Eccentric, nonspinning, inspiral, Gaussian-process merger approximant for the detection and characterization of eccentric binary black hole mergers
Bibliographic record
Abstract
We present ENIGMA, a time domain, inspiral-merger-ringdown waveform model that describes nonspinning binary black holes systems that evolve on moderately eccentric orbits. The inspiral evolution is described using a consistent combination of post-Newtonian theory, self-force and black hole perturbation theory. Assuming eccentric binaries that circularize prior to coalescence, we smoothly match the eccentric inspiral with a stand-alone, quasicircular merger, which is constructed using machine learning algorithms that are trained with quasicircular numerical relativity waveforms. We show that ENIGMA reproduces with excellent accuracy the dynamics of quasicircular compact binaries. We validate ENIGMA using a set of Einstein Toolkit eccentric numerical relativity waveforms, which describe eccentric binary black hole mergers with mass-ratios between $1\ensuremath{\le}q\ensuremath{\le}5.5$, and eccentricities ${e}_{0}\ensuremath{\lesssim}0.2$ ten orbits before merger. We use this model to explore in detail the physics that can be extracted with moderately eccentric, nonspinning binary black hole mergers. In particular, we use ENIGMA to show that the gravitational wave transients GW150914, GW151226, GW170104, GW170814 and GW170608 can be effectively recovered with spinning, quasicircular templates if the eccentricity of these events at a gravitational wave frequency of 10 Hz satisfies ${e}_{0}\ensuremath{\le}{0.175,0.125,0.175,0.175,0.125}$, respectively. We show that if these systems have eccentricities ${e}_{0}\ensuremath{\sim}0.1$ at a gravitational wave frequency of 10 Hz, they can be misclassified as quasicircular binaries due to parameter space degeneracies between eccentricity and spin corrections. Using our catalog of eccentric numerical relativity simulations, we discuss the importance of including higher-order waveform multipoles in gravitational wave searches of eccentric binary black hole mergers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".