PreprintCC BY 4.0arXiv
Opening the Black Box: What Neural Networks Learn from Pulsar Timing Array Data
Abstract
In recent years, simulation-based inference (SBI) methods have been proposed to address several data-analysis challenges faced by existing and planned gravitational-wave experiments. For example, SBI classification has recently been shown to significantly improve the prospects for detecting anisotropies in pulsar timing array (PTA) data. In this work, we use a simple toy model of a PTA to provide a more pedagogical explanation of how, and under which circumstances, SBI-based detection can improve on classical detection statistics for gravitational-wave background anisotropies.
Related
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- Hierarchical Inference of the Supermassive Black Hole Binary Merger Rates from Joint Searches using Pulsar Timing Arrays
- Red noise and evolving signals: a complete frequentist approach to supermassive black hole binary searches with pulsar timing arrays
BibTeX
@misc{alvey2026opening,
title = {{Opening the Black Box: What Neural Networks Learn from Pulsar Timing Array Data}},
author = {James Alvey and Andrea Mitridate and Mauro Pieroni and Joseph D. Romano},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.12308},
eprint = {2610.12308},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.12308},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Opening the Black Box: What Neural Networks Learn from Pulsar Timing Array Data
AU - James Alvey
AU - Andrea Mitridate
AU - Mauro Pieroni
AU - Joseph D. Romano
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2610.12308
UR - https://arxiv.org/abs/2610.12308
AB - In recent years, simulation-based inference (SBI) methods have been proposed to address several data-analysis challenges faced by existing and planned gravitational-wave experiments. For example, SBI classification has recently been shown to significantly improve the prospects for detecting anisotropies in pulsar timing array (PTA) data. In this work, we use a simple toy model of a PTA to provide a more pedagogical explanation of how, and under which circumstances, SBI-based detection can improve on classical detection statistics for gravitational-wave background anisotropies.
ER -