Of Harbingers and Higher Modes: Improved Gravitational-wave Early Warning of Compact Binary Mergers
Bibliographic record
Abstract
Abstract A crucial component to maximizing the science gain from the multi-messenger follow-up of gravitational-wave (GW) signals from compact binary mergers is the prompt discovery of the electromagnetic counterpart. Ideally, the GW detection and localization must be reported early enough to allow for telescopes to slew to the location of the GW event before the onset of the counterpart. However, the time available for early warning is limited by the short duration spent by the dominant (ℓ = m = 2) mode within the detector’s frequency band. Nevertheless, we show that including higher modes—which enter the detector’s sensitivity band well before the dominant mode—in GW searches can enable us to significantly improve the early warning ability for compact binaries with asymmetric masses (such as neutron star–black hole (NSBH) binaries). We investigate the reduction in the localization sky-area when the ℓ = m = 3 and ℓ = m = 4 modes are included in addition to the dominant mode, considering typical slew-times of electromagnetic telescopes (30–60 s). We find that, in LIGO’s projected “O5” (“Voyager”) network with five GW detectors, some of the NSBH mergers, located at a distance of 40 Mpc, can be localized to a few hundred sq. deg. ∼45 s prior to the merger, corresponding to a reduction-factor of 3–4 (5–6) in sky-area. For a third-generation network, we get gains of up to 1.5 min in early warning times for a localization area of 100 sq. deg., even when the source is placed at 100 Mpc.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".