Gravitational Waves Data Analysis
Table of Contents
🏡 Useful Information
- SXS Gravitational Waveform Database
- LIGOWiki Web Site
- LSC Academic Advisory Committee (LAAC)
- Gravitational-Wave Early Career Scientists (GWECS)
Laser Interferometer Gravitational-wave Observatory (LIGO)
GW project documents:
Publications of the LIGO Scientific Collaboration and Virgo Collaboration
Gravity Spy Project | Doc | Zooniverse | zenodo | zenodo | Kaggle | 2308.15530 | zenodo | zenodo
GW Open Science Center (GWOSC)
- GWOSC Event Portal Snapshots: zenodo
Others
- The Gamma-ray Coordinates Network (GCN) / Transient Astronomy Network (TAN)
- North American Nano-Hertz Observatory for Gravitational-waves (NANOGrav)
- Cosmic Explorer (CE)
- Einstein Telescope (ET)
- Laser Interferometer Space Antenna (LISA):
- The Lunar Gravitational-wave Antenna (LGWA) | GitHub
- The International Pulsar Timing Array (IPTA) Collaboration | GitHub
- Compact Object Mergers: Population Astrophysics and Statistics (COMPAS)
- BlackHoles@Home
📈 Awesome Data Release
- Zenodo for LVK (This community is devoted to data releases associated with publications by the LIGO Scientific Collaboration, Virgo Collaboration and KAGRA Collaboration.)
Sensitivity Design Curve
- Cosmic Explorer Sensitivity Curves
- Noise curves used for Simulations in the update of the Observing Scenarios Paper
- Sensitivity Curves for KAGRA, LIGO and Virgo; used for localization simulations (LIGO-P1200087) for CBC and Burst
- LIGO-T1800545 (Private)
- Updated Advanced LIGO sensitivity design curve
- Early aLIGO Configurations: example scenarios toward design sensitivity (2015-2017)
- Advanced LIGO anticipated sensitivity curves OBSOLETE
- Unofficial sensitivity curves (ASD) for aLIGO, Kagra, Virgo, Voyager, Cosmic Explorer, and Einstein Telescope
- Horizon plots and noise curves for second- and third-generation detectors
- LIGO-T1800084 (Public | Private)
- gw-horizon-plot: https://git.ligo.org/evan.hall/gw-horizon-plot
- Visualizing BNS and BBH detections for 2G and 3G detectors: LIGO-G1900803-v1 (Public | Private)
Gravity Spy
- Gravity Spy Machine Learning Classifications of LIGO Glitches from Observing Runs O1, O2, O3a, and O3b: P2200238 | zenodo | Google colab notebook
- For the most recently uploaded training set used in Gravity Spy machine learning algorithms, please see Gravity Spy Training Set on Zenodo.
- For detailed information on the training set used for the original Gravity Spy machine learning paper, please see Machine learning for Gravity Spy: Glitch classification and dataset on Zenodo. We anticipate moving forward to release more labelled Gravity Spy data sets, including a refined version of this training set which can be found here 10.5281/zenodo.1476551, and data sets containing the annotations provided by our citizen science volunteers.
- GravitySpy O3 and O2 classification model (private)
- GravitySpy guide (private)
IAS Data Release
- New binary black hole (BBH) mergers in the O3a data (2201.02252)
- Supplementary material to “New Binary Black Hole Mergers in the Second Observing Run of Advanced LIGO and Advanced Virgo” (1904.07214, 1902.10331)
- GW search pipeline with higher harmonics from the IAS GW group: gwIAS-HM
coherent WaveBurst Data Release
O4 Data Release
GWTC-3/O3b Data Release
- O3b Catalog Paper Wiki: Private
- Data release for Tests of General Relativity with GWTC-3 (Private | Public)
- Candidate data release: https://doi.org/10.5281/zenodo.5546664
- Glitch modelling: https://doi.org/10.5281/zenodo.5546679
- Data quality products: https://doi.org/10.5281/zenodo.5636795
- Parameter estimation: https://doi.org/10.5281/zenodo.5546662
- O3 search sensitivity: https://doi.org/10.5281/zenodo.5546675
- O1+O2+O3 search sensitivity: https://doi.org/10.5281/zenodo.5636815
- Data behind the figures: https://doi.org/10.5281/zenodo.5571766
- Downsampled O3b PE files for Open Data Workshop: LIGO-T2200137 (Public | Private)
- LIGO-Virgo Cumulative Event/Candidate Rate Plot O1-O3: LIGO-G2102395 (Public | Private) |
- Segments used for creating standard SFTs in O3 data: LIGO-T2300068 (Private)
- Data for Upper Limits on the Isotropic Gravitational-Wave Background from Advanced LIGO’s and Advanced Virgo’s Third Observing Run: LIGO-G2001287 (Public | Private)
- Beyond GWTC-3: Analysing and verifying new gravitational-wave events from the 4-OGC Catalogue: Zenodo
GWTC-2/O3a Data Release
- O3a Catalog Paper Wiki: Private
- O3a subthresh Review Wiki: Private
- GWTC-2.1 - Data Quality Products for GW Searches: Zenodo
- GWTC-2.1 - Sensitivity of search pipelines to simulated signals: Zenodo
- GWTC-2.1 - Parameter Estimation Data Release: Zenodo
- GWTC-2.1 - Candidate Data Release: Zenodo
- GWTC-2.1 - Glitch modelling for events: LIGO-T2100218 (Private) | Zenodo
- Data release for GW200105_162426 and GW200115_042309 (Private)
- Data release for lensing with O3a events: LIGO-P2100173 (Private)
- Data release for Tests of General Relativity with GWTC-2: LIGO-P2000438 (Public | Private)
- GWTC-2: Figures
- Data and plotting scripts for fig. 2: LIGO-P2000251 (Public | Private)
- Data and plotting scripts for fig. 3: LIGO-P2000252 (Public | Private)
- Data and plotting scripts for fig. 4: LIGO-T2000472 (Public | Private)
- Data and plotting scripts for fig. 5: LIGO-T2000473 (Public | Private)
- Data and plotting scripts for fig. 9: LIGO-P2000439 (Private)
- Data and plotting scripts for fig. 11: LIGO-G2001846 (Public | Private)
- Data and plotting scripts for fig. 12: LIGO-G2001865 (Private)
- Data and plotting scripts for fig. 13: LIGO-G2001847 (Public | Private)
- Data and plotting scripts for fig. 16: LIGO-P2000447 (Private)
- Data and plotting scripts for fig. 17: LIGO-P2000448 (Private)
- Parameter Estimation Samples and Skymaps for the O3a Catalog Paper
- Sensitivity of Matched Filter Searches to Binary Black Hole Merger Populations
- Data Release for “Population properties of compact objects from the second LIGO-Virgo Gravitational-Wave Transient Catalog”
- Description of trigger data file contents for O3a events presented in the GWTC-2 catalog of compact binary mergers observed by LIGO and Virgo, generated by the PyCBC and GstLAL searches.
- Glitch model for O3a catalog events
- O3 Search Sensitivity Estimates: LIGO-T2100113 (Private)
- Selected pulsar injection parameters for injection epoch O3April1
- aLIGO, CAL, Official Advanced LIGO Sensitivity Plots
GWTC-1 Data Release
- GWTC-1 project review page: Private
- GWTC-1: All Figures & Trigger Data
- LIGO-P1900305 (Public | Private)
- LIGO-P1900392 (Public | Private)
- Data and plotting scripts for fig. 1: LIGO-P1800374 (Public | Private)
- Data and plotting scripts for fig. 2 and 3: LIGO-P1800373 (Public | Private)
- Data and plotting scripts for fig. 10: LIGO-P1800376 (Public | Private)
- Data and plotting scripts for fig. 11: LIGO-P1800375 (Public | Private)
- Data and plotting scripts for fig. 16: LIGO-P1800395 (Public | Private)
- Parameter estimation sample release for GWTC-1
- Supplementary parameter estimation sample release for GWTC-1: Comparisons to NR
- Sky localization probability maps (skymaps) release for GWTC-1
- Low-latency skymaps for transient GW events in LIGO-Virgo O1 and O2:
- Data release for testing GR with GWTC-1 events
- GWTC-1 Residuals reconstructions:
- LIGO-P1900164 (Private)
- Calibration uncertainty envelope release for GWTC-1
- Power Spectral Densities (PSD) release for GWTC-1
- Parameter estimation posterior samples for BILBY analysis of GWTC-1
- bilby_pe_event_samples (Private)
- Data release for event GW150914 | LVT151012 | GW151226 | GW170104 | GW170608 | GW170814 | GW170817
O1 Data Release
- O1 parameter estimation samples release
- Figure images and data of (Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914)
- Data release from analysis of GW150915 & GW170104 using numerical relativity
- arXiv:1808.08004 [gr-qc] | GitHub
- Data Quality Vetoes Applied to the Analysis of GW150914: LIGO-T1600011 (Public | Private)
- LIGO-P150914 (Observation of Gravitational Waves from a Binary Black Hole Merger) Figure 4 PyCBC: LIGO-G1600105 (Public | Private )
- Localization and broadband follow-up of the gravitational-wave transient GW150914
S5 Data Release
- Selected pulsar injection parameters for S5 injection epoch test4
Others
- GstLAL EW Online Documents:(This includes the template bank, mass model, and pastro files): (Private | Public)
- Template bank and mass model for GstLAL low-latency subsolar mass analysis: (Private | Public)
- BAM catalogue: A catalogue of binary-black-hole numerical relativity waveforms produced using the BAM code: Site | 2303.05419
🎻 Awesome Application
- Real-time status of the LIGO Data Grid | Current Status (GWISTAT)
- GW distance calculator | 1709.08079
- GW Detectors and Sources
- Signal Processing Tutorial
- Gravitational Wave Quickview App
- Gravitational Wave PE Viewer
- PE Demo App
- Masses in the Stellar Graveyard
- GW-Toolbox
- IGWN Conda Distribution
- LIGO-Virgo Compact Binary Catalogue
- GOING THE DISTANCE
- Ned Wright’s cosmology calculator
- Waveform Fitter
- Online event catalog query and REST API
- H0 website (private)
- LISA Detectability Calculator
- FloorBroekgaarden/GW_visualization_detection_number
- Gravitational Wave Observatory Designer
- SurrogateMovie GitHub
👍 Awesome Hero & Expert
Computer Science
(No Particular Order)
Mathematics
(No Particular Order)
Physics
(No Particular Order)
Astrophysics
(No Particular Order)
- 黄崧 SONG HUANG: Website | GitHub | taotie
- Miles Cranmer: Website/Blog | GitHub
- Charlie Hoy: Profile | GitHub
- Leonardo Werneck: Website/Profile
- Johannes Buchner: Profile | GitHub
- Wuhan University Astrophysics Group: Website | GitHub
- 赵文 Wen Zhao: Website
- 邵立晶 Lijing Shao: Website
- 杨辰涛 C. Yang: Blog
- 天文理科人: Website
- AstroBetter - Tips and Tricks for Professional Astronomers: Website
- Astrobites - The astro-ph reader’s digest: Website
Gravitational-wave Astrophysics
(No Particular Order)
- Neil Cornish: Profile
- Eliu Huerta: Profile
- Elena Cuoco: Website/Blog | GitHub
- Soumya D. Mohanty: Profile
- Frank Ohme: Profile
- Stephen Fairhurst: Profile
- Christoph Weniger: Profile
- Pau Amaro Seoane: Weisite
- Alex Nitz: GitHub
- Tyson Littenberg: GitHub
- Christopher Berry: Website/Blog | Twitter
- Will Meierjurgen Farr: Profile | GitHub | GW Data Analysis Summer School
- Daniel Williams: Website
- Michele Vallisneri: Website | GitHub
- Emanuele Berti: Blog
- Béatrice Bonga: Profile
- Collin Capano: Profile | GitHub
- Eve Chase: Github | GitLab
- Stephen R. Green: Profile | GitHub
- Marlin Benedikt Schäfer: Profile | GitHub
- Justin Ellis: Website/Blog | GitHub
- Colm Talbot: Profile | GitHub
- Isobel Marguarethe Romero-Shaw: Website | GitHub
- Asad Khan: Profile | GitHub
- Siddharth Soni: Profile | GitHub
- Gregory Ashton: Profile | GitHub
- Md Arif Shaikh: Profile
- Yan Wang: GitHub
- Xiyuan Li: Profile | GitHub
- 曹军威 Junwei Cao: Profile | ligo@tsinghua group
- 邵立晶 Lijing Shao: Profile
- 范锡龙 XiLong Fan: Blog
- 胡一鸣 YI-MING HU: Website
- 王一帆 Yifan Wang: Profile | GitHub | Atlas Directory
- 陈祖成 Zu-Cheng Chen: GitHub
- 吴仕超 Shichao Wu: GitHub
- 刘屿 Yu Liu: Profile/Blog | GitHub
- 杨舒成: GitHub
📚 Awesome Lecture / Tutorial
- https://www.caprameeting.org/resources/for-students
- https://www.caprameeting.org/resources/for-researchers
- https://www.ztf.caltech.edu/summer-school.html
Signal Processing
- IAIFI Summer School & Workshop 2022
- GWANW Student Workshop 2022
- spatialaudio
- Material related to the course “Swarm intelligence methods for statistical regression” delivered by Soumya D. Mohanty at the BigDat 2019 international winter school on big data, Cambridge university, UK. (SDMBIGDAT19): GitHub
NR
- NRPy+, BlackHoles@Home, SENRv2, and the NRPy+ Jupyter Tutorial: Python-Based Code Generation for Numerical Relativity… and Beyond! (nrpytutorial): GitHub | 1712.07658 | 2011.08878
GW
- An Online Course On Gravitational Waves
- “An introduction to LIGO–Virgo data analysis”, a nice blog post from Christopher Berry.
- Gravitational Wave Data Analysis School in China, 2018 (GWDACSchool): GitHub | GWDACSchoolSandBox GitHub
- GWOSC:
- GWOSC Learning Paths
- GW Open Data Workshops: WebSite (2018-now) | ThinkiFic
- GW discussion forum: forum
- A short introduction to working with gravitational wave data: GitHub
- RIFT tutorials: GitHub
- ICERM 2020 tutorial (jupyter notebook on methods; docker + ILE-GPU-Paper for details) this link, with associated slides to follow. The first tutorial can be opened directly in colab with this link.
- A tutorial in how to use LVK’s sensitivity data products. (SensitivityTutorial): GitLab
- PhD_lecture_tutorials: GitHub
- LSC Academic Advisory Committee (LAAC): WebsSite
- ESCAPE data science summer school 2021: School main page | Lectures portal | GitHub | YouTube live
- A collection of resources to act as an introduction to Bayesian inference: GitHub
- GstLAL small BBH-only analysis documents:
- Configuration files needed to launch a GstLAL online analysis for testing or onboarding purposes. These configuration files are mainly just used as an educational tool for people to get familiar with how to run GstLAL online analyses and are not used in any production environments. Files include: small BBH-only template bank, mass model, reference PSD, and FGMC pastro model files.
- LIGO-T2300144 (Public | Private)
- Gravitational Wave Data Analysis & Machine Learning (引力波暑期学校 Summer School on Gravitational Waves @Tianqin): Slide1 | Slide2 | Slide3 | GitHub | Kaggle
- Introductory materials for SURF (gw_detection_101_for_surf)
LISA
- LISA Data Challenge Workshop (July, 2022): Website
- Data generation: Page | Google Colab notebook
- Fast waveform generation: Page | GitHub
- Detection and parameter estimation of Galactic binaries: Page | Google Colab notebook
- MBHB parameter estimation: Page | Google Colab notebook
- LISA data tutorials based on LDC datasets and codes (lisatutos): GitHub
- Tutorial material for LISA Data Analysis Winter School in China (2017) (LDACSchool): GitHub | Mocked LISA Data Analysis (MLDC_2018) GitHub | GitHub | GitHub
- LDC pipeline: Home Page
- Tutorial on Machine Learning for Gravitational Wave Parameter Estimation of the single Galactic Binary: GitHub
- LISA Analysis Tools Workshop (LATW): GitHub
- LISA Data Generation and Analysis Workshop: Website
PTA
🐒 Awesome Repo / Code
It’s just a collection for my own….
Python
- Signal Processing Library - various MATLAB-like signal processing math: Doc | GitHub or repo
- A Genetic Programming platform for Python with TensorFlow for wicked-fast CPU and GPU support. Karoo gp: GitHub For an interesting read on scalar vs vector and CPU vs GPU performance with Karoo GP: https://arxiv.org/abs/1708.03157 or to learn how Karoo applied to supernova detection at LIGO: https://arxiv.org/abs/2002.04591.
Inference
- The Python ensemble sampling toolkit for affine-invariant MCMC (emcee): GitHub | 1202.3665
- Visualization of multidimensional posteriors; An illustrative representation of different projections of samples in high dimensional spaces (corner.py): GitHub | Doc
- Parallel tempering MCMC sampler package written in Python (PTMCMCSampler): GitHub
- Pythonic Bayesian inference and visualization for the MultiNest Nested Sampling Algorithm and PyCuba’s cubature algorithms. (PyMultiNest): GitHub
- The Markov-chain Monte Carlo Interactive Gallery (mcmc-demo): GitHub
- Gaussian Process Regression Demo (gp-demo): GitHub
- A simple, complete and reliable implementation capable to robustly perform Bayesian inference on arbitrary sets of data, with specific functionalities for multimessenger astrophysics (bajes): GitHub | 2102.00017
- A Python library for reliability engineering and survival analysis. It significantly extends the functionality of scipy.stats and also includes many specialist tools that are otherwise only available in proprietary software (reliability): Documentation |
- Machine learning assisted marginal likelihood (Bayesian evidence) estimation for Bayesian model selection (Harmonic): GitHub
- pocoMC is a Python implementation of the Preconditioned Monte Carlo method for accelerated Bayesian inference: 2207.05652 | GitHub
- pyobs A Python library to analyse data generated from (Monte Carlo) Markov chains. GitHub
- Statistical error analysis for Monte Carlo simulations (pyerrors): 2209.14371 | GitHub
- A Package for Bayesian inference of expensive likelihoods with Gaussian Processes (GPry): 2211.02045 | GitHub
- Normalizing-flow enhanced sampling package for probabilistic inference (FlowMC): 2211.06397 | 2105.12603 | GitHub
- Jim - A JAX-based gravitational-wave inference toolkit: 2302.05333 | GitHub
- Reduced Order Models in a scikit-learn approach. GitHub | Doc
- simple-pe: GitHub | PRD
Physics
- Lagrangian Neural Networks: 2003.04630 | Blog | GitHub
- Symbolic Deep Learning: 2006.11287 | Blog | GitHub
- Repository for the EinsteinPy core package (einsteinpy): GitHub | Website
- Mayawaves is an open-source python library for processing, studying, and exporting NR simulations performed using ETK and MAYA. 2309.00653
- A fast Lomb-Scargle periodogram. It’s nifty, and uses a NUFFT! GitHub
Gravitational Waves
Programming
- Script to search for GW signals emitted by binary systems of pulsars (binary_systems): GitHub
- Tools for the construction and characterization of hybrid GW models (HybridTools): GitHub | Doc
- A Python wrapper for tempo2 (libstempo): GitHub | Homepage
- Example using LAL codes to estimate effects of spin on LIGO detection rates (SpinSensitivity): GitHub
- A python package for GW astronomy (gravpy): GitHub
- A Python package to produce Burst Mock Data Challenge data sets for LIGO interferometers (Minke): GitHub | Doc
- Repository containing all the codes raltive to overlapping signals (Overlapping_signals): GitHub | (parameters_influence) GitHub | (Neutron_stars) GitHub
- Repository to hold summary pages made with the
pesummary
python package (public-pesummary-pages): GitHub - LIGO Data Analysis project implemented in C (ligo_data_analysis): GitHub
- Interactive exploration of GW posterior samples from GWTC-1 (GWposteriors): GitHub
- My own implementation of FGMC rates calculation methods for GW events (gw_rates): GitHub
- Computing Fisher Information matrices for GW parameter estimation (fisher): GitHub
- GWAstro
- PyCBC: GitHub | Doc | PyCBC tutorials GitHub | 1-OGC GitHub | 2-OGC GitHub | 3-OGC GitHub |
- A python package for Bayesian inference of GW data (gwin): GitHub | Doc
- Associated data release to the search for mergers of stellar-mass and sub-solar mass black holes (stellar-pbh-search): GitHub | 2007.03583
- Matched Filtering with PyCBC Inspiral by Duncan A. Brown (notebook)
- …
- coherent WaveBurst (cWB): Website
- The Low-Latency Pipeline: Doc
- CIERA-Northwestern
- COSMIC-PopSynth
- Gravity-Spy
- Set of plotting utilities focused on spectral and time series analysis (plottools): GitHub
- Python package for power spectral density modeling and estimation (pywer): GitHub
- Python Software for Studying Data from Gravitational-Wave Detectors (GWpy): GitHub | Doc | Paper
- A python interface to the Gravitational-Wave Open Data Center archive (gwosc): GitHub | Doc
- Pure-python implementation of
lal.LIGOTimeGPS
(ligotimegps): GitHub - Python utilities and extensions for the Omicron (C++) GW event trigger generator (pyomicron): GitHub | actual Omicron algorithm GWOLLUM
- Omicron - An algorithm to detect and characterize transient events in gravitational-wave detectors: 2007.11374 | GitHub | Document
- PESummary: GitHub
- Code to generate summary pages for Parameter Estimation results. Mirror of https://git.ligo.org/lscsoft/pesummary: GitHub
- GW190412 Summary Pages: GitHub
- A python package for gravitational wave analysis with the F-statistic (PyFstat): GitHub | 2101.10915 | LIGO-G2100073 | LIGO-P2100008 | G2102273/G2102272
- Python-based glitch characterization tool (PyChChoo):GitLab | Documentation | LIGO-P2100031 | 2104.07134
- Gravitational lensing software package (lenstronomy): GitHub | lenstronomy_extensions | 1893.09746 | 1504.07629
- A Python package for lensing of gravitational waves (lensingGW): GitLab | Documentation | 2006.12879
- Python package targeting ringdown time-domain analyses (pyRing): GitLab | GitLab | 1902.07527 | 1905.00869
- Modified GWBinning code package (MGWB): Bitbucket | 2010.07663
- A novel Fisher information package for gravitational-wave benchmarking (gwbench): GitLab | 2010.15202
- Blazingly fast EMRI waveforms, a part of the Black Hole Perturbation Toolkit (FastEMRIWaveforms): GitHub | Website | 2104.04582
- A generalized precession parameter to interpret gravitational-wave data (generalizedchip): GitHub | 2011.11948
- Code and data for producing a plot of the detection rate versus sensitive time-volume for use in presentations (lvkratesummaryplot): GitLab(private)
- Gravitational Wave dEtector desigN Toolkit (gwent): GitHub | 2010.02135
- Reproducing the Detection of GW150914: the first observation of gravitational waves from a binary black hole merger (gw150914-fig4b): GitHub | zenodo | IEEEDataPort | 2010.07244
- Bilby: a user-friendly Bayesian inference library. Doc | GitLab
- Bilby GWTC-1 plots: Website | 2006.00714
- A code for simulating gravitational waves and evaluating their detectability. (Riroriro): GitHub | zenodo | Documentation | 2103.06943
- An ability to construct quasi-equilibrium and eccentricity-reduced ID for BBH, BNS, and BHNS utilising the publicly available Kadath spectral solver library: Website | GitLab | 2103.09911
- A package to estimate cosmological parameters using gravitational-wave observations (gwcosmo): GitLab | tutorial | 2308.02281
- A pure CPU/GPU python code developed to infer population properties of noisy, heterogeneous, and incomplete observations (icarogw): GitHub | tutorial | P2300144 | 2305.17973
- A new python-based data analysis pipeline designed to search for long transient GW signals in ground-based interferometers data. (PySTAMPAS): LIGO-P2100278 | 2108.10588
- Python 3 post-processing tools for simulations performed with the Einstein Toolkit (kuibit): GitHub | 2104.06376
- This repository is a companion to the technical note A Thesaurus for Common Priors in Gravitational-Wave Astronomy. (effective-spin-priors): GitHub | 2104.09508
- stochastic: GitLab | Tutorial
- A Python based code for SGWB mapping from GW interferometer data. (PyStoch): GitLab
- GW background: Python-based library for gravitational-wave background searches (pygwb): GitLab | 2303.15696 | PyPi | P2300048
- IGWN Conda Distribution: a programme to manage and distribute software and environments used by the International Gravitational-Wave Observatory Network (IGWN) using the conda package manager, the conda-forge community, and the CernVM File System (CVMFS): WebSite
- Open Source Strong Gravitational Lensing (PyAutoLens): GitHub | 2106.01384
- python Gravitational Wave Interferometer NoiseCalculator (GWINC): GitLab | G2101196
- Gravitational Wave Universe Toolbox (GW-Toolbox): Website | Bitbucket | 2106.13662
- GWCelery is a simple and reliable package for annotating and orchestrating LIGO/Virgo alerts, built from widely used open source components. (GWCelery): GitHub | GitLab
- An interactive demonstration of matched filtering with some examples using real LIGO data and your computer’s audio. (MatchedFiltering): GitHub
- A library of tools for modelling and mitigating LIGO glitches with Probabilistic Principal Component Analysis (PPCA). (glitschen): GitLab | 2108.12044
- A Python-based reduced order quadrature building code (PyROQ): 2009.13812
- Gravitational wave template bank generation made easy. (diffbank): GitHub | 2202.09380
- A searchable repository for the creation and curation of gravitational-wave inference results (GWCloud): 2204.13267 | Site | GitLab | G2200936
- Simulation of detector networks with Fisher-matrix PE (GWFish): GitHub | 2205.02499
- CPU/GPU agnostic gravitational-wave population inference (GWPopulation): GitHub
- Asimov was developed to manage and automate the parameter estimation analyses used by the LIGO, Virgo, and KAGRA collaborations to analyse gravitational wave signals, but it aims to provide tools which can be used for other workflows.: 2207.01468 | GitLab
- Fisher Information Matrix package for GW cosmology, written in Python and based on automatic differentiation. (GWFAST): 2207.02771 | 2207.06910 | GitHub | Francesco Iacovelli et al 2022 ApJS 263 2 | Chapter
- Gravitational waves waveform models in pure Python language (WF4Py): GitHub
- GW detector inspiral range calculation tools: GitLab
- FIGARO - Fast Inference for GW Astronomy, Research & Observations: 2205.07252 | GitHub
- SIGWfast is a python code to compute the Scalar-Induced Gravitational Wave spectrum from a primordial scalar power spectrum that can be given in analytical or numerical form. : 2209.05296 | GitHub
- Metric bank generation for gravitational waves data analysis (mbank): GitHub | 2302.00436
- GWSim: A python package to create GW mock samples for different astrophysical populations and cosmological models of binary black holes: DCC | 2210.05724
- GWInferno: Gravitational-Wave Hierarchical Inference with NumPyro: 2210.12834 | GitLab | GitHub | DCC
- A package of functions to accompany Bilby for the analysis of gravitational wave signals from binary black holes. Specifically, these functions allow one to restrict the prior to a given precessional morphology. (bbh_spin_morphology_prior): 2301.10125 | GitLab
- Differentiable Gravitational Waveforms with JAX (Ripple): GitHub | 2302.05329 | G2300133
- A collection of notebooks for black hole perturbation theory calculations in GR and modified gravity. (ringdown-calculations): GitHub | 2301.10272
- gw_eccentricity: PyPI | LIGO-P2300026 | GitHub
- pySEOBNR: a software package for the next generation of effective-one-body multipolar waveform models: LIGO-P2300072 | 2303.18203
- gwisotropy: Software and data release for The directional isotropy of LIGO-Virgo binaries by M. Isi, W. M. Farr and V. Varma (2023).: GitHub | 2304.13254 | LIGO-P2300088
- ML4GW: Torch utilities for doing machine learning in gravitational wave physics: GitHub-ml4gw | PE | hermes | BBHNet | DeepClean
- Public repository of the Cosmic Linear Anisotropy Solving System (master for the most recent version of the standard code; classnet branch for acceleration with neutral networks; ExoCLASS branch for exotic energy injection; class_matter branch for FFTlog) (GW_CLASS): GitHub | 2305.01602
- A new Fisher-matrix, python based software that computes likelihood gradients to forecast parameter-estimation precision of arbitrary network of terrestrial gravitational wave detectors observing compact binary coalescences. (GWDALI): 2307.10154 | GitHub
- GravAD offers a cutting-edge approach to gravitational wave detection, leveraging Automatic Differentiation (AD), JAX, and Ripple for template generation via IMRPhenomD (GravAD): 2307.11891 | GitHub
- Gravitational waves lensing rate calculator (LeR): GitHub | Doc | G2301359
- PycWB: A User-friendly and Modular python wrapper for cWB. LIGO-G2301429 | GitLab | Doc
- X Pipeline is a burst gravitational-wave search algorithm. (X-Pypeline): GitHub | Doc
- GW polarization parameterizations and corresponding Jacobians. GitHub | Doc
- gw_sky: Project for making gravitational wave sky maps for images and animations.: GitHub
- Localization of gravitational-wave transients (ligo.skymap): Doc | GitHub | GitLab
- SEmi-Analytical approach for sky Localization of Gravitational Waves (SealGW): GitLab | 2110.01874
- Comparison between time-domain and frequency-domain Bayesian inferences for GW190521 (FD_TD_IMR): GitHub | 2401.13997
- A high-performance topological machine learning toolbox in Python (giotto-tda): GitHub | Doc
- GWtool is a set of simple tools for working with gravitational waves: GitHub | PyPI
- Example of GAMES (Gravitational-wave Amortized Metric Enhanced Sampler): GitHub | 2410.05190
- Multivariate PSD estimation using VI (sgvb_psd): GitHub | 2409.13224 | https://doi.org/10.1016/j.csda.2022.107596
LISA
- (lisatools): GitHub
- A noise and signal simulator for LISA-like GW observatories (Synthetic LISA): GitHub | Homepage
- Bayesian Data Augmentation for Waves and Noise (BayesDawn): GitHub | 1907.04747
- This is a C/C++ suite that allows kludge waveforms for extreme-mass-ratio inspirals (EMRIs) to be generated with shared settings and parameters. (EMRI Kludge Suite): GitHub
- Repository for code, notes related to LISA detection of CE-driven binary evolution (LISA-and-CE-Evolution): GitHub
- Prototype data analysis software for LISA analysis (LDASoft): GitHub
- lisacattools is a python module for interacting with simulated LISA source catalogs: Document | Google Colab Project
- The LISA Evolution and Gravitational Wave ORbit Kit (LEGWORK): 2111.08717 | GitHub | Document
- Codes to find and characterize massive black hole binary signals (LISA-Black-Hole): GitHub
- LISA_Sensitivity: GitHub | Zenodo
- LitePIG :a Lite Parameter Inference system for the Gravitational Waves in the millihertz band: GitHub
- Using GPU to compute LISA response to gravitational waves in millisecond scale. (fastlisaresponse): 2204.06633 | GitHub
- PyTDI is a Python package that provides a toolset to perform symbolical and numerical time-delay interferometry (TDI) calculations.: Zenodo
- LISA GW Response is a Python package that computes the generic time-domain instrument response to gravitational-waves, and produce a gravitational-wave file compatible with LISA Instrument and LISANode: Doc | Zenodo | GitLab
- Python package simulating instrumental noises, the propagation of laser beams, the measurements and the on-board processing. (LISA Instrument): GitLab
- Python package providing values sanctioned by the LISA Consortium for physical constants and mission parameters. (LISA Constants): GitLab
- LISA Orbits is a Python package which generates orbit files compatible with LISA Instrument, LISA GW Response, the LDC Software, and LISANode.: Doc | GitLab
- GPU-Accelerated Black Hole Binary Waveforms (bbhx): GitHub | Doc | 2005.01827 | 2111.01064
- GBGPU is a GPU-accelerated version of the FastGB waveform which has been developed by Neil Cornish, Tyson Littenberg, Travis Robson, and Stas Babak. : GitHub | GitHub
- GWSpace: a multi-mission science data simulator for space-based gravitational wave detection. 2309.15020
- bhpwave a new Python-based, open-source tool for generating the gravitational waveforms of stellar-mass compact objects undergoing quasi-circular inspirals into rotating massive black holes. GitHub | 2310.19706
- EMRI_MC: A GPU-based code for Bayesian inference of EMRI waveforms: 2311.17174 | Zenodo
- Combining gravitational wave harmonics for efficient evaluation of likelihood (cogwheel): GitHub
- Accelerated global Galactic binary search algorithm (LDC-GB): GitHub | Zenodo
- MBHB paramter estimation of LDC1-1 and LDC2a data set (from Strub, Stefan): Zenodo
Pulsar Timing Array (PTA)
- A repository of useful material related to the 2015 CSI PTA study program at the Aspen Center for Physics (aspen2015): GitHub
- PTA Algorithm Library (PAL): GitHub
- Bayesian-inference tools for PTA data (mc3pta): GitHub
- NANOGrav
- PINT is not TEMPO3 – New software for high-precision pulsar timing: GitHub
- ENTERPRISE (Enhanced Numerical Toolbox Enabling a Robust PulsaR Inference SuitE) is a pulsar timing analysis code, aimed at noise analysis, gravitational-wave searches, and timing model analysis (enterprise): GitHub | Doc
- A set of extension codes, utilities, and scripts for the enterprise PTA analysis framework (enterprise_extensions): GitHub
- …
- Repository of Analysis Algorithms for Pulsar Timing Residuals (RAAPTR): GitHub | 1406.5496/1506.01526/Journal of Physics: Conference Series 840, 012058 (2017)/1611.09440
- Ceffyl - a software package to rapidly and flexibly analyse Pulsar Timing Array data: GitHub
- RAAPTR (Repository of Analysis Algorithms for Pulsar Timing Residuals): GitHub
Machine Learning (ML)
- Search for GW transients with a CNN at VIRGO (cnn4gw): ipynb | GitHub
- A Deep CNN for low-latency supernova bursts detection (burst): GitHub
- Search for GW transients with a CNN (RGBgw/Master thesis): GitHub
- Analysis code for the research paper “Convolutional neural networks: a magic bullet for gravitational-wave detection?” (magic-bullet): GitHub | 1904.08693
- A surrogate modelling toolkit for python, using Gaussian process regression (Heron): 1903.09204 | Doc | Tutorial | GitHub | Thesis
- A feed-forward neural network for fast SNR calculation (NeuralSNR): GitHub | 2007.10350
- A ML model for generating gravitational waves (mlgw): 2011.01958 | GitHub
- DNN for GW posterior estimation (truebayes): 1811.05491 | 1909.05966 | GitHub
- Likelihood-Free Inference for Gravitational Waves (lfigw): 2008.03312 | GitHub | Project
- Merger-Ringdown Consistency: A New Test of Strong Gravity using Deep Learning (Merger_Ringdown_Test): GitHub | 2101.07817
- Nested Sampling with Aritificial Intelligence (Nessai): GitHub | Document | Blinder | 2102.11056 | Zenodo
- Gravitational-wave selection effects using neural-network classifiers (pdetclassifier): GitHub | 2007.06585
- Data release for the evaluation of different training strategies for deep learning gravitational wave search algorithms. (ml-training-strategies): GitHub | 2106.03741
- Swift Sky Localization of Gravitational Waves Using Deep Learning Seeded Importance Sampling: 2111.00833 | GitHub
- A Machine Learning Multi-Class classifier for LIGO–Virgo Public Alerts (GWSkyNet-Multi): 2111.04015 | GitHub
- A data analysis pipeline that leverages the Temporal Outlier Factor (TOF) method to find anomalies in LVC data. (UniMAP): 2111.09465 | GitHub
- MLGWSC-1 - Machine Learning Gravitational-Wave Search (Mock Data) Challenge: 2209.11146 | GitHub | zenodo
- AResGW: Gravitational Wave Detection using Deep Residual Networks (Virgo-AUTH): 2211.01401 | GitHub
- Machine Learning for Gravitational Waves from Binary Neutron Star mergers (mlgw_bns): 2210.15684 | GitHub
- Dingo: Deep inference for gravitational-wave observations: GitHub
- Peregrine: A simulation-based Inference (SBI) library designed to perform analysis on a wide class of gravitational wave signals. 2304.02035 | GitHub | GitHub
- CosmoFlow: Cosmological Inference using Gravitational Waves and Machine Learning. DCC | GitLab
- Aframe: An end-to-end ML pipeline for BBH detection: GitHub | DCC
- Training Neural Networks to improve the quality of the output of the GSTlal pipeline. DCC | GitLab
- NonSENS: Non-Stationary Estimation of Noise Subtraction: GitLab | 1911.09083
- Neural network model for gravitational wave sky localization (GW-SkyLocator): GitHub |
- swiftsky: Fast sky localization of gravitational waves using deep learning seeded importance sampling: GitHub | 2111.00833
- starccato is a Python library for training and using a GAN (Generative Adversarial Network) to generate synthetic GW signals from Stellar core collapse events. GitHub | 2309.15020 | Doc