How loud are echoes from exotic compact objects?
Bibliographic record
Abstract
The first direct observations of gravitational waves by the LIGO collaboration have motivated different tests of general relativity (GR), including the search for extra pulses following the GR waveform for the coalescence of compact objects. The motivation for these searches comes from the alternative proposal that the final compact object could differ from a black hole by the lack of an event horizon and a central singularity. Such objects are expected in theories that, motivated by quantum gravity modifications, predict horizonless objects as the final stage of gravitational collapse. In such a hypothetical case, this exotic compact object (ECO) will present a (partially) reflective surface at ${r}_{\mathrm{ECO}}={r}_{+}(1+\ensuremath{\epsilon})$, instead of an event horizon at ${r}_{+}$. For this class of objects, an in-falling wave will not be completely lost and will give rise to secondary pulses, to which recent literature refers as echoes. However, the largely unknown ECO reflectivity is determinant for the amplitude of the signal, and details also depend on the initial conditions of the progenitor compact binary. Here, for the first time, we obtain estimates for the detectability of the first echo, using a perturbative description for the inspiral-merger-ringdown waveform and a physically motivated ECO reflectivity. Binaries with comparable masses will have a stronger first echo, improving the chances of detection. For a case like GW150914, the detection of the first echo will require a minimum ringdown signal-to-noise ratio (SNR) in the range $\ensuremath{\sim}20--60$. The most optimistic scenario for echo detection could already be probed by LIGO in the next years. With the expected improvements in sensitivity we estimate one or two events per year to have the required SNR for the first echo detection during O4.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".