Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation

TL;DR

TIER is a machine learning framework that enhances gravitational wave detection sensitivity by utilizing extended strain data, leading to significant improvements in detection volume and candidate significance, especially for high-mass systems.

Contribution

This work introduces TIER, a novel ML-based method that leverages extended strain data to improve gravitational wave search sensitivity without requiring new data or costly simulations.

Findings

Up to 20% increase in sensitive volume time in LIGO-Virgo-Kagra O3 data.

Enhanced detection significance for near-threshold candidates.

Improved sensitivity particularly in high-mass and intermediate-mass black hole regions.

Abstract

We introduce a machine learning (ML) framework called $\texttt{TIER}$ for improving the sensitivity of gravitational wave search pipelines. Typically, search pipelines only use a small region of strain data in the vicinity of a candidate signal to construct the detection statistic. However, extended strain data ($\sim 10$ s) in the candidate's vicinity can also carry valuable complementary information. We show that this information can be efficiently captured by ML classifier models trained on sparse summary representation/features of the extended data. Our framework is easy to train and can be used with already existing candidates from any search pipeline, and without requiring expensive injection campaigns. Furthermore, the output of our model can be easily integrated into the detection statistic of a search pipeline. Using $\texttt{TIER}$ on triggers from the $\texttt{IAS-HM}$ pipeline, we find up to $\sim 20\%$ improvement in sensitive volume time in LIGO-Virgo-Kagra O3 data, with improvements concentrated in regions of high masses and unequal mass ratios. Applying our framework increases the significance of several near-threshold gravitational-wave candidates, especially in the pair-instability mass gap and intermediate-mass black hole (IMBH) ranges.