Phenomenological model for the gravitational-wave signal from precessing binary black holes with two-spin effects
Bibliographic record
Abstract
The properties of compact binaries, such as masses and spins, are imprinted in the gravitational waves (GWs) they emit and can be measured using parametrized waveform models. Accurately and efficiently describing the complicated precessional dynamics of the various angular momenta of the system in these waveform models is the object of active investigation. One of the key models extensively used in the analysis of LIGO and Virgo data is the single-precessing-spin waveform model IMRPhenomPv2. In this article we present a new model IMRPhenomPv3, which includes the effects of two independent spins in the precession dynamics. Whereas IMRPhenomPv2 utilizes a single-spin frequency-dependent post-Newtonian rotation to describe precession effects, the improved model, IMRPhenomPv3, employs a double-spin rotation that is based on recent developments in the description of precessional dynamics. Besides double-spin precession, the improved model benefits from a more accurate description of precessional effects. We validate our new model against a large set of precessing numerical-relativity simulations. We find that IMRPhenomPv3 has better agreement with the inspiral portion of precessing binary-black-hole simulations and is more robust across a larger region of the parameter space than IMRPhenomPv2. As a first application we analyze the gravitational-wave event GW151226 with an efficient frequency-domain waveform model that describes two-spin precession. Within statistical uncertainty our results are consistent with published results. IMRPhenomPv3 will allow studies of the measurability of individual spins of binary black holes using GWs and can be used as a foundation upon which to build further improvements, such as modeling precession through merger, extending to higher multipoles, and including tidal effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".