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Record W4414383416 · doi:10.1093/mnras/staf1583

Thermal X-ray signatures in late-stage unequal-mass massive black hole binary mergers

2025· article· en· W4414383416 on OpenAlexaff
Luke Major Krauth, Jordy Davelaar, Zoltán Haiman, John Ryan Westernacher-Schneider, Jonathan Zrake, Andrew MacFadyen

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsInstitute of Particle Physics
FundersNuclear Safety and Security CommissionAmes Research CenterNational Aeronautics and Space AdministrationSpace Telescope Science InstituteNational Science Foundation
KeywordsGravitational waveBinary numberGalaxyBlack hole (networking)ThermalRadiative transferSignature (topology)GravitationLuminosity

Abstract

fetched live from OpenAlex

ABSTRACT The multimessenger combination of gravitational waves (GWs) from merging massive black hole binaries (MBHBs) and the electromagnetic (EM) counterpart from the surrounding circumbinary disc (CBD) will open avenues to new scientific pursuits. In order to realize this science, we need to correctly localize the host galaxy of the merging MBHB. Multiwavelength, time-dependent EM signatures can greatly facilitate the identification of the unique EM counterpart among many sources in LISA’s localization volume. To this end, we studied merging unequal-mass MBHBs embedded in a CBD using high-resolution 2D simulations, with a $\Gamma$-law equation of state, incorporating viscous heating, shock heating, and radiative cooling. We simulate each binary starting from before it decouples from the CBD until just after the merger. We compute EM signatures and identify distinct features before, during, and after the merger. We corroborate previous findings of a several orders of magnitude drop in the thermal X-ray luminosity near the time of merger, but with delayed timing compared to an equal-mass system. The source remains X-ray dark for hours post-merger. Our main results are a potential new signature of a sharp spike in the thermal X-ray emission just before the tell-tale steep drop occurs. This feature may further help to identify EM counterparts of LISA’s unequal MBHBs before merger without the need for extensive pre-merger monitoring. Additionally, we find a role-reversal in which the primary out-accretes the secondary during late inspiral, which may diminish signatures originating from Doppler modulation.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Simulation or modelinglow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Simulation or modelinglow
models agreeAgreement compares identical category sets and study designs across arms.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Labeled directly by 2 models reading the full record.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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