〘 Astrophysics 〙

Usage Requirements: Fairly strong internet connection, decent graphics processing for downloadable software.

Using either the web-based interactive or the downloadable application, explore the night sky using this well-known software detailing the celestial sphere. Great for outreach, education, amateur astronomy, and anyone who wants to take a zoomed-in look at the night sky. Use this tool to determine exactly what the sky will look like at a specific location and time and to gain an interactive understanding of how to use popular astronomical coordinate systems. Stellarium allows you to chart magnitude, position, and other physical properties of almost all astronomical objects.

Contributor: Amelia Binau, Indiana University

Usage Requirements: Strong internet connection.

Universe Monitor is a free public website created by Dave Owen, AKA "Space Dave" of Te Awamutu, New Zealand. Owen is also the creator of the Te Awamutu Space Centre, a space museum and education center. The website contains live feeds, video, CGI visualizations, text reports, etc. from various sources, such as the Solar Dynamics Observatory, NASA Earth Observatories, NOAA, ISS, etc, and includes recent space news, launches, and random astronomical facts. It is accessible from any device. Dave Owen writes that anyone is able to access the website for educational purposes, as well as set up public displays for science museums, observatories, and schools. To help keep the website ad-free, one can support their Patreon and learn more about the service on their about page.

Contributor: Robert J. Mailliard, Indiana University - Bloomington

Usage Requirements: Works best on Linux, but also available on MacOS and Windows

How do astronomers process, analyze, and display the electromagnetic data they collect through telescopes from astronomical objects? One of the most common software for this purpose is SAODS9, a product of theChandra X-Ray Center (CXC). This software requires astronomical data to be contained in FITS (Flexible Image Transport System) files, which is the standard among astronomers. NASA has collected public FITS files for processing here and more are available on MAST.

Contributor: Amelia Binau, Indiana University

Usage Requirements: Fairly strong internet connection, paid subscription.

Slooh is a powerful online platform that allows educators and amateur astronomers remotely access telescopes in Chile, the Canary Islands, and Australia. Simply select a target & telescope, queue a scheduling block, adjust preferences, and watch as your research-grade image is captured. It is a brilliant, interactive way to explore the cosmos. Slooh hosts a variety of educational events and more advanced research options (have your data exported as FITS files for more detailed examination) and a constant stream of observations is available to watch in real-time. While the service comes with a price, I helped use this platform for Purdue University's physics and astronomy outreach program and I can personally attest it is worth the investment if you're strongly interested in amateur astronomy but are overwhelmed with the mechanics/cost of a full personal telescope.

Contributor: Amelia Binau, Indiana University

Usage Requirements: TOPCAT requires Java environment to run. It can be used with or without an internet connection, but an internet connection is required if you want to use its database searching capabilities.

From their website "TOPCAT is an interactive graphical viewer and editor for tabular data. Its aim is to provide most of the facilities that astronomers need for analysis and manipulation of source catalogues and other tables, though it can be used for non-astronomical data as well. It understands a number of different formats, both astronomically important (FITS, VOTable, CDF) and general purpose (CSV, ASCII, Parquet), and more formats can be added. It is especially good at interactive exploration of large (multi-million row, lots of columns) tables. It handles the following file types (list from their website): FITS BINTABLE (binary table) or TABLE (ASCII table) extensions, VOTables in any of the format variants (TABLEDATA, FITS, BINARY, BINARY2) or versions, ASCII tables in a number of variations, CDF files, Comma-Separated Values (CSV), Enhanced Character-Separated Values (ECSV), Results of SQL queries on relational databases, Parquet files, IPAC format, AAS Machine-Readable Tables, HAPI streams, Feather files, GBIN files. It offers a variety of ways to view and analyse tables, including a browser for the cell data themselves, viewers for information about table and column metadata, and facilities for sophisticated interactive 1-, 2-, 3- and higher-dimensional visualisation, calculating statistics and joining tables using flexible matching algorithms. Using a powerful and extensible Java-based expression language new columns can be defined and row subsets selected for separate analysis. Table data and metadata can be edited and the resulting modified table can be written out in a wide range of output formats. It is a stand-alone application which works quite happily with no network connection. However, because it uses Virtual Observatory (VO) standards, it can cooperate smoothly with other tools, services and datasets in the VO world and beyond. The program is written in pure Java (except for optional Parquet I/O libraries) and available under the GNU General Public Licence, though some of the library code is LGPL. Source code is available at https://github.com/Starlink/starjava. It has been developed mostly in the UK within various UK and Euro-VO projects (Starlink, AstroGrid, VOTech, AIDA, GAVO, GENIUS, DPAC) and under PPARC and STFC grants. Its underlying table processing facilities are provided by the related packages STIL and STILTS. In my experience, it is an excellent resource for handling large data tables, and it is very straightforward to use.

Contributor: Prof. Jeffrey Gerber, Purdue University

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

This non-profit organization of both amateur and professional astronomers aims to provide scientific and educational resources worldwide to those who are interested in variable stars. Memberships are open to anyone and offers observing guides and manuals for those interested in helping deepen their pool of data on variable stars.

Contributor: Braden Garretson, Purdue University

Language Requirement(s): Compatible with C++, Fortran 90, IDL, Java and Python. Usage Requirements: Use of FITS files.

Designed specifically for descritization/pixelizations and analysis of data on a sphere, particularly for detailed studies of the cosmic microwave background (CMB), HEALPix allows for the analysis and visualization of any data that are constrained to the surface of a sphere. Additionally useful for Earth & planetary data, including satellite imaging. A Python wrapper for HEALPix, healpy, is also available.

Contributor: Amelia Binau, Indiana University, Bloomington

Language Requirement(s): Fortran. Usage Requirements: Use of FITS files.

PolSpice calculates cross-correlation functions between parameters of spherically-based maps (specifically maps of cosmic microwave background) of Stokes parameters, specifically maps pixelized by software like HEALPix. A Python wrapper, python_spice, is also available.

Contributor: Amelia Binau, Indiana University, Bloomington

Language Requirement(s): Requires C/C++ and a compiler, MPI (for parallel computing), and Python (for the interactive setup GUI), and a Linux/Unix environment or equivalent. Usage Requirements: Standard laptop sufficient for basic tests, HPC cluster required for heavy production. Outputs raw binary, HDF5, or VTK files. Works offline.

A highly modular, multi-physics code optimized for high-Mach-number, discontinuous astrophysical fluid flows. Users use an interactive Python menu to configure plasma settings to simulate environments like stellar winds or relativistic jets, making it the ideal pedagogical gateway into grid-based MHD. PLUTO is not the only code for MHD in astrophysics, all of which have their own strengths and weaknesses (see: Athena++, AthenaK, Cholla, etc.).

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Python via Astroquery or Java via Aladin, if you wish to use either for access instead of the standard web API. Usage Requirements: Web-accessible catalog database requires internet connection to query, although data can be saved locally later.

An international scientific data hub operated by the Strasbourg Observatory that provides access to global astronomical databases. This includes SIMBAD, VizieR, and Aladin. It serves as an indispensable lookup ecosystem for identifying celestial obejcts and sourcing archival data.

Contributor: Amelia Binau, Indiana University - Bloomington, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): None (desktop application). Usage Requirements: Desktop OS, USB3.0/2.0 ports for camera connections, optional local or remote storage for captured image files, internet connection optional. Depending on operation system, might require a specialized driver download.

ASIStudio is ZWO's official, all-in-one desktop software suite designed for astrophotography acquisition. It is specially designed for ZWO's consumer- and pro-level CCD/CMOS cameras. It breaks down into specialized sub-apps (like ASIImg for deep-sky imaging, ASILive for real-time image stacking, etc.), providing an integrated platform to control cameras, focusers, and filter wheels without needing complex setups.

Typically, for Linux/MacOS, you don't need any drivers. For Windows, you typically need to install the following ZWO drivers alongside ASIStudio:

• ASCOM Platform
• 3.5 Net Framework
• ASCOM Driver
• Camera Driver

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Language agnostic (REST API, official and community Python libraries also exist). Usage Requirements: Active internet connection, user registration to obtain an API access token if wanted, HTTP client, or Python environment.

Operated by the Smithsonian Astrophysical Observatory (SAO) under a NASA grant, ADS is the primary digital library for research papers in astronomy, astrophysics, and physics. Its REST API enables developers to programmatically search millions of publication abstracts, track citation networks, extract BibTeX entries, and analyze academic metrics. It's also an amazing way to find papers, get PDF or HTML versions of those papers, and see results by authors or by similar topic.

It is important to note that ADS is transitioning (although not entirely) to a more generalized science literature platform, called SciX. The impacts of this on ADS are still unclear at this time.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): REST/HTTP queries for raw data feeds, otherwise no language requirements. Usage Requirements: Active internet connection. Compatible with a web browser or server-side fetcher.

Based on numerical weather prediction models from the US and Europe, Clear Sky Charts provide hourly forecasts tailored specifically for amateur astronomers. They evaluate localized cloud cover, atmospheric transparency, and astronomical seeing over a 96-hour window for thousands of observing sites across North America. Integrations can display visual forecast charts directly on site-specific dashboards. As with any weather-based system, these predictions are predictions, and are subject to changes, fluctuations, or are possibly completely incorrect.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Python. Usage Requirements: Python-compatable IDE or Jupyter Notebooks

Astropy is an all-in-one Python package focused on helping astronomers/astrophysicists navigate and transform large and small datasets. It allows users to easily work with numerous types of coordinate systems, constants, units, dates and times, and models and fitting. The package makes it easy to create, modify, and interface with FITS files, a common file type for working with astronomical data. Astropy is a must-have package for astronomers of all experience levels working in Python.

Contributor: Ethan Pinarski, Purdue University

Language Requirement(s): Python. Usage Requirements: Python-compatable IDE or Jupyter Notebooks

Altaipony is used to analyze flaring data from Kepler, K2, and Tess missions. It has built-in functions that lessen the noise of photometric data and identify flares from the normalized data. It’s completely free and the data from these missions can be pulled fromMASTthrough Altaipony. It also works with target pixel files! (andLightkurvedoes all of this as well).

Contributor: Grace Cassidy, Purdue University

Language Requirement(s): Python. Usage Requirements: Python-compatable IDE or Jupyter Notebooks

REBOUND can be used to run N-body simulations easily. It takes into account all gravitational influences and does the numerical integration for you. This is useful for simulations of what our solar system may look like over a large timescale, simulations of stellar flybys, exoplanet systems, exomoons, mergers, the kozai-lidov effect, and many more open and current areas of research. REBOUNDx (rebound eXtension) includes non-gravitational effects such as tides, mass loss, GR.

Contributor: Max Edelman, Tufts University Graduate

Language Requirement(s): Python. Usage Requirements: Python-compatable IDE or Jupyter Notebooks

This package is extremely useful in downloading and analyzing flux-time series data. Through this package you can download this flux data from TESS, Kepler, and Kepler 2. You can then easily visualize and analyze the light curves and target pixel data provided by those telescopes. This is useful in research for exoplanet detection, spots and flares, determining rotational periods, and much more. In addition, you can use “Wotan” which is another free python package to easily detrend the data to be able to work with flat lightcurves, which is again useful for exoplanet detection, etc.

Contributor: Max Edelman, Tufts University Graduate

Language Requirement(s): Terminal, Bash, Fortran 90. Usage Requirements: Ubuntu Linux setup for windows, or IOS alternative, git packages

MESA is a hydrodynamic code that simulates stars, black bodies, and supernovae remnants. It is often used to simulate stars along the main sequence. The applications are wide in astrophysics and nuclear physics. You can use it to simulate the life and conditions of just about any star or black body you want. MESA also hosts a yearlysummer school; past summer schools have their materials publishedonline.

Contributor: Aydian Brown, Purdue University

Language Requirement(s): Terminal C-Based Language. Usage Requirements: Ubuntu Linux setup for windows or IOS alternative

DISCO is a moving-mesh hydrodynamics code that simulates gases moving and evolving at its core. This can be applied to any problem in astrophysics and broader applications for other hydrodynamic/fluid dynamic problems. For example, one could simulate a pulsar or a fluid-based experiment in a lab. The basics are set up for you in templates and you can create any fluid dynamic simulation you want simply by utilizing a little basic C and reading the source code.

Contributor: Aydian Brown, Purdue University

Language Requirement(s): Python. Usage Requirements: Python-Compatable IDE, Jupyter Notebook

galpy allows the user to model galactic dynamics or any large-scale system in a gravitaitonal potential. With plenty of examples and documentation, users can plot rotation curves and integrate orbits (plot object paths over time).

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Python. Usage Requirements: Python-Compatable IDE & compiler, internet connection for dataset downloading

SunPy is an open-source Python library for solar physics data analysis. It provides tools to query and download data from major solar observatories (like SDO and SOHO) and coordinate transformations specific to the Sun, helping solar scientists and learners study solar flares and space weather.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Fortran backend, Python interface (through python-FSPS). Usage Requirements: Requires stellar evolution and spectral libraries (which can be installed through FSPS). Requires moderate computing resources.

A library designed to compute the spectral energy distributions (SEDs) and evolution of stellar populations. It allows users to simulate how galaxies change in brightness and color over time under different chemical configurations, which is vital for matching computational models to actual telescope observations.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Python. Usage Requirements: Standard laptop hardware. Handles FITS, ASCII, and CSV files. Works offline once the required reference data files are downloaded.

A synthetic photometry software package developed by STScI that simulates astronomical observations through various telescope filters. Users input stellar spectra to calculate predicted counts and magnitudes, which is critical for planning and calibrating observations with telescopes like HST and JWST.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Python (with NumPy and Matplotlib). Usage Requirements: Local installation of the core RADMC-3D executable (compiled via gfortran/make). Standard computer hardware is sufficient. Reads and writes custom RADMC-3D text/binary inputs, FITS files, and VTK data. Works offline.

A comprehensive Python library meant for pre- and post-processing of RADMC-3D files, used to compute dust and gas radiative transfer. Users write Python scripts to generate grid density structures and plot resultant synthetic images or spectral energy distributions (SEDs). This makes it an indispensable, highly accessible diagnostic tool for modeling dust behavior in galaxies and protoplanetary disks.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Python. Usage Requirements: Scales from consumer laptops to supercomputer clusters, works offline but may require moderate RAM for larger datasets.

A powerful Python package designed for analyzing and visualizing volumetric, spatially-resolved data from astrophysical studies and simulations. Users write scripts to generate slices, projections, and 3D volume renderings, lowering the barrier for researchers to interpret complex galaxy and star formation simulations, among other visualization uses.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Requires Python and a C compiler (wraps NASA's SPICE Toolkit shared library). Usage Requirements: Works offline on standard laptop hardware. Handles SPICE binary kernel files (.bsp, .bc, .tls).

The official Python wrapper for NASA's SPICE toolkit, which is the international standard for calculating space geometry and planetary trajectories. It allows students to calculate the precise positions, velocities, and orientations of planets, satellites, and spacecraft at any given moment in time, making it useful for planetary science and mission planning.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Requires Python and multiple Python packages as dependencies, such as NumPy and Astropy. Usage Requirements: Cross-platform, parallelizable for multi-core CPU projects, and works offline once necessary files and data are loaded.

An open-source software for analysing the morphologies & structures of galaxies. It uses inference and analysis to dissect galaxy images into light profiles and identifies structural features like bars, spiral arms, merger tidal tails, etc. This helps bridge the gap between raw telescope imagery (like ALMA) and astrophysical morphology measurements. PyAutoGalaxy can also fit interferometer data from observatories.

Contributor: Amelia Binau, Indiana University - Bloomington, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Requires Python and PyTorch/Tensorflow. Usage Requirements: Local hardware for fine-tuning or inference, but GPU hardware recommended for model training (and is supported). Works offline once necessary files are downloaded.

An open-source Python library developed by the Galaxy Zoo collaboration that provides pre-trained deep learning models for galaxy morphology classification. Trained on millions of answers by volunteers, Zoobot lets researchers fine-tune Bayesian convolutional neural networks and vision transformers to identify specific features of galaxies with minimal new training labels and code. Such features include spiral arms, bars, or galaxy mergers.

Contributor: Amelia Binau, Indiana University - Bloomington, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Requires Python with PIP or Conda, and multiple package dependencies. Some basic SQL knowledge typically helpful or required. Usage Requirements: Internet connection for querying (pending the requested servers are currently online too). Returned info can be cached locally.

An official Astropy-affiliated Python package that provides a programmatic web-query interface to astronomical databases. It enables researchers to query remote databases and archives, like SIMBAD, ESA's GAIA, VizieR, among others. You can then automatically load catalog data, spectra, and images into standardized Astropy/Numpy/Pandas formats for processing. SQL knowledge is helpful in making correct queries.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Python, with C extensions. Usage Requirements: Requires a C compiler for building backend extensions upon installation. Internet connection optional (runs offline after setup).

BATMAN stands for Bad-A** Transit Model cAlculatioN. It generates fast, analytical transit models using custom or standard radial limb-darkening laws. Written in C and wrapped for Python, it can calculate millions of transit light curves in seconds, making it the standard forward-modeling endinge to pair with MCMC samplers like emcee.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Python/C++. Usage Requirements: C++ compiler for PyMC model compilation, runs offline.

Part of the PyMC ecosystem, exoplanet provides probabilistic tools designed specifically for astronomical time-series data. It pairs C++ evaluations of orbital mechanics and limb-darkening models with Gaussian Processes to handle stellar variability. This enables robust Bayesian parameter estimation via Hamiltonian Monte Carlo (HMC). As the name suggests, this PyMC package is focused on applying these tools to the observations of exoplanets.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): Fortran (for development). Usage Requirements: Fortran compiler (i.e. gfortran), Unix/Linux/macOS terminal environment, local compute resources (runs offline, might require supercomputers for more compelx simulations).

YREC is a high-precision stellar evolution code developed at Yale University to model 1D hydrostatic stars from pre-main sequence through helium burning. It incorporates pseudo-2D rotational effects, internal angular momentum transport, and magnetic wind braking (among others), serving as a core computational tool for solar physics, astroseismology, and general stellar theory.

Contributor: Neil Ghugare, University of Florida

Language Requirement(s): None; depends on file format of choice. Usage Requirements: Web-based; internet connection and/or local storage required. IDE/programming environment of choice required.

A free, comprehensive, massive catalog of over 36,000 open-source datasets/metadata collected or published by NASA. Query a perfect dataset for your project by file type, subfield, and license for use. Includes data for Earth sciences, planetary sciences, high-energy physics, geology, oceanography, and more. Particularly useful, as well, for projects focused on geophysics. NASA has created an interesting infographic detailing the breadth of topics cataloged.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

Spectra, images, photometry. Through their extensivecatalog, the Space Telescope Science Insitute allows simple querying of mass collections of astronomical data spanning missions such as JWST, Hubble, TESS, and more, including ground-based observations. Select a mission/enter the name of an astronomical target and begin querying.

Contributor: Grace Cassidy, Purdue University

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

The Sloan Digital Sky Survey (SDSS) is one of the largest and longest-running astronomical surveys ever, regularly mapping over one-third of the night sky since 2000. SDSS is made up of several smaller surveys over each phase of operation (I-V), which collect data through images and spectroscopy in both the optical and near-infrared light regimes. These surveys consist of the Sloan Legacy Survey (which took data of ~2 million objects, 800,000 galaxies, and 100,000 quasars), the Baryon Oscillation Spectroscopic Survey (BOSS; which was designed to measure the expansion rate of the Universe), and many more. Data for specific observations and targets can be explored through the SDSS SkyServer

Contributor: Ethan Pinarski, Purdue University

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

Short for Automatic Learning for the Rapid Classification of Events, ALeRCE is a “Chilean-led Community Broker” which uses machine learning models to process and classify events in real-time. It is processing the massive alert data streams from the Zwicky Transient Facility (ZTF) and the Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory in Chile. The abundant data in this broker is often used in time-domain astronomy catch supernovae in their earliest stages.

Contributor: Ethan Pinarski, Purdue University

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

Operated by Caltech under a contract with NASA, NED aims to accelerate scientific discovery in astrophysics by capturing the most reliable census of extragalactic objects. It also provides essential tools and data to facilitate research in astrophysics.

Contributor: Braden Garretson, Purdue University

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

Led by the University of Hawaii and funded by NASA, Pan-STARRS surveys the sky on a continual basis in search for moving or variable objects, such as asteroids, comets, supernovae, variable stars, and more. Pan-STARRS focuses 90% of its observing time in search for Near Earth Objects.

Contributor: Braden Garretson, Purdue University

Language Requirement(s): None. Usage Requirements: Web-based; only internet connection and/or local storage required.

IRSA is a curator of NASA’s infrared and submillimeter mission science products, which include numerous large-area and all-sky surveys. It provides access to a trillion astronomical measurements across 29 bands through its digital archives and query engines. This is resources offers data analysis and visualization tools, and is run through Caltech.

Contributor: Ethan Pinarski, Purdue University

Language Requirement(s): Python (via astroquery.gaia). Usage Requirements: Web browser. Requires a stable internet connection to query the database. Outputs VOTable, FITS, CSV, and JSON file formats. Usability is subject to the current status of the Gaia data servers.

A massive , high-precision astrometric dataset mapping the positions, distances (parallaxes), and 3D motions of over one billion stars in the Milky Way. Researchers use the online repository via ADQL queries to chart galactic structure, stellar evolution, and kinematics.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirement(s): Python. Usage Requirements: Jupyter Notebooks, Python-compatable IDE, .fits files.

The COSMOS-Web survey is a branch of the Cosmic Evolution Survey (COSMOS) utilizing the James Webb Space Telescope MIRI and NIRCam to study galactic creation and evolution in infrared. Part of its research data have been made available to the public, with tutorials for use found here in the form of Jupyter notebooks. The collaboration also hosts an interactive image viewer in which the working field of view for the released data can be examined.

Contributor: Amelia Binau, Indiana University - Bloomington

Usage Requirements: Web browser interface via the ASAS-SN Sky Patrol dashboard or Python APIs. Downloads available in CSV and ASCII table text formats. Requires internet connectivity to query the target database.

A premier, open-access dataset providing real-time and historical photometric light curves for millions of stars across the entire sky. It is an incredibly powerful resource for entry-level researchers looking to study stellar variability, discover supernovae, or practice data-mining variable stars without needing specialized telescope access. Pronounced like “assassin”.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Usage Requirements: Large storage capacity, especially for larger data sets. Internet connection required for initial download. Usage requires Python analysis tools, HDF5 support, and moderate-to-high memory.

Public data releases from the "Feedback in Realistic Environments" project, featuring high-resolution zoom-in cosmological simulations of galaxy formation (and more). It lets independent learners and researchers analyze how stellar winds and supernova feedback shape galaxy structures without needing a supercomputer to run the simulation themselves.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Usage Requirements: Web broweser, Python, or web API. Large local storage for snapshot downloads. Utilizes HDF5 files. Internet connection required for downloading data or running web-based API queries.

A massive, public repository of cosmologicial magnetohydrodynamical simulations tracking the evolution of thousands of galaxies from the early universe to today. It provides a vast "playground" for researchers to extract synthetic galaxy catalogs, track dark matter halo dynamics, and study the cosmic web.

Contributor: Neil Ghugare, University of Florida, The Ohio State University

Language Requirements: Python used in tutorials, but other languages can be used for open data analysis. Usage Requirements: Internet connection for tutorials and access to data, GitHub.

Gravitational Wave Open Science Center (GWOSC) is a collaborative project that serves as the main library for gravitational wave open data and online tutorials. Combining open data from the LIGO, Virgo, GEO600, and KAGRA observatories, this platform allows the user to access the data releases and visualize signals using simple Jupyter Notebooks. Query events based on run number (up through O4b), the mass of the objects involved, distance, and more.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Multi-format dataset (PyTorch tensor files, HDF5, NumPy arrays, or CSV annotations). Language-agnostic, but it seems heavily geared towards Python/uv/Huggingface. Usage Requirements: Requires local disk space and internet connection for initial download.

An astronomical dataset comprising of galaxy imagery, morphological classifications, and Sparse Autoencoder (SAE) latent fefature representations for ESA's Euclid space mission analysis pipelines. The code for the related research paper is also available in the GitHub.

Contributor: Amelia Binau, Indiana University - Bloomington, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Python (distributed as a Python package). Usage Requirements: Internet connection required for download, works offline on standard laptop hardware. Formatted natively for easy integration into machine learning projects and code bases.

GalaxyMNIST is a dataset containing galaxy images labelled by morphology (shape). It is aimed to help with ML debugging and teaching, containing 10,000 images of galaxies, confidently labelled by Galaxy Zoo volunteers. The dataset has four classes: smooth and round, smooth and cigar-shaped, edge-on-disk, and unbarred spiral. The data provides a frictionless way to teach students computer vision, image classification, and machine learning techniques on real scientific data.

Contributor: Amelia Binau, Indiana University - Bloomington, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Language agnostic (SQL-based queries via Python, R, cURL, etc.). Usage Requirements: Active internet connection, modern web browser, or HTTP request library.

Maintained by NexScI at Caltech, the NASA Exoplanet Archive is the authoritative online database for confirmed exoplanet data, stellar properties, and light curves. Its TAP (Table Access Protocol) service allows researchers to programmatically fetch catalog parameters directly into custom analysis pipelines.

Contributor: Neil Ghugare, University of Florida