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#gravitational-waves

4 curated events
papersTODAY 04:00 UTC

Autoencoder Method Targets Quasinormal Mode Parameter Estimation in Ringdown Signals

A new arXiv preprint describes using an autoencoder to estimate the parameters of ringdown gravitational waves, which are modeled as combinations of quasinormal modes carrying information about the remnant Kerr black hole. The work focuses on reliably extracting multiple quasinormal modes, a task that is difficult with conventional fitting methods. The paper appears in the cross-listed machine learning category.

gravitational-waves/autoencoders/physics/research
papersTODAY 04:00 UTC

Symbolic regression estimates neutron-star radii from gravitational-wave data alone

A new arXiv preprint explores using symbolic regression to infer neutron-star radii from gravitational-wave signals emitted during binary neutron-star inspirals. Such signals directly constrain component masses and tidal deformabilities, but radii are normally obtained through electromagnetic observations. The approach aims to support multi-messenger studies by deriving radius estimates without relying on electromagnetic data.

symbolic-regression/gravitational-waves/astrophysics/arxiv
papersTODAY 04:00 UTC

Survey Reviews Deep Learning Architectures for Gravitational-Wave Denoising

A new arXiv survey examines deep learning methods for cleaning noise from gravitational-wave detector data, arguing that techniques must cope with the full range of spinning and precessing binary systems. The paper notes that matched filtering remains the established approach but comes with trade-offs that learned models aim to address. Reconstructed waveforms feed into parameter estimation, tests of general relativity and population studies.

gravitational-waves/deep-learning/signal-processing/survey
papersTODAY 04:00 UTC

Study compares Claude Code and Codex on gravitational-wave pipeline task

A preprint describes a methodological comparison of two coding agents, Anthropic's Claude Code and OpenAI's Codex, each autonomously running the same matched-filter pipeline on simulated Einstein Telescope data. The authors frame it as an early look at how agentic AI performs on a real gravitational-wave analysis workflow rather than as a model benchmark.

agents/research/benchmarks/gravitational-waves