A Fast and Scalable Transformer Pipeline for Binary Black Hole Detection

arXiv:2609.00339 · gr-qc, astro-ph.GA · Submitted 2026-08-31 · Read on arXiv

gr-qc, astro-ph.GA

Submitted: 2026-08-31

Updated: 2026-09-23

Code: https://github.com/chayanchatterjee/castor

Terminology

• Transformer — 32× in this paper · explained in 2 episodes
• Foundation Model — 10× in this paper · explained in 3 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Adaptation — 5× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Attention Mechanism — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• International Conference on Machine Learning — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Signal-to-noise ratio (SNR) — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Unbounded Softmax Replacement — 1× in this paper
• Verification — 1× in this paper · explained in 2 episodes

Sources

• GWTC-4.0: Updating the Gravitational-Wave Transient Catalog with Observations from the First Part of the Fourth LIGO-Virgo-KAGRA Observing Run
• GWTC-4.0: Methods for Identifying and Characterizing Gravitational-wave Transients
• GWTC-5.0: Observations from the Second Part of the Fourth LIGO-Virgo-KAGRA Observing Run and Updates to the Gravitational-Wave Transient Catalog
• Cosmic Explorer: The U.S. Contribution to Gravitational-Wave Astronomy beyond LIGO
• The GstLAL Search Analysis Methods for Compact Binary Mergers in Advanced LIGO's Second and Advanced Virgo's First Observing Runs
• LIGO Detector Characterization in the Second and Third Parts of the Fourth Observing Run
• Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit
• Scalable matched-filtering pipeline for gravitational-wave searches of compact binary mergers
• The Sound of Noise: Leveraging the Inductive Bias of Pre-trained Audio Transformers for Glitch Identification in LIGO
• Applications of machine learning in gravitational wave research with current interferometric detectors
• A machine-learning pipeline for real-time detection of gravitational waves from compact binary coalescences
• AI-enabled gravitational-waves searches for binary neutron stars at optimal sensitivity
• Binary Neutron Star Merger Search Pipeline Powered by Deep Learning
• New Gravitational Wave Discoveries Enabled by Machine Learning
• Enhancing gravitational-wave detection: a machine learning pipeline combination approach with robust uncertainty quantification
• Pre-trained Audio Transformer as a Foundational AI Tool for Gravitational Waves
• Robust Speech Recognition via Large-Scale Weak Supervision
• DoRA: Weight-Decomposed Low-Rank Adaptation

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