Opening the Black Box: What Neural Networks Learn from Pulsar Timing Array Data

Name: Opening the Black Box: What Neural Networks Learn from Pulsar Timing Array Data
Uploaded: 2026-10-14T08:14:51.091315+00:00
Duration: 169 s
Description: The work uses a simple pulsar timing array (PTA) toy model to explain how simulation-based inference (SBI) using neural networks can improve detection of gravitational-wave background anisotropies. It compares different statistics, showing that while linear networks learn nothing from raw data, trained classifiers can approximate the optimal Bayesian statistic efficiently.

The work uses a simple pulsar timing array (PTA) toy model to explain how simulation-based inference (SBI) using neural networks can improve detection of gravitational-wave background anisotropies. It compares different statistics, showing that while linear networks learn nothing from raw data, trained classifiers can approximate the optimal Bayesian statistic efficiently.

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