{"title":"Hierarchical searches for subsolar-mass binaries and the third-generation gravitational wave detector era","authors":"Kanchan Soni, Alexander H. Nitz","doi":"arxiv-2409.11317","DOIUrl":null,"url":null,"abstract":"The detection of gravitational waves (GWs) from coalescing compact binaries\nhas become routine with ground-based detectors like LIGO and Virgo. However,\nbeyond standard sources such as binary black holes and neutron stars and\nneutron star black holes, no exotic sources revealing new physics have been\ndiscovered. Detecting ultra-compact objects, such as subsolar mass (SSM)\ncompact objects, offers a promising opportunity to explore diverse\nastrophysical populations. However, searching for these objects using standard\nmatched-filtering techniques is computationally intensive due to the dense\nparameter space involved. This increasing computational demand not only\nchallenges current search methodologies but also poses significant obstacles\nfor third-generation (3G) ground-based GW detectors. In the 3G era, signals may\nlast tens of minutes, and detection rates could reach one per minute, requiring\nefficient search strategies to manage the computational load of long-duration\nsignals. In this paper, we demonstrate a hierarchical search strategy designed\nto address the challenges of searching for long-duration signals, such as those\nfrom SSM compact binaries, and the anticipated issues with 3G detectors. We\nshow that by adopting optimization techniques in a two-stage hierarchical\napproach, we can efficiently search for the SSM compact object in the current\nLIGO detectors. Our preliminary results show that conducting matched filtering\nat a lower frequency of 35 Hz improves the signal-to-noise ratio by 6% and\nenhances the detection volume by 10-20%, compared to the standard two-detector\nPyCBC search. This improvement is achieved while reducing computational costs\nby a factor of 2.5.","PeriodicalId":501041,"journal":{"name":"arXiv - PHYS - General Relativity and Quantum Cosmology","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - General Relativity and Quantum Cosmology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The detection of gravitational waves (GWs) from coalescing compact binaries
has become routine with ground-based detectors like LIGO and Virgo. However,
beyond standard sources such as binary black holes and neutron stars and
neutron star black holes, no exotic sources revealing new physics have been
discovered. Detecting ultra-compact objects, such as subsolar mass (SSM)
compact objects, offers a promising opportunity to explore diverse
astrophysical populations. However, searching for these objects using standard
matched-filtering techniques is computationally intensive due to the dense
parameter space involved. This increasing computational demand not only
challenges current search methodologies but also poses significant obstacles
for third-generation (3G) ground-based GW detectors. In the 3G era, signals may
last tens of minutes, and detection rates could reach one per minute, requiring
efficient search strategies to manage the computational load of long-duration
signals. In this paper, we demonstrate a hierarchical search strategy designed
to address the challenges of searching for long-duration signals, such as those
from SSM compact binaries, and the anticipated issues with 3G detectors. We
show that by adopting optimization techniques in a two-stage hierarchical
approach, we can efficiently search for the SSM compact object in the current
LIGO detectors. Our preliminary results show that conducting matched filtering
at a lower frequency of 35 Hz improves the signal-to-noise ratio by 6% and
enhances the detection volume by 10-20%, compared to the standard two-detector
PyCBC search. This improvement is achieved while reducing computational costs
by a factor of 2.5.