Searching for precessing binary systems with mode-by-mode filtering and marginalization

Fuente: arXiv
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Autores principales: Zhou, Zihan, Wadekar, Digvijay, Roulet, Javier, Ivashtenko, Oryna, Venumadhav, Tejaswi, Islam, Tousif, Mehta, Ajit Kumar, Mushkin, Jonathan, Cheung, Mark Ho-Yeuk, Zackay, Barak, Zaldarriaga, Matias
Formato: Preprint
Publicado: 2026
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author Zhou, Zihan
Wadekar, Digvijay
Roulet, Javier
Ivashtenko, Oryna
Venumadhav, Tejaswi
Islam, Tousif
Mehta, Ajit Kumar
Mushkin, Jonathan
Cheung, Mark Ho-Yeuk
Zackay, Barak
Zaldarriaga, Matias
author_facet Zhou, Zihan
Wadekar, Digvijay
Roulet, Javier
Ivashtenko, Oryna
Venumadhav, Tejaswi
Islam, Tousif
Mehta, Ajit Kumar
Mushkin, Jonathan
Cheung, Mark Ho-Yeuk
Zackay, Barak
Zaldarriaga, Matias
contents Nearly all previous binary black hole searches in LIGO--Virgo--KAGRA (LVK) gravitational wave data have assumed that the component spins are aligned with the orbital angular momentum, thereby neglecting spin-precession effects in the waveform, which can lead to potentially missing interesting signals. Precessing searches are challenging, because the extra degrees of freedom due to misaligned spins lead to: $(i)$ a much larger number of templates compared to the aligned-spin configurations, $(ii)$ an increased rate of background triggers. To address this, we develop novel precessing signal template banks using mode-by-mode filtering and marginalization methods. We use the precession harmonic decomposition from Fairhurst et al. (2019) and filter each precessing harmonic separately with the data. We then marginalize over the SNRs from different harmonics in our detection statistic. We also use machine learning methods to improve our search efficiency: $(i)$ we use singular value decomposition together with random forest regressor to reduce redundancy in the dominant precessing-harmonic templates; $(ii)$ we use normalizing flows to generate optimal prior samples for harmonic SNRs for the marginalized statistic. We show that marginalizing (instead of maximizing) over the harmonic mode SNRs increases the search sensitive volume by $\sim 10\%$. Results from searching in LVK data using this framework will be reported in a companion paper.
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id arxiv_https___arxiv_org_abs_2603_05784
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Searching for precessing binary systems with mode-by-mode filtering and marginalization
Zhou, Zihan
Wadekar, Digvijay
Roulet, Javier
Ivashtenko, Oryna
Venumadhav, Tejaswi
Islam, Tousif
Mehta, Ajit Kumar
Mushkin, Jonathan
Cheung, Mark Ho-Yeuk
Zackay, Barak
Zaldarriaga, Matias
General Relativity and Quantum Cosmology
Cosmology and Nongalactic Astrophysics
High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
Nearly all previous binary black hole searches in LIGO--Virgo--KAGRA (LVK) gravitational wave data have assumed that the component spins are aligned with the orbital angular momentum, thereby neglecting spin-precession effects in the waveform, which can lead to potentially missing interesting signals. Precessing searches are challenging, because the extra degrees of freedom due to misaligned spins lead to: $(i)$ a much larger number of templates compared to the aligned-spin configurations, $(ii)$ an increased rate of background triggers. To address this, we develop novel precessing signal template banks using mode-by-mode filtering and marginalization methods. We use the precession harmonic decomposition from Fairhurst et al. (2019) and filter each precessing harmonic separately with the data. We then marginalize over the SNRs from different harmonics in our detection statistic. We also use machine learning methods to improve our search efficiency: $(i)$ we use singular value decomposition together with random forest regressor to reduce redundancy in the dominant precessing-harmonic templates; $(ii)$ we use normalizing flows to generate optimal prior samples for harmonic SNRs for the marginalized statistic. We show that marginalizing (instead of maximizing) over the harmonic mode SNRs increases the search sensitive volume by $\sim 10\%$. Results from searching in LVK data using this framework will be reported in a companion paper.
title Searching for precessing binary systems with mode-by-mode filtering and marginalization
topic General Relativity and Quantum Cosmology
Cosmology and Nongalactic Astrophysics
High Energy Astrophysical Phenomena
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2603.05784