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Record W2792749774 · doi:10.1103/physrevd.98.083014

Detection and characterization of spin-orbit resonances in the advanced gravitational wave detectors era

2018· article· en· W2792749774 on OpenAlexafffund
Chaitanya Afle, Anuradha Gupta, B. U. Gadre, P. Kumar, Nick Demos, Geoffrey Lovelace, Han Gil Choi, Hyung Mok Lee, S. Mitra, Michael Boyle, Daniel A. Hemberger, Harald Pfeiffer, Mark Scheel, Béla Szilágyi

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsCanadian Institute for Advanced ResearchCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersCalifornia State University, FullertonCanada Research ChairsNatural Sciences and Engineering Research Council of CanadaUniversity Grants CommissionPittsburgh FoundationDepartment of Science and Technology, Ministry of Science and Technology, IndiaKorea Institute of Science and Technology InformationSir Ratan Tata Trust and Navajbai Ratan Tata TrustCharles E. Kaufman FoundationScience and Engineering Research BoardCanadian Institute for Advanced ResearchCalifornia Institute of TechnologyUniversity of Wisconsin-MilwaukeeCalifornia State UniversityNational Niemann-Pick Disease FoundationSherman Fairchild FoundationNational Science Foundation
KeywordsPhysicsSpinsSpin (aerodynamics)Gravitational waveAngular momentumOrbit (dynamics)ChirpWaveformAstrophysicsComputational physicsQuantum mechanicsCondensed matter physics

Abstract

fetched live from OpenAlex

Spin-orbit resonances have important astrophysical implications as the evolution and subsequent coalescence of supermassive black hole binaries in one of these configurations may lead to low recoil velocity of merger remnants. It has also been shown that black hole spins in comparable mass stellar-mass black hole binaries could preferentially lie in a resonant plane when their gravitational waves (GWs) enter the advanced LIGO frequency band [1]. Therefore, it is highly desirable to investigate the possibility of detection and subsequent characterization of such GW sources in the advanced detector era, which can, in turn, improve our perception of their high mass counterparts. The current detection pipelines involve only nonprecessing templates for compact binary searches whereas parameter estimation pipelines can afford to use approximate precessing templates. In this paper, we test the performance of these templates in detection and characterization of spin-orbit resonant binaries. We use fully precessing time-domain SEOBNRv3 waveforms as well as four numerical relativity (NR) waveforms to model GWs from spin-orbit resonant binaries and filter them through IMRPhenomD, SEOBNRv4 and IMRPhenomPv2 approximants. We find that the nonprecessing approximants IMRPhenomD and SEOBNRv4 recover only $\ensuremath{\sim}70%$ of injections with fitting factor (FF) higher than 0.97 (or 90% of injections with $\mathrm{FF}>0.9$). This loss in signal-to-noise ratio is mainly due to the missing physics in these approximants in terms of precession and nonquadrupole modes. However, if we use a new statistic, i.e., maximizing the matched filter output over the sky-location parameters as well, the precessing approximant IMRPhenomPv2 performs magnificently better than their nonprecessing counterparts with recovering 99% of the injections with FFs higher than 0.97. Interestingly, injections with $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=180\ifmmode^\circ\else\textdegree\fi{}$ have higher FFs ($\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}$ is the angle between the components of the black hole spins in the plane orthogonal to the orbital angular momentum) as compared to their $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=0\ifmmode^\circ\else\textdegree\fi{}$ and generic counterparts. This is because $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=180\ifmmode^\circ\else\textdegree\fi{}$ binaries are not as strongly precessing as $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=0\ifmmode^\circ\else\textdegree\fi{}$ and generic binaries. This implies that we will have a slight observation bias towards $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=180\ifmmode^\circ\else\textdegree\fi{}$ and away from $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=0\ifmmode^\circ\else\textdegree\fi{}$ resonant binaries while using nonprecessing templates for searches. Moreover, all template approximants are able to recover most of the injected NR waveforms with FFs $>0.95$. For all the injections including NR, the systematic error in estimating chirp mass remains below $<10%$ with minimum error for $\mathrm{\ensuremath{\Delta}}\ensuremath{\phi}=180\ifmmode^\circ\else\textdegree\fi{}$ resonant binaries. The symmetric mass-ratio can be estimated with errors below 15%. The effective spin parameter ${\ensuremath{\chi}}_{\mathrm{eff}}$ is measured with maximum absolute error of 0.13. The in-plane spin parameter ${\ensuremath{\chi}}_{p}$ is mostly underestimated indicating that a precessing signal will be recovered as a relatively less precessing signal. Based on our findings, we conclude that we not only need improvements in waveform models towards precession and nonquadrupole modes but also better search strategies for precessing GW signals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.435
Teacher spread0.420 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2018
Admission routes2
Has abstractyes

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