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Binary Black Hole Population Properties Inferred from the First and Second Observing Runs of Advanced LIGO and Advanced Virgo

2019· article· en· 747 citations· W2972955928 on OpenAlex· 10.3847/2041-8213/ab3800

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: ObservationalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.970
Threshold uncertainty score
0.277
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

Machine scores (provisional)

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

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.

Opus teacher head0.010
GPT teacher head0.251
Teacher spread
0.241 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Abstract We present results on the mass, spin, and redshift distributions with phenomenological population models using the 10 binary black hole (BBH) mergers detected in the first and second observing runs completed by Advanced LIGO and Advanced Virgo. We constrain properties of the BBH mass spectrum using models with a range of parameterizations of the BBH mass and spin distributions. We find that the mass distribution of the more massive BH in such binaries is well approximated by models with no more than 1% of BHs more massive than 45 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> </mml:math> and a power-law index of α = <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msubsup> <mml:mrow> <mml:mn>1.3</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1.7</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>1.4</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> (90% credibility). We also show that BBHs are unlikely to be composed of BHs with large spins aligned to the orbital angular momentum. Modeling the evolution of the BBH merger rate with redshift, we show that it is flat or increasing with redshift with 93% probability. Marginalizing over uncertainties in the BBH population, we find robust estimates of the BBH merger rate density of R = <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msubsup> <mml:mrow> <mml:mn>53.2</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>28.2</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>55.8</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> Gpc −3 yr −1 (90% credibility). As the BBH catalog grows in future observing runs, we expect that uncertainties in the population model parameters will shrink, potentially providing insights into the formation of BHs via supernovae, binary interactions of massive stars, stellar cluster dynamics, and the formation history of BHs across cosmic time.

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.

The record

Venue
The Astrophysical Journal Letters
Topic
Pulsars and Gravitational Waves Research
Field
Physics and Astronomy
Canadian institutions
Université de MontréalPolytechnique MontréalCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Funders
Division of Human Resource DevelopmentAustralian Research CouncilScience and Technology Facilities CouncilIstituto Nazionale di Fisica NucleareLeverhulme TrustScottish Funding CouncilRussian Science FoundationMinistry of Education, IndiaNational Research Foundation of KoreaEngineering and Physical Sciences Research CouncilHungarian Scientific Research FundGeneralitat ValencianaCouncil of Scientific and Industrial Research, IndiaCentre National de la Recherche ScientifiqueIndustry CanadaKavli FoundationNational Natural Science Foundation of ChinaNational Research, Development and Innovation OfficeAgencia Estatal de InvestigaciónSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungGovern de les Illes BalearsNederlandse Organisatie voor Wetenschappelijk OnderzoekNational Research FoundationNemzeti Kutatási Fejlesztési és Innovációs HivatalAbdus Salam International Centre for Theoretical PhysicsEuropean CommissionRussian Foundation for Basic ResearchEuropean Regional Development FundScottish Universities Physics AllianceICTP South American Institute for Fundamental ResearchCanadian Institute for Advanced ResearchMinistero dello Sviluppo EconomicoInstitut des Origines de LyonScience and Engineering Research BoardNational Science FoundationRoyal Society
Keywords
LIGOBinary black holeRedshiftPopulationSpinsBinary numberMass distribution
Has abstract in OpenAlex
yes