data: flat field, bias subtract, gain correct, etc. This has been demonstrated to work with merged CCD images from Mont4K imager on the Kuiper-61 inch on Mt Bigelow, AZ.
- Extract Photometry
- Extract Spectroscopy
Code Language(s): Python3
Last updated: Sep. 18, 2024
Version: v0.4
Subcategories:
Spectroscopy Data Red.
Photometry Data Red.
IGRINS transit is a pipeline to take high-resolution observations of transiting exoplanets with Gemini-S/IGRINS and produce cross-correlation detections of molecules in the exoplanet's atmosphere.
Code Language(s): Python3
Last updated: Sep. 6, 2024
Version: v1.0
Subcategories:
Spectroscopy Data Red.
The data reduction pipeline for the Keck Planet Imager and Characterizer. It is used for processing high resolution spectroscopy data taken with KPIC to study exoplanet atmospheres. Designed to process and calibrate KPIC data to enable spectroscopic model fitting.
Code Language(s): Python
Last updated: Jul. 2, 2024
Subcategories:
Spectroscopy Data Red.
Direct Imaging Data Red.
breads, or the Broad Repository for Exoplanet Analysis, Detection, and Spectroscopy, is a flexible framework that allows forward modeling of data from moderate to high resolution spectrographs. The philosophy of breads is to have the users choose a data class, a forward model function, and a fitting strategy. Data classes normalize the data format, simplifying reduction across different spectrographs while allowing for specific behaviors of each instrument to also be coded into their own specific class. The forward model (FM) aims to reproduce the data (d) as d = FM + n, where n is the noise.
Code Language(s): Python3
Last updated: Jun. 6, 2024
Version: 0.2
Subcategories:
Spectroscopy Data Red.
Direct Imaging Data Red.
An open-source TESS FFI pipeline to access TESS data, produce noise-corrected light curves, and search for planets transiting evolved stars, with an emphasis on detecting planets around subgiant and RGB stars. The giants pipeline produces a one-page PDF summary for each target including the following vetting materials. Built with Lightkurve.
Code Language(s): Python3
Last updated: May. 13, 2024
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Lightcurve Fitting
The exovetter package provide statistical metrics and quick visualizations needed when evaluating a periodic transit found in time domain photometry, such as Kepler and TESS. This code wraps codes used to evaluate TESS, Kepler and K2 transit-like signals in order to remove obvious false positives.
Code Language(s): python
Last updated: Mar. 28, 2024
Version: 0.0.8
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Lightcurve Fitting
Collections:
K2
Kepler
TESS
The TIKE (Time series Integrated Knowledge Engine) is a new service being offered by STScI to support astronomers working with the time series data archived at MAST, such as data from NASA's TESS, Kepler and K2 missions. This tool is built on the Pangeo deployment of JupyterHub, using Kubernetes in AWS. TIKE is a platform where astronomers can make use of data science utilities, astronomy software, and community software packages to retrieve and analyze data sets without having to download the data to their machines or maintain their own set of python packages.
Code Language(s): Docker, k8s, AWS, Jupyterhub
Last updated: Mar. 27, 2024
Version: 0.12.0
Subcategories:
Spectroscopy Data Red.
Photometry Data Red.
Lightcurve Visualization
Lightcurve Fitting
Exoplanet Observation Catalogs
Collections:
K2
Kepler
TESS
A simple tool to process near-infrared high-resolution spectra for the atmospheric characterisation of transiting exoplanets. The code remove the stellar and Earth atmosphere spectra and correct for systematics in a data-driven way (e.g. principal component analysis or auto-encoders). It contains a planet atmosphere retrieval (nested sampling algorithm). The code is initially designed to work with telluric-corrected SPIRou transmission spectra, but could be easily adapted to other instruments (e.g. GEMINI-IGRINS, VLT-CRIRES+, ESO-NIRP) and to emission spectroscopy.
Code Language(s): Python3
Last updated: Mar. 26, 2024
Subcategories:
Spectroscopy Data Red.
V1.0 of CUTE data reduction pipeline.
This software is intented to be fully automated, aimed at producing science-quality output with a single command line with zero user interference for CUTE data. It can be easily used for any single order spectral data in any wavelength without any modification.
Code Language(s): IDL
Last updated: Mar. 26, 2024
Subcategories:
Data Reduction Tools
Formerly known as supreme-SPOON, exoTEDRF is an end-to-end pipeline for the reduction of JWST exoplanet time series observations (NIRISS and NIRSpec currently supported, MIRI in development).
Code Language(s): Python3
Last updated: Mar. 22, 2024
Version: v2.3.1
Subcategories:
Spectroscopy Data Red.
Spectroscopy Instr. Models
Collections:
JWST
JWST - Direct Imaging Data Reduction
A tool to produce empirical 2D point spread functions for JWST NIRISS/SOSS observations. These PSFs are necessary input for the ATOCA extraction algorithm implemented in the STScI calibration pipeline.
Code Language(s): Python3
Last updated: Mar. 22, 2024
Version: v2.1.0
Subcategories:
Spectroscopy Data Red.
Spectroscopy Instr. Models
This toolset includes a difference image analysis pipeline, which employs a delta-function kernel, useful for reducing TESS Full Frame Images. The data extracted using the pipeline for the first two years of TESS imagery is available for inspection at
https://filtergraph.com/tess_ffi.
Code Language(s): IDL, Python3
Last updated: Mar. 21, 2024
Version: v0.2
Subcategories:
Photometry Data Red.
Lightcurve Visualization
VCAL-SPHERE, for VIP-based Calibration of VLT/SPHERE data, is a versatile pipeline for high-contrast imaging of exoplanets and circumstellar disks. The pipeline covers all steps of data reduction, including raw calibration, pre-processing and post-processing (i.e., modeling and subtraction of the stellar halo), for the IFS, IRDIS-DBI and IRDIS-CI modes (and combinations thereof) of the VLT instrument SPHERE. The three main steps of the reduction correspond to different modules, where the first follows the recommended EsoRex (ascl:1504.003) workflow and associated recipes with occasional inclusion of VIP (ascl:1603.003) routines.
Code Language(s): Python3
Last updated: Jan. 16, 2024
Subcategories:
Direct Imaging Data Red.
pycrires runs the CRIRES+ recipes of EsoRex. The pipeline organizes the raw data, creates SOF and configuration files, runs the calibration and science recipes, and creates plots of the images and extracted spectra. Additionally, it corrects remaining inaccuracies in the wavelength solution and the spectrum curvature. pycrires also provides dedicated routines for the extraction, calibration, and detection of spatially-resolved objects such as directly imaged planets.
Code Language(s): Python3
Last updated: Dec. 27, 2023
Version: v0.4.0
Subcategories:
Spectroscopy Data Red.
Direct Imaging Data Red.
The Data & Analysis Center for Exoplanets (DACE) is a PlanetS web-platform located at the University of Geneva (CH) dedicated to extrasolar planets data visualization, exchange and analysis. DACE provides the research and education community with an enhanced access to exoplanet data with a suite of statistical tools for data analysis. Published observational data such as high resolution spectra, radial velocities, photometric light curves and high contrast imaging measurements are available online. Planetary systems formation and evolution can be studied as well as their long term dynamical evolution.
Code Language(s): N/A
Last updated: Nov. 9, 2023
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Planet Population Visualization
Orbit Evolution (N-body)
Lightcurve Fitting
Orbit Fitting
RV Fitting
RV Instr. Models
Population Simulations and Catalogs
pycdata is a module to import datasets from various telescopes/instruments in
pycheops. pycheops is a tool specifically designed to model CHEOPS observations of transits, eclipses and phase curves. While being a genius tool, what it lacks is a facility to model datasets from other telescopes/instruments, even the PSF photometry produced by
PIPE. pycdata can be used to import datasets from PIPE, TESS and Kepler/K2 in pycheops thus enabling a joint lightcurve analysis of PIPE, TESS, Kepler/K2 data along with CHEOPS data in pycheops.
Code Language(s): Python3
Last updated: Oct. 24, 2023
Version: 1.3.0
Subcategories:
Photometry Data Red.
Lightcurve Fitting
The smart is a Markov Chain Monte Carlo (MCMC) forward-modeling framework for spectroscopic data, currently working for high-resolution spectrometers including Keck/NIRSPEC, SDSS/APOGEE, Gemini/IGRINS, Lick/HPF, Keck/HIRES and medium-resolution spectrometers including Keck/OSIRIS and Keck/NIRES.
For NIRSPEC users, required adjustments need to be made before reducing private data using NIRSPEC-Data-Reduction-Pipeline(NSDRP), to perform telluric wavelength calibrations, and to forward model spectral data. The code is currently being developed.
Code Language(s): Python3
Last updated: Sep. 29, 2023
Version: 1.0
Subcategories:
Spectroscopy Data Red.
RV Fitting
Stellar Parameter Fitting
Applefy calculates detection limits for exoplanet high contrast imaging (HCI) datasets. The package provides a number of features and functionalities to improve the accuracy and robustness of contrast curve calculations. Applefy implements the classical approach based on the t-test as well as the parametric boostrap test for non-Gaussian residual noise. Written in Python, it computes contrast curves and contrast grids.
Code Language(s): Python
Last updated: May. 26, 2023
Version: v0.1.2
Subcategories:
Direct Imaging Data Red.
WATSON (Visual Vetting and Analysis of Transits from Space ObservatioNs is a lightweight software package that enables a comfortable visual vetting of a transiting signal candidate from Kepler, K2 and TESS missions. WATSON looks for transit-like signals that could be generated by other sources or instrument artifacts. The code runs simplified tests on scenarios including:
-
Transit shape model fit
-
Odd-even transits checks
-
Centroids shifts
-
Optical ghost effects
-
Transit source offsets
and more...
With these data, we compute metrics to alert scientists about problematic signals.
Code Language(s): Python3
Last updated: Feb. 17, 2023
Version: 0.2.13
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Lightcurve Fitting
Collections:
K2
Kepler
TESS
PyMieScatt is a comprehensive forward and inverse Mie theory solver for Python 3. This package calculates relevant parameters such as absorption, scattering, extinction, asymmetry, backscatter, and more. It also contains single-line functions to calculate optical coefficients (in Mm-1) of ensembles of particles in lognormal (with single or multiple modes) or custom size distributions.
The inverse calculations retrieve the complex refractive index from laboratory measurements of scattering and absorption (or backscatter), useful for studying atmospheric organic aerosol of unknown composition.
Read more in
our JQSRT paper!
Code Language(s): Python3
Last updated: Feb. 7, 2023
Version: 1.8
Subcategories:
Atm Retrieval Codes
Spectroscopy Data Red.
Atm Retrieval Codes
Spectroscopy Instr. Models
Here we present PACMAN, an end-to-end pipeline developed to reduce and analyze HST/WFC3 data. The pipeline includes both spectral extraction and light curve fitting. The foundation of PACMAN has been already used in numerous publications (e.g., Kreidberg et al., 2014; Kreidberg et al., 2018) and these papers have already accumulated hundreds of citations.
Code Language(s): Python3
Last updated: Dec. 27, 2022
Version: v0.4.0
Subcategories:
Spectroscopy Data Red.
Photometry Data Red.
Lightcurve Fitting
Collections:
HST
HST - WFC3
The spaceKLIP pipeline enables to reduce & analyze JWST NIRCam & MIRI coronagraphy data. It provides functions to run the official jwst stage 1 and 2 data reduction pipelines with several modifications that were made to improve the quality of high-contrast imaging reductions. It then performs PSF subtraction based on the KLIP algorithm as implemented in the widely used pyKLIP package, outputs contrast curves, and enables forward model PSF fitting for any detected companions in order to extract their properties (offset and flux). The pipeline is still under heavy development.
Code Language(s): Python3
Last updated: Dec. 7, 2022
Subcategories:
Direct Imaging Data Red.
Collections:
JWST
JWST - Direct Imaging Data Reduction
Molecfit is a tool to correct for telluric absorption lines based on synthetic modelling of the Earth’s atmospheric transmission. It can be used with data obtained with various ground-based telescopes and instruments. It combines a publicly available radiative transfer code, a molecular line database, atmospheric profiles, and various kernels to model the instrument LSF. The atmospheric profiles are created by merging a standard atmospheric profile representative of a given observatory’s climate, of local meteorological data, and of dynamically retrieved altitude profiles for temperature, pressure, and humidity.
Code Language(s): C, ESO Common Pipeline Library (CPL), Python
Last updated: Nov. 18, 2022
Subcategories:
Spectroscopy Data Red.
Explicitly including Keplerian dynamics in the transit search allows Optimal BLS to enhance transit detectability while allowing such searches to be done with much-reduced resources and time. By using the (standard) BLS, one is either fairly insensitive to long-period planets or less sensitive to short-period planets and computationally slower by a significant factor of ~330 (for a 3 yr long dataset). Physical system parameters, such as the host star's size and mass, directly affect transit search. This understanding can then be used to optimize the search for every star individually. The code is well-used by the community.
Code Language(s): Matlab, Octave
Last updated: Nov. 14, 2022
Version: 1.0
Subcategories:
Photometry Data Red.
Lightcurve Fitting
The Polygon + Segments model allows modeling the light curve of an exoplanet with rings. This high-precision model includes full ring geometry as well as possible ring transparency and the host star’s limb darkening. Additionally, it can model oblate ringless planets as an opaque “ring” (same shape as a planet). pyPplusS is also computationally efficient, requiring just a 1D integration over a small range, making it faster than existing techniques. The algorithm at its core is further generalized to compute the light curve of any set of convex primitive shapes in transit (e.g. multiple planets, oblate planets, moons, rings, combination thereof, etc.) while accounting for their overlaps.
Code Language(s): Python3
Last updated: Nov. 14, 2022
Version: v0.1.5.3
Subcategories:
Photometry Data Red.
Lightcurve Fitting
ATOCA is used to extract and decontaminate spectroscopic images with multiple sources or diffraction orders. The inputs are, for all orders and sources: the wavelength solutions, the trace profiles, the throughputs and the spectral resolution kernels. From this, ATOCA can model simultaneously the detector and extract the spectra. See
Darveau-Bernier et al. (2022) for more details.
Code Language(s): Python3
Last updated: Oct. 14, 2022
Subcategories:
Spectroscopy Data Red.
Spectroscopy Instr. Models
Tool for creating a Systematics-insensitive Periodogram (SIP) to detect long period rotation in NASA's TESS mission data. Read more in our published Research Note of the
American Astronomical Society. SIP is a method of detrending telescope systematics (the TESS scattered light) simultaneously with calculating a Lomb-Scargle periodogram. This allows us to estimate of the rotation rate of variables with a period of >30days when there are multiple sectors. You can read a more in-depth work of how SIP is used in NASA's Kepler/K2 data
here
Code Language(s):
Last updated: Sep. 26, 2022
Version: 1.1.0
Subcategories:
Data Reduction Tools
Lightcurve Fitting
Observatory/Instrument Models
IGRINS RV is a python open source pipeline for extracting radial velocities (RVs) from spectra taken with the Immersion GRating INfrared Spectrometer (IGRINS). It uses a modified forward modeling technique that leverages telluric absorption lines as a common-path wavelength calibrator. IGRINS RV achieves an RV precision in the H and K bands of around 25-30 m/s for narrow-line stars, and it has successfully recovered the planet-induced RV signals of both HD 189733 and τ Boo A. Visit Stahl et al. 2021 to see the published paper.
Code Language(s):
Last updated: Sep. 26, 2022
Version: v1.5.1
Subcategories:
Data Reduction Tools
RV Fitting
RV Instr. Models
Built for astronomy, Prose is instrument-agnostic and allows the construction of data reduction pipelines using a wide range of building blocks, pre-implemented or user-defined. Using its modular architecture, it features basic reduction pipelines to deal with common tasks such as automatic reduction and photometric extraction.
Code Language(s): Python3, LaTeX
Last updated: Sep. 21, 2022
Version: 3.3.4
Subcategories:
Photometry Data Red.
dips is an algorithm for detrending timeseries of strictly periodic signals. It does not assume any functional form for the signal or the background or the noise; it disentangles the strictly periodic component from everything else. We use it in astronomy for detrending Kepler, K2 and TESS timeseries of periodic variable stars, eclipsing binary stars, exoplanets etc. The algorithm is described in detail in Prša, Zhang and Wells (2019), PASP 131, 8001. A new, generalized version of dips will be explained in Horvat and Prša (2022), currently in preparation.
Code Language(s): Python3
Last updated: Feb. 8, 2022
Version: 0.2.0
Subcategories:
Photometry Data Red.
Serval measures and analyses precise radial velocities in stellar spectra using least square fitting.
Code Language(s): Python2, Python3, C, Fortran
Last updated: Feb. 4, 2022
Subcategories:
Spectroscopy Data Red.
RV Fitting
Here we present an open-source Python-based Bayesian orbit retrieval code (Nii) that implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) strategy. Nii provides a module to simulate the observations of a space-based astrometry mission in the search for exoplanets, a signal extraction process for differential astrometric measurements using multiple reference stars, and an orbital parameter retrieval framework using APT-MCMC. We further verify the orbit retrieval ability of the code through two examples corresponding to a single-planet system and a dual-planet system. In both cases, efficient convergence on the posterior probability distribution can be achieved.
Code Language(s): Python3
Last updated: Dec. 7, 2021
Version: 0.1
Subcategories:
Data Reduction Tools
Orbit Fitting
Astrometry Instr. Models
We introduce zeus, a well-tested Python implementation of the Ensemble Slice Sampling (ESS) method for Bayesian parameter inference. ESS is a novel Markov chain Monte Carlo (MCMC) algorithm specifically designed to tackle the computational challenges posed by modern astronomical and cosmological analyses. In particular, the method requires only minimal hand--tuning of 1-2 hyper-parameters that are often trivial to set; its performance is insensitive to linear correlations and it can scale up to 1000s of CPUs without any extra effort. Furthermore, its locally adaptive nature allows to sample efficiently even when strong non-linear correlations are present.
Code Language(s): Python3
Last updated: Nov. 9, 2021
Version: 2.5.4
Subcategories:
Data Reduction Tools
Model-Fitting Tools
TRAN_K2 is standalone Fortran code to search for planetary transits under the colored noise of stellar variability and instrumental effects. Stellar variability is represented by a Fourier series and, when necessary, by an autoregressive model aimed at avoiding excessive Gibbs overshoots at the edges. For the treatment of systematics, a co-trending and an external parameter decorrelation are employed. The filtering is done within the framework of the standard weighted least squares, where the weights are determined iteratively, to allow a robust fit and to separate the transit signal from stellar variability and systematics.
Code Language(s): Fortran, Shell
Last updated: Oct. 26, 2021
Version: V0
Subcategories:
Photometry Data Red.
Lightcurve Fitting
TRIPPy is a python package aimed to perform all the steps required to measure accurate photometry of both trailed and non-trailed (stationary) astronomical sources. This includes the ability to generate stellar and trailed point source functions, and to use circular and pill shaped apertures to measure photometry and estimate appropriate aperture corrections. Tools for source fitting with a model PSF (both MCMC and classical least-squares minimizers) are available.
Citation: If you use TRIPPy in your science works, please cite
Fraser, W. et al., 2016, Astronomical Journal, 151. DOI at
Zenodo.
Code Language(s): Python2, Python3
Last updated: Oct. 19, 2021
Version: 0.4
Subcategories:
Data Reduction Tools
This Fortran computer program models orbital motion in the solar system, including almost 100 individual asteroids as well as all of the planets and some moons, along with a detailed model of our moon, and a model of pulsar motions and of distant radio sources. It takes as input diverse astrometric data: radio, radar, laser, timing of signal arrivals, and VLBI. The program can solve for well over 100 parameters, including orbital and (for some bodies) rotational initial conditions, sky coordinates for radio sources, plasma densities, the second harmonic of the Sun's gravitational field, and those related to tests of fundamental physics.
Code Language(s): Fortran
Last updated: Oct. 19, 2021
Version: 790
Subcategories:
Atmosphere Models
Photometry Data Red.
Data Visualization Tools
Orbit Evolution (N-body)
Interior & Surface Processes
Model-Fitting Tools
Direct Imaging Instr. Models
Astrometry Instr. Models
Photometry Instr. Models
Deep-Transit is an open-source Python package designed for transit detection with a deep learning based 2D object detection algorithm. For simple usage, Deep-Transit can handle your light curve and then output the transiting candidates' bounding boxes and confidence scores. Deep-Transit has already been trained for Kepler and TESS data, but can be easily extended to other photometric surveys, even ground-based observations. Deep-Transit also provides the interface to train on your own datasets.
Code Language(s): Python3
Last updated: Sep. 22, 2021
Version: 0.1.0
Subcategories:
Photometry Data Red.
Lightcurve Fitting
An IDL routine for fitting multiple Keplerian curves (i.e. those that neglect planet-planet interactions) to radial velocity data. Handles heteroschedastic data, and constraints on P, e, phase, and transit timing. It is fast because it solves, via maximum likelihood, for all parameters other than P, e, and phase with a linear least-squares matrix inversion. It then determines the remaining 3*n parameters (where n is the number of planets) via a Levenberg-Marquardt optimization. The method is described in Wright & Howard ApJS 182, 205. Uncertainties in the fitted parameters can be determined via bootstrapping using BOOTTRAN (Wang et al. ApJ 761, 46).
Code Language(s): IDL
Last updated: Apr. 27, 2021
Version: 2.1
Subcategories:
Photometry Data Red.
Formation and Dynamics Tools
Orbit Fitting
RV Fitting
The Gemini Planet Imager Data Pipeline allows transformation of raw data from GPI into calibrated spectral and polarimetric data cubes. It also provides some basic capabilities for PSF suppression through differential imaging, and for astrometry and spectrophotometry of detected sources. See complete documentation
here.
Code Language(s): IDL
Last updated: Apr. 13, 2021
Version: v1.5.0
Subcategories:
Direct Imaging Data Red.
This program was originally designed to identify false positive transit signals in K2 photometry, but has been modified to play nicely with the Transit Least Squares software package. It contains several thresholds which mimic visual inspection and help automate the transit detection process.
Code Language(s): Python3
Last updated: Mar. 31, 2021
Version: 0.1.3
Subcategories:
Photometry Data Red.
Lightcurve Fitting
Transit Survey Predictions
The MCMCI tool offers the opportunity to perform an integrated analysis of an exoplanetary system without splitting it into the preliminary stellar characterisation through theoretical models.The MCMCI combines the Markov chain Monte Carlo approach of analysing photometric or radial velocity time series with a proper interpolation within stellar evolutionary isochrones and tracks, to be performed at each chain step, to retrieve stellar theoretical parameters such as age, mass, and radius. This approach favours a close interaction between lightcurve analysis and isochrones, so that the parameters recovered at each step of the MCMC enter as inputs for purposes of the isochrone placement.
Code Language(s): Fortran
Last updated: Mar. 31, 2021
Subcategories:
Photometry Data Red.
Lightcurve Fitting
RV Fitting
Atm Retrieval Codes
Stellar Parameter Fitting
Stellar Models and Catalogs
MAYO is a pipeline for exoplanet and disk high-contrast imaging from ADI datasets. For more information, please refer to Pairet, Benoît, Faustine Cantalloube, and Laurent Jacques. "MAYONNAISE: a morphological components analysis pipeline for circumstellar disks and exoplanets imaging in the near infrared.", Monthly Notices of the Royal Astronomical Society, 2021.
Code Language(s): Python3
Last updated: Mar. 29, 2021
Version: 0.1
Subcategories:
Direct Imaging Data Red.
The VARTOOLS program is a command line utility that provides tools for processing and analyzing astronomical time series data, especially light curves. It includes methods for calculating variability/periodicity statistics of light curves; for filtering, transforming, and otherwise modifying light curves; and for modeling light curves. It is intended primarily for batch processing a large number of light curves. The program is run by issuing a sequence of commands to perform actions on light curves, each command is executed in turn with the resulting light curves passed to the next command. Statistics computed by each command are sent to stdout as an ascii table.
Code Language(s): C, Shell
Last updated: Mar. 29, 2021
Subcategories:
Photometry Data Red.
Lightcurve Fitting
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).
Code Language(s): Python3
Last updated: Dec. 21, 2020
Version: v1.0.19
Subcategories:
Photometry Data Red.
Lightcurve Fitting
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.
Code Language(s): Python3
Last updated: Dec. 21, 2020
Version: 0.1.13
Subcategories:
Spectroscopy Data Red.
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.
Code Language(s): Python3
Last updated: Dec. 18, 2020
Version: v1.10
Subcategories:
Photometry Data Red.
Lightcurve Visualization
Lightcurve Fitting
Photometry Instr. Models
Juliet is a versatile modelling tool for transiting and non-transiting exoplanetary systems that allows to perform quick-and-easy fits to data coming from transit photometry, radial velocity or both using bayesian inference and, in particular, using Nested Sampling in order to allow both efficient fitting and proper model comparison. This pip-installable python library (pip install juliet) also allows to model these time-series using either simple linear models and/or more involved correlated noise on both photometry and radial-velocities through Gaussian Processes. Full documentation is available
here
Code Language(s): Python3
Last updated: Dec. 18, 2020
Version: v.2.2.7
Subcategories:
Photometry Data Red.
Lightcurve Fitting
RV Fitting
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.
Code Language(s): Python3
Last updated: Nov. 25, 2020
Subcategories:
Photometry Data Red.
Lightcurve Visualization
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 .
Code Language(s): Python3
Last updated: Nov. 20, 2020
Version: v1.2.1
Subcategories:
Photometry Data Red.
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).
Code Language(s): Python3
Last updated: Sep. 10, 2020
Version: v0.4.4
Subcategories:
Photometry Data Red.
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.
Code Language(s): Python3
Last updated: Jul. 6, 2020
Version: v0.11.0
Subcategories:
Direct Imaging Data Red.
Code Language(s): Python3
Last updated: Mar. 6, 2020
Version: v0.1.8
Subcategories:
Photometry Data Red.
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.
Code Language(s): Java8
Last updated: Mar. 6, 2020
Subcategories:
Photometry Data Red.
Lightcurve Fitting
RV Fitting
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.
Code Language(s): Python2
Last updated: Mar. 6, 2020
Version: 2.0.1
Subcategories:
Direct Imaging Data Red.
ASPIRED reduces 2D spectral data from raw image to wavelength and flux calibrated 1D spectrum automatically without any user input (quicklook quality), and provides a set of easily configurable routines to build pipelines for long slit spectrographs on different telescopes (science quality).
Published in "Automated SpectroPhotometric Image REDuction (ASPIRED)", 2020, Astronomical Data Analysis Software and Systems XXIX. ASP Conference Series, Vol. 527, proceedings of a conference held (6—10 October 2019) at the Martini Plaza, Groningen, the Netherlands.
Code Language(s): Python3
The Transiting Exoplanet Survey Satellite (TESS) produces Full Frame Images (FFIs) at a half hour cadence and keeps the same pointing for ~27 days at a time. Astrocut performs the same cutout across all FFIs that share a common pointing to create a time series of images on a small portion of the sky.
Published in "Astrocut: Tools for creating cutouts of TESS images", 2019, Astrophysics Source Code Library (ASCL).
JWST NIRCam Reduction PipelineThe reduction process includes corrections for known prelaunch issues such as 1/f noise, as well as in-flight issues including snowballs, wisps, and astrometric alignment.
Published in "CEERS Epoch 1 NIRCam Imaging: Reduction Methods and Simulations Enabling Early JWST Science Results", 2023, The Astrophysical Journal Letters, Volume 946, Issue 1, id.L12, 23 pp.
Code Language(s): Python3
The charis pipeline is capable of extracting spectral data cubes from both the Subaru/CHARIS as well as the SPHERE/IFS integral field spectrographs for high-contrast imaging.
Published in "Data reduction pipeline for the CHARIS integral-field spectrograph I: detector readout calibration and data cube extraction", 2017, Journal of Astronomical Telescopes, Instruments, and Systems, Volume 3, id. 048002 (2017).
Code Language(s): Python3
EVEREST (EPIC Variability Extraction and Removal for Exoplanet Science Targets) removes instrumental noise from light curves with pixel level decorrelation and Gaussian processes. The code, written in Python, generates the EVEREST catalog and offers tools for accessing and interacting with the de-trended light curves. EVEREST exploits correlations across the pixels on the CCD to remove systematics introduced by the spacecraft’s pointing error.
Published in "EVEREST: Pixel Level Decorrelation of K2 Light Curves", 2016, ApJ, and "An Update to the EVEREST K2 Pipeline: Short Cadence, Saturated Stars, and Kepler-like Photometry Down to Kp = 15", 2018, ApJ
ExoTOM is a target-observation-manager automating exoplanet transit follow-up.
Published in "ExoTOM: a target-observation-manager automating exoplanet transit follow-up", 2022, Proceedings of the SPIE, Volume 12186, id. 121861O 18 pp. (2022).
Code Language(s): Python3
f3 is a package for extracting photometry from Kepler’s Full-Frame Images, a set of calibration data obtained approximately monthly during the primary Kepler mission.
Published in "Long-term Photometric Variability in Kepler Full-frame Images: Magnetic Cycles of Sun-like Stars", 2017, The Astrophysical Journal, Volume 851, Issue 2, article id. 116, 15 pp. (2017).
k2photometry reads, reduces and detrends K2 photometry and searches for transiting planets. MAST database pixel files are used as input; the output includes raw lightcurves, detrended lightcurves and a transit search can be performed as well.
Published in "k2photometry: Read, reduce and detrend K2 photometry", 2016, Astrophysics Source Code Library, record ascl:1602.014.
Used in "The K2-ESPRINT Project. II. Spectroscopic Follow-up of Three Exoplanet Systems from Campaign 1 of K2", 2016, The Astrophysical Journal, Volume 820, Issue 1, article id. 56, 8 pp.
Kadenza enables time-critical data analyses to be carried out using NASA's Kepler Space Telescope. It enables users to convert Kepler's raw data files into user-friendly Target Pixel Files upon downlink from the spacecraft. The primary motivation for this tool is to enable the microlensing, supernova, and exoplanet communities to create quicklook lightcurves for transient events which require rapid follow-up.
Code Language(s): Python3
A JWST NIRISS spectral extraction code.
Published in "Early Release Science of the exoplanet WASP-39b with JWST NIRISS", 2023, Nature, Volume 614, Issue 7949, p.670-675.
Code Language(s): Python3
The Notch and LOCoR pipelines for detrending TESS and K2 lightcurves and identifying planetary signals.
Published in "Zodiacal Exoplanets in Time (ZEIT). V. A Uniform Search for Transiting Planets in Young Clusters Observed by K2", 2017, The Astronomical Journal, Volume 154, Issue 6, id.224.
Code Language(s): Python3
PACO ASDI produces detection maps with improved sensibility compared to existing methods.
Published in "PACO ASDI: an algorithm for exoplanet detection and characterization in direct imaging with integral field spectrographs", 2020, Astronomy & Astrophysics, Volume 637, id.A9, 29 pp.
PIPE is a photometric extraction package for CHEOPS that is complementing the official Data Reduction Pipeline (DRP).
Published in "CHEOPS geometric albedo of the hot Jupiter HD 209458 b", 2022, Astronomy & Astrophysics, Volume 659, id.L4, 8 pp.
Code Language(s): Python3
IDL based software for Planetary image processing and navigation developed at the Grupo de Ciencias Planetarias (GCP) in the University of the Basque country UPV/EHU.
Published in "The Planetary Laboratory for Image Analysis (PLIA)", 2010, Advances in Space Research, Volume 46, Issue 9, p. 1120-1138.
A python pipeline to reduce astronomical IR imaging data, written with SPHERE data in mind.
Published in "precision: a fast python pipeline for high-contrast imaging - application to SPHERE observations of the red supergiant VX Sagitariae", 2020, Monthly Notices of the Royal Astronomical Society, Volume 494, Issue 3, pp.3200-3211.
pterodactyls builds on publicly available and tested tools in order to extract, de-trend, search, and vet
transiting young planet candidates.
Published in "pterodactyls: A Tool to Uniformly Search and Vet for Young Transiting Planets in TESS Primary Mission Photometry", 2022, The Astronomical Journal, Volume 164, Issue 3, id.78, 22 pp.
Code Language(s): Python3
SPORK is a spectrum normalization routine adapted from the stellar abundance determination software Spectroscopy Made Hard(er).
Published in "SPORK That Spectrum: Increasing Detection Significances from High-resolution Exoplanet Spectroscopy with Novel Smoothing Algorithms", 2022, The Astronomical Journal, Volume 164, Issue 2, id.35, 8 pp.
Code Language(s): Python3
Extreme Value Theory for comparing periodograms: Optimizing future transiting exoplanet surveys. TCF calculates a periodogram designed to detect exoplanet transits after the light curve has been differenced.
Published in "Autoregressive Planet Search: Methodology", 2019, The Astronomical Journal, Volume 158, Issue 2, article id. 57, 21 pp.
Published in "Identification and Removal of Noise Modes in Kepler Photometry", 2012, Publications of the Astronomical Society of the Pacific, Volume 124, Issue 920, pp. 1073 (2012).
TESSreduce builds on lightkurve to reduce TESS data while preserving transient signals.
Published in "TESSreduce: Transient focused reduction for TESS data", 2021, Astrophysics Source Code Library (ASCL).
Used in "Progenitor and close-in circumstellar medium of type II supernova 2020fqv from high-cadence photometry and ultra-rapid UV spectroscopy", 2022, Monthly Notices of the Royal Astronomical Society, Volume 512, Issue 2, pp.2777-2797.
Code Language(s): Python3
An implementation of the Causal Pixel Model (CPM) de-trending method to obtain TESS Full-Frame Image (FFI) light curves.
Published in "The unpopular Package: A Data-driven Approach to Detrending TESS Full-frame Image Light Curves", 2022, The Astronomical Journal, Volume 163, Issue 6, id.284, 19 pp.
Code Language(s): Python3
TIERRA is a 1D spEctRoscopy code that adopted the original Matlab by Julien de Wit (de Wit et. al 2016, 2018) and expanded it in python. Currently only 7 molecules are included in the code: methane, carbon-monoxide, carbon-dioxide, water, hydrogen, nitrogen and ozone as part of the study Niraula & de Wit et. al 2022).
Code Language(s): Python3
transitspectroscopy is a package containing algorithms and wrappers useful for performing transit (transmission and emission) spectroscopy of exoplanetary systems.
Published in "TransitSpectroscopy", 2022, Zenodo.