Gravitational-Wave Astronomy

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3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data
Sep 30, 2026Gianluca Inguglia, Huw Haigh, Ulyana Dupletsa +1Gravitational-Wave Astronomy Anomaly Detection
Marietta Blau Institute for Particle Physics, Austrian Academy of Sciences, Vienna, Austria · Universit`a degli Studi di Urbino ‘Carlo Bo’, I-61029 Urbino, Italy · INFN, Sezione di Firenze, I-50019 Sesto Fiorentino, Firenze, Italy
Deep Learning Detection of Beyond-General-Relativity Deviations in Gravitational-Wave Signals: A Detection-Threshold Study with Real LIGO Noise
Sep 16, 2026Muhammad Adnan ShahzadGravitational-Wave Astronomy
Department of Computer Science and Software Engineering (CSSE), Concordia University, Montreal, QC, Canada
Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction
Sep 10, 2026Ann-Kristin Malz, Gregory Ashton, Nicolo ColomboWeighted Conformal Prediction Gravitational-Wave Astronomy
Department of Physics, Royal Holloway, University of London · School of Mathematical Sciences, University of Southampton · Department of Computer Science, Royal Holloway University of London
Introducing SINFONIA: Symplectic, slimplectic and Magnusian (Neural) Flows for Orbital Numerical Integration and Acceleration
Sep 3, 2026Lidia J. Gomes Da SilvaDynamical Systems Gravitational-Wave Astronomy
SISSA, Via Bonomea 265, 34136 Trieste, Italy and INFN Sezione di Trieste · INFN Sezione di Trieste · IFPU - Institute for Fundamental Physics of the Universe, Via Beirut 2, 34014 Trieste, Italy
MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models
Jul 31, 2026Boxiao Wang, Runxiang Wang, Kai Li +4Gravitational-Wave Astronomy Scientific ML
National Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Advanced Interdisciplinary Sciences, University of the Chinese Academy of Sciences, Beijing, China · School of Astronomy and Space Science, University of the Chinese Academy of Sciences, Beijing, China +2
Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms
Jul 27, 2026Michael Pürrer, Ashwin Girish, Lucy M. Thomas +2Neural Surrogate Modeling Gravitational-Wave Astronomy
Department of Physics, East Hall, University of Rhode Island, Kingston, RI 02881, USA · Institute for AI & Computational Research, Carothers Library, University of Rhode Island, Kingston, RI 02881, USA · 3TAPIR, California Institute of Technology, Pasadena, California 91125, USA +2
Transformers with Physics-Informed Encodings and Simulation-Based Inference for Robust Detection of Eccentric Binary Black Holes in Pulsar Timing Array Data
Jul 4, 2026Subhajit Dandapat, Alvin J. K. ChuaGravitational-Wave Astronomy Transformer
Department of Physics, National University of Singapore, 21 Lower Kent Ridge Road, Singapore 119077 · Department of Mathematics, National University of Singapore, Singapore 119076
AI-enabled gravitational-waves searches for binary neutron stars at optimal sensitivity
Jul 1, 2026Bhavya Gupta, Deep Chatterjee, William Benoit +7Gravitational-Wave Astronomy
1LIGO Laboratory, 185 Albany St, MIT, Cambridge, MA 02139, USA · Department of Physics, MIT, Cambridge, MA 02139, USA · School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455, USA
Binary Black Hole Parameter Estimation with Hybrid CNN-Transformer Neural Networks
Jun 11, 2026Panagiotis N. Sakellariou, Spiros V. Georgakopoulos, Sotiris Tasoulis +1Gravitational-Wave Astronomy Hybrid CNN-Transformer Architectures
Department of Mathematics, University of Thessaly, 3rd km. Old National Road Lamia-Athens, Lamia, 35100, Greece · Department of Computer Science and Biomedical Informatics, University of Thessaly, 35100, Greece
Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves
May 11, 2026Tousif Islam, Digvijay Wadekar, Tejaswi Venumadhav +4Surrogate Modeling Gravitational-Wave Astronomy
Kavli Institute for Theoretical Physics, University of California Santa Barbara, Kohn Hall, Lagoon Rd, Santa Barbara, CA 93106, USA. · Center for Gravitational Physics, University of Texas at Austin, Austin, TX 78712, USA. · Department of Physics, University of California at Santa Barbara, Santa Barbara, CA 93106, USA. +5
gwBenchmarks: Stress-Testing LLM Agents on High-Precision Gravitational Wave Astronomy
May 11, 2026Tousif Islam, Digvijay Wadekar, Zihan ZhouGravitational-Wave Astronomy AI Coding Agents
Kavli Institute for Theoretical Physics, University of California Santa Barbara, Kohn Hall, Lagoon Rd, Santa Barbara, CA 93106 · Center for Gravitational Physics, University of Texas at Austin, Austin, TX 78712, USA · Department of Physics, Princeton University, Princeton, NJ 08540, USA
An agentic framework for gravitational-wave counterpart association in the multi-messenger era
May 11, 2026Yiming Dong, Yacheng Kang, Junjie Zhao +3AI Agents for Scientific Discovery Gravitational-Wave Astronomy
Department of Astronomy, School of Physics, Peking University, No. 5 Yiheyuan Road, Beijing, 100871, Beijing, China. · Kavli Institute for Astronomy and Astrophysics, Peking University, No. 5 Yiheyuan Road, Beijing, 100871, Beijing, China. · Institute for Gravitational Wave Astronomy, Henan Academy of Sciences, No. 228 Chongshili Road, Zhengzhou, 450046, Henan, China. +2
Testing General Relativity Through Gravitational Wave Classification: A Convolutional Neural Network Framework
May 4, 2026Lavinia Heisenberg, Shayan Hemmatyar, Hector Villarrubia-RojoGravitational-Wave Astronomy Binary Classification
Institute for Theoretical Physics, Heidelberg University, Philosophenweg 16, 69120 Heidelberg, Germany · Departamento de F´ısica Te´orica and IPARCOS, Facultad de Ciencias F´ısicas, Universidad Complutense de Madrid, Plaza de las Ciencias 1, 28040 Madrid, Spain
When Attention Collapses: Residual Evidence Modeling for Compositional Inference
May 4, 2026Niklas HoubaGravitational-Wave Astronomy Self-Attention
Institute for Particle Physics and Astrophysics ETH Zurich
Flexible Gravitational-Wave Parameter Estimation with Transformers
Dec 2, 2025Annalena Kofler, Maximilian Dax, Stephen R. Green +6Transformer Inference Gravitational-Wave Astronomy
Max Planck Institute for Intelligent Systems, Max-Planck-Ring 4, 72076 Tübingen, Germany · ELLIS Institute Tübingen, Maria-von-Linden-Straße 2, 72076 Tübingen, Germany · Tübingen AI Center, Maria-von-Linden-Straße 1, 72076 Tübingen, Germany +4

Sep 30, 2026, gr-qcJ/K move · Enter open · S save

MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data

Gianluca Inguglia, Huw Haigh, Ulyana Dupletsa, Alessandro Longo

Marietta Blau Institute for Particle Physics, Austrian Academy of Sciences, Vienna, Austria · Universit`a degli Studi di Urbino ‘Carlo Bo’, I-61029 Urbino, Italy · INFN, Sezione di Firenze, I-50019 Sesto Fiorentino, Firenze, Italy

Gravitational-Wave Astronomy Anomaly Detection

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We present the results of \textbf{MADGRAV}, a deep-learning-based search for high-mass compact binary coalescences, applied to the data collected by the LIGO interferometers during the third observing run and during the first and second part of the fourth observing run. The \textbf{MADGRAV} pipeline consists of a series of sequential convolutional neural networks that perform anomaly detection, glitch classification, coherence testing, and signal ranking. Data from the Hanford and Livingston LIGO detectors are studied (both individually and in coherence) by way of 1 second Q-transform windows. Of the candidates that survive every stage of the pipeline, 48 reach the significance threshold, and we report 47 gravitational wave detections characterised by a false alarm rate below

1\,{\rm yr}^{-1}

with a probability of astrophysical origin

p_{\rm astro}>0.9

. Of the 47 detections, 44 are shared with the minimally modelled coherent WaveBurst search. The observed total source-frame masses, extracted from official gravitational wave transient catalogues, are in the

14-236 M_{\odot}

range with a median of

69 M_{\odot}

, and a median SNR of 16. We note that the recovered fraction of confident detections rises with mass: for LIGO detectors network SNR

>10

the pipeline recovers

8.1\%

of confident catalog events below

30 M_{\odot}

39.8\%

between

30

and

100 M_{\odot}

, and

53.3\%

above

100 M_{\odot}

, corresponding to

33.3\%

45.5\%

and

53.3\%

of the events detected by coherent WaveBurst in the same bins. These results suggest that anomaly detection pipelines can serve as an independent detection channel complementary to matched filtering in the high-mass high-SNR regime.

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