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!
  • Subscribe to our monthly RSS messages on new updates and tools
  • Check out the Twitter account @ExoplanetModels (not an official NASA account), where new tools and features are highlighted
Help us improve EMAC!
  • Email us with general feedback at and tell us what you’d change or improve.
  • Click the icon in a resource box to provide suggestions for an individual tool or tools.
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.

The P.I. is Avi Mandell, and the Deputy P.I. is Eric Lopez; more information on EMAC staffing and organization can be found on Our Team page.

MOLPOP-CEP: An exact, fast line transfer code for multi-level line emission

Asensio Ramos, Andrés ; Elitzur, Moshe

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https://emac.gsfc.nasa.gov?cid=2405-006
2405-006

MOLPOP-CEP is a universal line transfer code that allows the exact calculation of multi-level line emission from a slab with variable physical conditions for any arbitrary atom or molecule for which atomic data exist.

About

sunbather

Linssen, Dion et al.

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https://emac.gsfc.nasa.gov?cid=2405-005
2405-005

sunbather performs simulations of escaping planet atmospheres and their transit signatures. The main use of the code is to construct 1D Parker wind profiles using the Python p-winds package, to simulate these with photoionization code Cloudy, and to postprocess the output with a custom radiative transfer module to predict the transmission spectra of exoplanets, for a nearly arbitrary chemical composition.

About

polyrot: A small package for computing polytropic models of rapidly rotating planets and stars.

Dewberry, Janosz W.

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https://emac.gsfc.nasa.gov?cid=2405-004
2405-004

This package computes the equilibrium structure of rapidly rotating planets and stars modeled as "polytropes."

About

The Sonora Elf Owl Models: Substellar Atmosphere Models

Mukherjee, Sagnick et al.

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https://emac.gsfc.nasa.gov?cid=2405-003
2405-003

The Sonora Elf Owl Models is a successor to the Sonora Bobcat and Sonora Cholla models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model PICASO. The model grid samples equilibrium temperatures between 275-2400 K and log(g) between 3.25-5.5. The mixing parameter log(Kzz) has been varied from 2-9 in cgs units. The [M/H] and C/O has been varied between [M/H]=-1.0 to [M/H]=+1.0 and C/O=0.22 to C/O=1.14.

About

SpectralRadex

Holdship, J. ; Vermarien, G. ; Van der Tak, F. F. S. ; Black, J. H.

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https://emac.gsfc.nasa.gov?cid=2405-002
2405-002

A python library that serves two purposes: run RADEX directly from python and create model spectra from RADEX outputs. A number of libraries exist for the first purpose. However, most either launch the RADEX compiled binary as a subprocess or wrap the original code. In the former case, the creating of subprocesses can interfere with many Python multiprocessing methods. In the latter, running multiple models simultanously can be problematic due to the use of F77 common blocks in RADEX. SpectralRadex uses F2PY to compile a version of RADEX written in modern Fortran, most importantly dropping the use of common blocks. As a result, RADEX models can be run in parallel.

About

The Giants Pipeline: An open-source Python package to search for exoplanets around evolved stars

Saunders, Nicholas et al.

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https://emac.gsfc.nasa.gov?cid=2405-001
2405-001

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.

About

TLCM: Transit and Light Curve Modeler

Csizmadia, Szilárd

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https://emac.gsfc.nasa.gov?cid=2404-006
2404-006

TLCM is a software package to analyze the light curves of transiting exoplanets. The code fits the light curves with quadratic limb darkening law, and the limb darkening coefficients can be different for the two objects considered.

About Demo

OoT: Out-of-Transit Light Curve Generator

Penoyre, Z. ; Sandford, E.

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https://emac.gsfc.nasa.gov?cid=2404-005
2404-005

OoT (Out-of-Transit) calculates the light curves and radial velocity signals due to a planet orbiting a star. It explicitly models the effects of tides, orbital motion, relativistic beaming, and reflection of the stars light by the planet. The code can also be used to model secondary eclipses.

About

SPCA: Spitzer Phase Curve Analysis

Dang, L ; Bell, T. J.

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https://emac.gsfc.nasa.gov?cid=2404-004
2404-004

SPCA is an open-source, modular, and automated pipeline for Spitzer Phase Curve Analyses.

About

nuance

Garcia, L.

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https://emac.gsfc.nasa.gov?cid=2404-003
2404-003

nuance uses linear models and gaussian processes (using JAX-based tinygp) to simultaneously search for planetary transits while modeling correlated noises (e.g. stellar variability) in a tractable way. nuance is written for python 3 and can be installed using pip.

About

The NASA Exoplanet Archive: Data and Tools for Exoplanet Research

NASA Exoplanet Science Institute

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https://emac.gsfc.nasa.gov?cid=2404-002
2404-002

The NASA Exoplanet Archive is an online astronomical exoplanet and stellar catalog and data service that collates and cross-correlates astronomical data and information on exoplanets and their host stars, and provides tools to work with these data. The archive is dedicated to collecting and serving important public data sets involved in the search for and characterization of extrasolar planets and their host stars. These data include stellar parameters (such as positions, magnitudes, and temperatures), exoplanet parameters (such as masses and orbital parameters) and discovery/characterization data (such as published radial velocity curves, photometric light curves, images, and spectra).

About Demo

Encyclopaedia of Exoplanetary Systems

The Exoplanet Team

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https://emac.gsfc.nasa.gov?cid=2404-001
2404-001

This catalog is a working tool providing all the latest detections and data announced by professional astronomers, useful to facilitate progress in exoplanetology. It contains data about objects lighter than 60 Jupiter masses, which are orbiting stars/brown dwarf or are free floating. It also provides databases of planets in binary systems and circumstellar disks.

Demo

exovetter: Transiting exoplanet detection python vetter

The exovetter development team

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https://emac.gsfc.nasa.gov?cid=2403-025
2403-025

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.

About

TIKE: The Time Series Integrated Knowledge Engine

The MAST Team at STScI

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https://emac.gsfc.nasa.gov?cid=2403-024
2403-024

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.

gollum: An intuitive programmatic and visual interface for precomputed synthetic spectral model grids

Shankar, S.; Gully-Santiago, M.; Morley, C.; Cao, J.; Kaplan, K.; Kimani-Stewart, K.; Gonzalez-Argueta, D.

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https://emac.gsfc.nasa.gov?cid=2403-023
2403-023

Gollum is a tool for spectral visualization and analysis. It boasts both a programmatic interface and a visual interface that help users analyze stellar and substellar spectra, with support included for a set of precomputed synthetic spectral model grids.

About

ATMOSPHERIX: Data Processing Tool

Klein, B. et al.

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https://emac.gsfc.nasa.gov?cid=2403-022
2403-022

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.

About

CONTROL: CUTE Autonomous Data Reduction Pipeline

Sreejith, A. G. et al.

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https://emac.gsfc.nasa.gov?cid=2403-021
2403-021

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.

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PyRADS: Python RADiation model for planetary atmosphereS

Koll, D. et al.

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https://emac.gsfc.nasa.gov?cid=2403-020
2403-020

The Python line-by-line RADiation model for planetary atmosphereS (PyRADS) is a 1D line-by-line radiation code. The default version is for longwave radiation (no scattering), a version for shortwave radiation (with scattering) is also available on github. Citation: Koll & Cronin (2018), Proceedings of the National Academy of Sciences, vol. 115, issue 41, pp.10293-10298.

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MARDIGRAS: MAss-Radius DIaGRAm with Sliders

Aguichine, A. et al.

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https://emac.gsfc.nasa.gov?cid=2403-019
2403-019

The MAss-Radius DIaGRAm with Sliders (MARDIGRAS) is a visualization tool that allows a simple and easy manipulation of mass-radius relationships (also known as iso-composition curves) with interactive sliders. Each slider controls one of the key parameters of the models implemented in the figure (core mass fraction, envelope mass fraction, equilibrium temperature, etc.). To run the program, download the repository and run with python (no installation needed): git clone https://github.com/an0wen/MARDIGRAS cd MARDIGRAS python mardigras.py

About

TATOO: Tidal-chronology Age TOOl

Gallet, F.

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https://emac.gsfc.nasa.gov?cid=2403-018
2403-018

Tidal-chronology standalone tool to estimate the age of massive close-in planetary systems. This tool is specifically developed for massive close-in planetary systems: Mp > 0.5 Mjup and 0.5 < Mstar/Msun < 1.0. TATOO currently only works with python3.5.

About

pile-up: Monte Carlo simulations of star-disk torques on hot Jupiters

Heller, R.

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https://emac.gsfc.nasa.gov?cid=2403-017
2403-017

A gnuplot script for Monte Carlo simulations of disk and stellar tidal torques acting on hot Jupiters. Details are described in the research paper by René Heller (2018), "Formation of hot Jupiters through Disk Migration and Evolving Stellar Tides", Astronomy & Astrophysics. This gnuplot script was used to generate Figure 3b in this paper.

About

Atmospheric Athena: 3D Atmospheric escape model with ionizing radiative transfer

Tripathi, A. ; Krumholz, M. R.

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https://emac.gsfc.nasa.gov?cid=2403-016
2403-016

Atmospheric Athena is a code intended to simulate hydrodynamic escape from close-in giant planets in 3D. It uses the Athena hydrodynamics code (v4.1) with a new ionizing radiative transfer implementation based on Krumholz et al, 2007, to self-consistently model photoionization driven winds from the planet. The code is fully compatible with static mesh refinement and MPI parallelization.

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exoTEDRF: exoplanet Transit and Eclipse Data Reduction Framework

Radica, M.

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https://emac.gsfc.nasa.gov?cid=2403-015
2403-015

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).

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APPleSOSS: A Producer of ProfiLEs for SOSS. Application to the NIRISS SOSS Mode

Radica, M. et al.

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https://emac.gsfc.nasa.gov?cid=2403-014
2403-014

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.

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optool: Command-line driven tool to create dust opacities.

Dominik, C. ; Min, M. ; Tazaki, R.

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https://emac.gsfc.nasa.gov?cid=2403-013
2403-013

Optool computes dust opacities and scattering matrices, for specific grain sizes or averaged over size distributions. It is derived from OpacityTool (ascl:2104.009) and implements the Distribution of Hollow Spheres (DHS) statistical method to approximate irregular and low porosity grains. Mie theory is available as a limiting case of DHS. It also implements the Tazaki Modified Mean Field Theory (MMF) to treat fractal and highly porous aggregates. The refractive index data for many astronomically relevant materials are compiled into the code, and external refractive index data can be used as well.

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GPS: Genesis Population Synthesis

Chakrabarty, A.; Mulders, G. D.

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https://emac.gsfc.nasa.gov?cid=2403-012
2403-012

This is a Python-based population synthesis codebase that uses the Genesis database of planet formation models (Mulders et al. 2020). It consists of independent stages of internal structure and atmopsheric evolution models that can be used to synthesize a population of small exoplanets for comparison with observed domgraphics, e.g., from Kepler. It also offers statistical tools for drawing comparisons with observed distributions and studying occurrence trends. By invoking migration models (e.g., from Genesis), one can explore the occurrence patterns of the speculative water worlds and generate a list of potential targets using GPS.

CALCEPH: Planetary ephemeris files access code

Gastineau, M. et al. ; IMCCE ; Observatoire de Paris ; PSL University ; CNRS

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https://emac.gsfc.nasa.gov?cid=2403-011
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The library CALCEPH accesses binary planetary ephemeris files, including INPOPxx, JPL DExxx, and SPICE ephemeris files. This library, available for the operating system Linux, MacOS and WIndows, provides a C Application Programming Interface (API) and, optionally, Fortran 77/2003, Python 2/3 and octave/Matlab interfaces to be called by the application. These functions provide access to many ephemeris file at the same time for parallel computations.

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BOOTTRAN: Error Bars for Keplerian Orbital Parameters

Wang, S.X.; Wright, J.

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https://emac.gsfc.nasa.gov?cid=2403-010
2403-010

BOOTTRAN calculates error bars for Keplerian orbital parameters for both single- and multiple-planet systems. It takes the best-fit parameters and radial velocity data (BJD, velocity, errors) and calculates the error bars from sampling distribution estimated via bootstrapping. It is recommended to be used together with the RVLIN (ascl:1210.031) package, which find best-fit Keplerian orbital parameters.

Posidonius: N-Body simulator for planetary and/or binary systems

Blanco-Cuaresma, S. et al.

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https://emac.gsfc.nasa.gov?cid=2403-009
2403-009

Posidonius is a N-body code for simulating planetary and/or binary systems which implements the WHFAST/IAS15 integrators (Rein & Tamayo, 2015; Rein & Spiegel, 2015) and the tidal model used in Mercury-T (Bolmont et al. 2015). The bodies in the simulation can be static or follow predefined evolutionary models matching FGKML stars and gaseous planets. The simulations can account for several different effects such as tidal forces, rotational-flattening effects, general relativity corrections, protoplanetary disk, stellar wind. Posidonius has a better spin integration than Mercury-T, it's more than six times faster, it conserves the total angular momentum of the system one order of magnitude.

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Difference Imaging Code and Visualization for TESS Full Frame Image Lightcurves

Oelkers, R. J. & Stassun, K.G.

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https://emac.gsfc.nasa.gov?cid=2403-008
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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.

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TriArc: Bayesian Detection Threshold test for Atmospheric Species utilising petitRADTRANS

Claringbold, A. B.

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https://emac.gsfc.nasa.gov?cid=2403-007
2403-007

TriArc uses Bayesian statistics to determine the minimum abundance of an atmospheric species in a given model atmosphere (excluding the species of interest) and spectral noise profile. The current version is configured for transmission spectroscopy, but can be adjusted to emission spectroscopy on request. It is built using the forward modelling capabilities of petitRADTRANS. Utilised to calculated prebiosignature detection thresholds for various potential JWST targets in Claringbold et al. 2023.

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IsoFATE: Isotopic Fractionation via ATmospheric Escape

Cherubim, C. et al.

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https://emac.gsfc.nasa.gov?cid=2403-006
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Open source code for the numerical model IsoFATE: Isotopic Fractionation via ATmospheric Escape. IsoFATE models mass fractionation of planetary atmospheres due to molecular diffusion for H, He, and an arbitrary number of trace species (e.g. D, O). The model includes EUV-driven photoevaporation and core-powered mass loss.

luas: A 2D Gaussian process package for systematics correlated in two dimensions

Fortune, M. et al.

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luas (from the Irish word for speed) is a small library aimed at building Gaussian processes (GPs) primarily for two-dimensional data sets. This has particularly useful applications when it comes to joint-fitting spectroscopic transit light curves, as demonstrated in Fortune et al. (2024). By utilising different optimisations - such as using Kronecker product algebra - we can make the application of GPs to 2D data sets which may have dimensions of 100s-1000s along both dimensions possible within a reasonable timeframe. luas can be used with popular inference frameworks such as NumPyro and PyMC for which there are tutorials to help you get ‎started.

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HPIC: The Habitable Worlds Observatory Preliminary Input‎ Catalog

Tuchow, Noah; Stark, Chris; Mamajek, Eric

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https://emac.gsfc.nasa.gov?cid=2403-004
2403-004

The Habitable Worlds Observatory Preliminary Input‎ Catalog (HPIC) is a list of ~13,000 nearby bright stars that will be potential targets for the Habitable Worlds Observatory in its search for Earth-sized planets around Sun-like stars. It was constructed using the TESS and Gaia DR3 catalogs, and uses an automated pipeline to compile stellar measurements and derived astrophysical properties for all stars.

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coronagraph: Telescope Noise Modeling for Exoplanets in Python

Lustig-Yaeger et al.

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https://emac.gsfc.nasa.gov?cid=2403-003
2403-003

A Python noise model for directly imaging exoplanets with a coronagraph-equipped telescope. The original IDL code for this coronagraph model was developed and published by Tyler Robinson and collaborators (Robinson, Stapelfeldt & Marley 2016). This open-source Python version has been expanded upon in a few key ways, most notably, the Telescope, Planet, and Star objects used for reflected light coronagraph noise modeling can now be used for transmission and emission spectroscopy noise modeling, making this model a general purpose exoplanet noise model for many different types of observations.

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mini_chem: Miniature chemical kinetics model for gas giant GCMs

Lee, E. K.H.; Tsai, S.-M.

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https://emac.gsfc.nasa.gov?cid=2403-002
2403-002

Mini-chem is a kinetic chemistry network solver primarily for gas giant atmospheric modelling, pared down from the large chemical networks. This makes use of 'net forward reaction tables', which reduce the number of reactions and species required to be evolved in the ODE solvers significantly. Mini-chem's NCHO network currently consists of only 12 species with 10 reactions, making it a lightweight and easy to couple network to large scale 3D GCM models, or other models of interest (such as 1D or 2D kinetic modelling efforts).

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cortecs: Compressed representations of opacity for radiative transfer

Savel, A.; Bedell, M.; Kempton, E. M.-R.

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https://emac.gsfc.nasa.gov?cid=2403-001
2403-001

cortecs is a Python package for compressing opacity files used in radiative transfer. We offer a few different types of compression methods with a range of flexibility, from polynomial to neural networks. We also provide utility functions for working with opacity files, such as chunking and interpolating them onto different grids.

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TRES-exo: TRiple Evolution Simulation package

Columba, G.; Toonen, S.; Dorozsmai, A.; Danielski, C.

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https://emac.gsfc.nasa.gov?cid=2402-001
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TRES is a numerical framework for simulating hierarchical triple systems of stars and giant planets (M>0.2 M_Jupiter). It accounts for three-body dynamics, stellar evolution and various interactions. TRES-exo is an extension of the original code (Toonen et al. 2016) specifically designed to simulate giant circumbinary planets and their evolution.

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Spright: Bayesian mass-radius relation for small planets

Parviainen, H.; Luque, R.; Palle, E.

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https://emac.gsfc.nasa.gov?cid=2401-006
2401-006

Spright is a fast Bayesian radius-density-mass relation for small planets. The package allows one to predict planetary masses, densities, and RV semi-amplitudes given the planet's radius or planetary radii given the planet's mass. The package offers an easy-to-use command line script for people not overly interested in coding and a nearly-as-easy-to-use set of Python classes for those who prefer to code. The command line script can directly create publication-quality plots, and the classes offer a full access to the predicted numerical distributions.

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VCAL-SPHERE: Hybrid pipeline for reduction of VLT/SPHERE data

Christiaens, Valentin et al.

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https://emac.gsfc.nasa.gov?cid=2401-005
2401-005

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.

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deconfuser: An algorithm for fast orbit-fitting of directly imaged planets

Pogorelyuk, L. et al.

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https://emac.gsfc.nasa.gov?cid=2401-004
2401-004

Fast orbit fitting of directly imaged multi-planetary systems. The deconfuser quickly fits orbits to planet detections in 2D images, guarantees that all orbits within a certain tolerance are found, and ranks partitions of detections by planets (decides which assignment of detection-to-planet fits the data best). Pogorelyuk et al. 2022 describes the deconfusion algorithm and estimates of confusion rates from simulated planetary systems using the deconfuser.

About Demo

AESTRA: Auto-Encoding STellar Radial-velocity and Activity

Liang, Yan et al.

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https://emac.gsfc.nasa.gov?cid=2401-003
2401-003

AESTRA (Auto-Encoding STellar Radial-velocity and Activity) is a deep learning method for precise radial velocity measurements in the presence of stellar activity noise. The architecture combines a convolutional radial-velocity estimator and a spectrum auto-encoder called spender. For an in-depth understanding of the spectrum auto-encoder, see Melchior et al. 2023 and Liang et al. 2023.

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sai: Surface-Atmosphere Interactions on Warm Exoplanets

Byrne, Xander et al.

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https://emac.gsfc.nasa.gov?cid=2401-002
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For warm rocky planets, broadly Venus-like planets, the high temperatures and moderate pressures at the base of their atmospheres may enable thermochemical equilibrium between rock and gas. This links the composition of the surface to that of the observable atmosphere. sai is a repository containing files for the GGchem equilibrium chemistry code, and associated helper functions, which we used to find a boundary in surface pressure-temperature space which simultaneously separates distinct mineralogical regimes and atmospheric regimes, potentially enabling inference of surface mineralogy from spectroscopic observations of the atmosphere (Byrne+23, MNRAS).

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VSPEC: Variable Star PhasE Curve

Johnson, Ted; Kelahan, Cameron et al.

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https://emac.gsfc.nasa.gov?cid=2401-001
2401-001

VSPEC (Variable Star PhasE Curve) is an exoplanet modeling suite that combines NASA’s Planetary Spectrum Generator (PSG) with a custom variable star. Originally built to simulate the infrared excess of non-transiting planets, the code supports transit, eclipse, phase curve geometries as well as spots, faculae, flares, granulation, and the transit light source effect. Install it with pip or see the documentation linked below.

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pycrires: Data reduction pipeline for VLT/CRIRES+

Stolker, Tomas; Landman, Rico

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https://emac.gsfc.nasa.gov?cid=2312-001
2312-001

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.

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ExPRES: Exoplanetary and Planetary Radio Emission Simulator

Louis, C. K. et al.

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https://emac.gsfc.nasa.gov?cid=2311-007
2311-007

ExPRES (Exoplanetary and Planetary Radio Emission Simulator) is a versatile tool that computes the observation opportunities of planetary radio emissions, based on the radio source beaming patterns and the observer’s location. The ExPRES code is assuming that auroral radio waves are emitted through the Cyclotron Maser Instability (CMI). This emission mechanism can transfer free energy present in the electron distribution function in the source, into the ambient electromagnetic fluctuation background, thus amplifying waves at a frequency close to the local electron cyclotron frequency, as a resonator.

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MAGPy-RV: Modelling stellar Activity with Gaussian Processes in Radial Velocity

Rescigno, Federica ; Dixon, Bryce ; Haywood, Raphaëlle D.

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https://emac.gsfc.nasa.gov?cid=2311-006
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MAGPy-RV models data with Gaussian Process regression and affine invariant Monte Carlo Markov Chain parameter searching. Developed to model intrinsic, quasi-periodic variations induced by the host star in radial velocity (RV) surveys for the detection of exoplanets and the accurate measurements of their orbital parameters and masses, it now includes a variety of kernels and models and can be applied to any time-series analysis. MAGPy-RV includes publication level plotting, efficient posterior extraction, and export-ready LaTeX results tables. It also handles multiple datasets at once and can model offsets and systematics from multiple instruments.

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NcorpiON: An O(N) software for N-body integration in collisional and fragmenting systems

Couturier, J.; Quillen, A. C.; Nakajima, M.

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https://emac.gsfc.nasa.gov?cid=2311-005
2311-005

NcorpiON is an N-body software developed for the time-efficient integration of collisional and fragmenting systems of planetesimals or moonlets orbiting a central mass. It features a fragmentation model, based on crater scaling and ejecta models, able to realistically simulate a violent impact. NcorpiON is designed for the study of accreting or fragmenting disks of planetesimal or moonlets. It detects collisions and computes mutual gravity faster than REBOUND, and unlike other N-body integrators, it can resolve a collision by fragmentation. The fast multipole expansions are implemented up to order six to allow for a high precision in mutual gravity computation.

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PBjam

Carboneau, Lindsey; Davies, Guy; Hall, Oliver; Lyttle, Alex; Nielsen, Martin

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https://emac.gsfc.nasa.gov?cid=2311-004
2311-004

PBjam is toolbox for modeling the oscillation spectra of solar-like oscillators. This involves two main parts: identifying a set of modes of interest, and accurately modeling those modes to measure their frequencies. Currently, the mode identification is based on fitting the asymptotic relation to the l=2,0 pairs, relying on the cumulative sum of prior knowledge gained from NASA's Kepler mission to inform the fitting process. Modeling the modes, or 'peakbagging', is done using the HMC sampler from pymc3, which fits a Lorentzian to each of the identified modes, with much fewer priors than during he mode ID process.

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DACE: Data & Analysis Center for Exoplanets

Ségransan, D. et al.

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https://emac.gsfc.nasa.gov?cid=2311-003
2311-003

The Data & Analysis Center for Exoplanets (DACE) is a PlanetS web-platform located at the University of Geneva (CH) dedicated to extrasolar planets data visualisation, 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.

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tapify: A Multitaper Periodogram package for computing the power spectrum of a time-series with minimal spec

Patil, A. et al.

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https://emac.gsfc.nasa.gov?cid=2311-002
2311-002

tapify is a Python package that implements a suite of multitaper spectral estimation techniques for analyzing time series data. It supports analysis of both evenly and unevenly sampled time series data. The multitaper statistic was first proposed by Thomson (1982) as a non-parametric estimator of the spectrum of a time series. It is attractive because it tackles the problems of bias and consistency, which makes it an improvement over the classical periodogram for evenly sampled data and the Lomb-Scargle periodogram for uneven sampling. In basic statistical terms, this estimator allows us to confidently look at the properties of a time series in the frequency or Fourier domain.

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MADYS: Isochronal parameter determination for young stellar and substellar objects

Squicciarini, V., & Bonavita, M.

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https://emac.gsfc.nasa.gov?cid=2311-001
2311-001

MADYS (Manifold Age Determination for Young Stars) determines astrophysical parameters (such as age, mass, radius and Teff) of young stellar and substellar objects. The code automatically retrieves and cross-matches photometry from several catalogs, estimates interstellar extinction, and derives parameter estimates for individual objects through isochronal fitting. Harmonizing the heterogeneity of publicly-available isochrone grids, MADYS enables its users to choose amongst >140 grids from >20 models. Its versatility allows for a wide range of scientific applications, ranging from the characterization of directly imaged planets to the study of stellar associations.

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ExoFOP: The Exoplanet Follow-up Observing Program

NASA Exoplanet Archive team at NExScI/IPAC

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https://emac.gsfc.nasa.gov?cid=2310-007
2310-007

This website is designed to optimize resources and facilitate collaboration in follow-up studies of exoplanet candidates. ExoFOP serves as a repository for project and community-gathered data by allowing upload and display of data and derived astrophysical parameters.

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pycdata: A module to import datasets from various instruments in pycheops

Jayshil A. Patel, Alexis Brandeker, Pierre Maxted

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https://emac.gsfc.nasa.gov?cid=2310-006
2310-006

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.

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ExoMDN: Rapid Characterization of Exoplanet Interiors with Mixture Density Networks

Baumeister, P. and Tosi, N.

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https://emac.gsfc.nasa.gov?cid=2310-005
2310-005

ExoMDN is a machine-learning-based exoplanet interior inference model using Mixture Density Networks. The model is trained on more than 5.6 million synthetic planet interior structures. Given mass, radius, and equilibrium temperature, ExoMDN is capable of providing a full inference of the interior structure of low-mass exoplanets in under a second without the need for a dedicated interior model.

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Exo_Transmit with Tholin Opacities

Corrales, Lia; Gavilan, Lisseth; Teal, D. J.; Kempton, E. M. R.

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https://emac.gsfc.nasa.gov?cid=2310-004
2310-004

A static, refactored version of Exo_Transmit (Kempton et al. 2017, Teal et al. 2022, Corrales et al. 2023) for computing exoplanet transmission spectra with the new tholin species. This code uses optical constants from tholins grown in the laboratory and computed cross-sections (Mie) for a wide range of particle sizes, for wavelengths of 0.13-10 micron.

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PCM_LBL: Planetary Climate Model (Line-By-Line)

Wordsworth, Robin et al.

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https://emac.gsfc.nasa.gov?cid=2310-003
2310-003

PCM_LBL is a 1D radiative-convective code designed to simulate the climates of diverse planetary atmospheres, from present-day Earth to early Mars and exoplanets. The code is written in modular modern Fortran and uses a 'brute-force' spectral approach where absorption coefficients are computed on a fixed spectral grid directly from line data. This allows climate calculations to be performed more simply and at higher accuracy than in a correlated-k approach.

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GEOCLIM: Global Silicate Weathering Estimation

Baum, Mark; Fu, Minmin

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https://emac.gsfc.nasa.gov?cid=2310-002
2310-002

This module replicates some features of the GEOCLIM model, originally written in Fortran, but now in Julia to make them easier to use. The module implements these formulations to estimate global silicate weathering rates from gridded climatology, typically taken from the results of a global climate model like CCSM or FOAM. It is intended to estimate weathering during periods of Earth history when the continental configuration was radically different, typically more than 100 million years ago. For more information about the original GEOCLIM, see the Methods/Supplement of Goddéris et al.

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photoevolver

Fernández, Jorge

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https://emac.gsfc.nasa.gov?cid=2310-001
2310-001

photoevolver is a Python module that evolves the gaseous envelope of planets backwards and forward in time, taking into account internal structure and cooling rate, atmospheric mass loss processes, and the stellar X-ray emission history.

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smart: Spectral Modeling Analysis and RV Tool

Hsu, Chih-Chun; Burgasser, Adam; Theissen, Chris; Birky, Jessica

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https://emac.gsfc.nasa.gov?cid=2309-001
2309-001

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.

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CROCODILE: CROss-COrrelation retrievals of Directly-Imaged self-Luminous Exoplanets

Hayoz, J. et al. 2023

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https://emac.gsfc.nasa.gov?cid=2308-001
2308-001

CROCODILE provides the statistical framework to interpret the three main observables of directly-imaged exoplanetary atmospheres, namely photometry, low-resolution spectroscopy, and medium (and higher) resolution cross-correlation spectroscopy. These will be measured by the next generation of instruments such as ERIS at the Very Large Telescope, MIRI aboard the James Webb Space Telescope, and METIS at the future Extremely Large Telescope.

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mr-plotter: Mass-Radius Diagrams Plotter

A. Castro-González, J. Lillo-Box

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https://emac.gsfc.nasa.gov?cid=2307-001
2307-001

Mister plotter (mr-plotter) is a user-friendly Python tool that creates paper-ready mass-radius diagrams with your favorite theoretical models. It also includes the ability to color-code diagrams based on any published stellar or planetary property collected in the NASA Exoplanet Archive.

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MAGIC: Microlensing Analysis Guided by Intelligent Computation

Haimeng Zhao and Wei Zhu

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https://emac.gsfc.nasa.gov?cid=2306-004
2306-004

MAGIC is a machine learning framework to efficiently and accurately infer the microlensing parameters of binary events with realistic data quality. In MAGIC, binary microlensing parameters are divided into two groups and inferred separately with different neural networks. The key feature of MAGIC is the introduction of neural controlled differential equation, which provides the capability to handle light curves with irregular sampling and large data gaps. MAGIC is able to locate degenerate solutions in real events even when large data gaps are introduced. As irregular samplings are common in astronomical surveys, it also has implications to other studies that involve time series.

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SWAMPE: A Shallow-Water Atmospheric Model in Python for Exoplanets

Landgren, E. and Nadeau, A.

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https://emac.gsfc.nasa.gov?cid=2306-003
2306-003

SWAMPE is a Python package for modeling the dynamics of exoplanetary atmospheres. SWAMPE is an intermediate-complexity, two-dimensional shallow-water general circulation model. Benchmarked for synchronously rotating hot Jupiters and sub-Neptunes, the code is modular and could be easily modified to model dissimilar space objects, from Brown Dwarfs to terrestrial, potentially habitable exoplanets. SWAMPE can be easily run on a personal laptop.

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Bioverse: Simulation framework for Bayesian hypothesis testing of statistical exoplanet missions

Alex Bixel et al.

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https://emac.gsfc.nasa.gov?cid=2306-002
2306-002

Bioverse is a quantitative framework for assessing the diagnostic power of a statistical exoplanet survey. It combines Gaia-based stellar samples with Kepler-derived exoplanet demographics and a mission simulator that enables exploration of a variety of observing, follow-up, and characterization strategies. Uniquely, Bioverse contains a versatile module for population-level hypothesis testing supporting trade studies and survey optimization. It currently supports direct imaging or transit missions, but its modularity makes it adaptable to any mission concept that makes measurements on a sample of exoplanets.

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TurbospectrumNLTE: Synthetic stellar spectra calculator LTE / NLTE

Plez, Bertrand; Gerber, Jeff; Magg, Ekaterina; Bergemann, Maria

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https://emac.gsfc.nasa.gov?cid=2306-001
2306-001

Latest version of TS (Turbospectrum), with NLTE capabilities. Computation of stellar spectra (flux and intensities) in 1D or average <3D> stellar atmosphere models. In order to compute NLTE stellar spectra, additional data is needed, downloadable outside GitHub. See documentation in DOC folder Python wrappers are available at https://github.com/EkaterinaSe/TurboSpectrum-Wrapper/ and https://github.com/JGerbs13/TSFitPy They allow interpolation between models and fitting of spectra to derive stellar parameters.

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Applefy: Robust detection limits for high-contrast imaging

Bonse, Markus J.; Gebhard, Timothy D.

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https://emac.gsfc.nasa.gov?cid=2305-003
2305-003

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.

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Tiberius: Time series spectral extraction and transit light curve fitting

Kirk, J.

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https://emac.gsfc.nasa.gov?cid=2305-002
2305-002

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.

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light-curve: Irregular time series analysis toolbox for Rust and Python

Malanchev, K.; Lavrukhina, A.

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https://emac.gsfc.nasa.gov?cid=2305-001
2305-001

The "light-curve" project is a toolbox for analyzing irregular time-series data, consisting of two components: a feature extractor and a dm-dt mapper. Feature extraction is available as Rust and Python libraries, including various feature extractors like magnitude statistics, shape-based features, Lomb-Scargle periodogram peaks, and parametric fits. The dm-dt mapper represents observation pairs as 2-D points based on magnitude and time differences, available in the same Python library, the Rust library, and a binary executable for generating PNG images.

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ExoCcycleGeo: Geophysical and geochemical controls on abiotic carbon cycling on Earth-like planets

Neveu, M. et al.

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https://emac.gsfc.nasa.gov?cid=2302-005
2302-005

This model of geological carbon fluxes leverages widely used geochemical codes of solid-melt equilibria for silicate rocks (MELTS) and of equilibria and kinetics of water-rock interactions (PHREEQC). Coupled with a simple numerical computation of global thermal evolution, this model enables investigation of the effects of planet size (mass) and bulk, surface, and upper mantle composition on carbon cycling through geologic time. Its applicable size range (0.5 to 2 Earth masses) is limited by the fidelity of the geodynamic model. The applicable range of compositions is limited by those that can be handled by MELTS and PHREEQC.

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MATRIX ToolKit: ToolKit for Multi-phAse Transits Recovery from Injected eXoplanets

Dévora-Pajares, Martín & Pozuelos, Francisco J.

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https://emac.gsfc.nasa.gov?cid=2302-004
2302-004

The MATRIX ToolKit has been specially designed to establish detection limits of photometry data sets by performing robust injection-and-recovery analyses on a three dimensional grid of scenarios (orbital period vs planetary radius vs transit epoch). This kind of scientific detection threshold determination can now be done with a simple python command with the significant addition of taking into account different transit epochs, which helps to establish a more reliable detection rate for a given period and radius.

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WATSON: Visual Vetting and Analysis of Transits from Space ObservatioNs

Dévora-Pajares, M.

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https://emac.gsfc.nasa.gov?cid=2302-003
2302-003

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.

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PEPITA: Prediction of Exoplanet Transit Parameters Precisions using Information Analysis Techniques

Julio Hernandez Camero

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https://emac.gsfc.nasa.gov?cid=2302-002
2302-002

PEPITA is a Python package that allows making predictions for the precision of exoplanet parameters using transit light-curves, without the need of performing a fit to the data. Behind scenes, it makes use of the Information Analysis techniques to predict the best precision that can be obtained by fitting a light-curve without actually needing to perform the fit.

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PyMieScatt: The Python Mie Scattering package

Sumlin, B., Heinson, W., and Chakrabarty, R.

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https://emac.gsfc.nasa.gov?cid=2302-001
2302-001

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!

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SHERLOCK: Searching for Hints of Exoplanets fRom Lightcurves Of spaCe-based seeKers

Dévora-Pajares, M. & Pozuelos, F. J. et al.

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https://emac.gsfc.nasa.gov?cid=2301-001
2301-001

SHERLOCK is an end-to-end pipeline that allows the users to explore the data from space-based missions to search for planetary candidates. It can be used to recover alerted candidates by the automatic pipelines such as SPOC and the QLP, the so-called Kepler objects of interest (KOIs) and TESS objects of interest (TOIs), and to search for candidates that remain unnoticed due to detection thresholds, lack of data exploration or poor photometric quality.

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PACMAN: A pipeline to reduce and analyze Hubble Wide Field Camera 3 IR Grism data

Zieba, Sebastian and Kreidberg, Laura

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https://emac.gsfc.nasa.gov?cid=2212-006
2212-006

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.

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PHOTOe: An efficient Monte Carlo model for the slowing down of photoelectrons

A. García Muñoz

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https://emac.gsfc.nasa.gov?cid=2212-005
2212-005

Monte Carlo model for simulating the slowing down of photoelectrons in gases in the local deposition approximation.

Version v1 works with H and He atoms plus thermal electrons. The model is described in: García Muñoz, Icarus, Volume 392, 1 March 2023, 115373

The model is available on https://antoniogarciamunoz.wordpress.com/ and upon email request from the author.

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SpecMatch-Empirical: Spectroscopic characterization of stars with an empirical spectral library

Yee, Samuel; Petigura, Erik; von Braun, Kaspar