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Testing the wormhole echo hypothesis for GW231123

Qi Lai, Qing-Yu Lan, Zhan-He Wang, Yun-Song Piao

TL;DR

This study tests whether the short-duration GW231123 can be explained by a wormhole-echo signal rather than a standard binary black hole merger. It models a leading echo pulse with a phenomenological sine-Gaussian waveform and compares its Bayesian evidence against a BBH baseline using the IMRPhenomXPHM-SpinTaylor waveform. The result, $\ln \mathcal{B}^{\rm Echo}_{\rm BBH}=1.87$, indicates weak-to-moderate support for the echo hypothesis under the chosen framework, while noting that GW190521 favored the BBH interpretation with a negative value. The authors emphasize that the Bayes factor is model-dependent and advocate for more realistic echo models that include spin effects and multiple echoes, as well as model-agnostic searches and population-level tests. Overall, the work motivates further exploration of wormhole-echo interpretations for massive, short-duration gravitational-wave events.

Abstract

The short-duration gravitational-wave (GW) event GW231123 has inferred component masses in the pair-instability mass gap and exhibits a burst-like morphology with no clearly inspiral, making it an interesting target for tests beyond the standard binary black hole (BBH) interpretation. In this work, motivated by its phenomenological similarity to GW190521, we test whether GW231123 is compatible with a wormhole-echo scenario by modeling a leading echo pulse with a well-motivated phenomenological sine-Gaussian wavepacket. We perform Bayesian model comparison against a BBH baseline described by the IMRPhenomXPHM-SpinTaylor waveform, and obtain the Bayes factor ratio $\ln B^{\rm Echo}_{\rm BBH} = 1.87$, corresponding to weak-to-moderate support for the echo hypothesis. In our previous analysis for GW190521 within the same overall framework, we found $\ln B^{\rm Echo}_{\rm BBH} \approx -2.9$, implying a shift of $Δ\ln B \approx 4.8$ between the two events. This sign change indicates that GW231123 is more compatible with a single-pulse echo description than GW190521.

Testing the wormhole echo hypothesis for GW231123

TL;DR

This study tests whether the short-duration GW231123 can be explained by a wormhole-echo signal rather than a standard binary black hole merger. It models a leading echo pulse with a phenomenological sine-Gaussian waveform and compares its Bayesian evidence against a BBH baseline using the IMRPhenomXPHM-SpinTaylor waveform. The result, , indicates weak-to-moderate support for the echo hypothesis under the chosen framework, while noting that GW190521 favored the BBH interpretation with a negative value. The authors emphasize that the Bayes factor is model-dependent and advocate for more realistic echo models that include spin effects and multiple echoes, as well as model-agnostic searches and population-level tests. Overall, the work motivates further exploration of wormhole-echo interpretations for massive, short-duration gravitational-wave events.

Abstract

The short-duration gravitational-wave (GW) event GW231123 has inferred component masses in the pair-instability mass gap and exhibits a burst-like morphology with no clearly inspiral, making it an interesting target for tests beyond the standard binary black hole (BBH) interpretation. In this work, motivated by its phenomenological similarity to GW190521, we test whether GW231123 is compatible with a wormhole-echo scenario by modeling a leading echo pulse with a well-motivated phenomenological sine-Gaussian wavepacket. We perform Bayesian model comparison against a BBH baseline described by the IMRPhenomXPHM-SpinTaylor waveform, and obtain the Bayes factor ratio , corresponding to weak-to-moderate support for the echo hypothesis. In our previous analysis for GW190521 within the same overall framework, we found , implying a shift of between the two events. This sign change indicates that GW231123 is more compatible with a single-pulse echo description than GW190521.
Paper Structure (8 sections, 5 equations, 3 figures, 2 tables)

This paper contains 8 sections, 5 equations, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Method and analysis setup
  3. Waveform template
  4. Bayesian model selection
  5. Result
  6. Parameter inference
  7. Model comparison
  8. Conclusion and outlook

Figures (3)

  • Figure 1: Posterior distributions for selected BBH parameters (source-frame component masses, dimensionless spin magnitudes, luminosity distance, and geocenter time) inferred under the BBH hypothesis using IMRPhenomXPHM-SpinTaylor. The vertical lines indicate the medians and the shaded regions show the 90% credible intervals.
  • Figure 2: Posterior distributions of the echo-for-wormhole waveform parameters inferred with the phenomenological sine-Gaussian wavepacket template. The vertical lines indicate the medians and the shaded regions show the 90% credible intervals.
  • Figure 3: Whitened strain data and maximum-likelihood waveform reconstructions for the H1, L1 detector around the trigger time (GPS $1384782888.634$).The top row shows the echo-pulse model, and the bottom row shows the BBH model using the IMRPhenomXPHM-SpinTaylor approximant. In both cases, the data and waveforms are whitened using the noise PSD provided with the public LIGO data release and band-passed over $20$--$128~\mathrm{Hz}$; the whitening follows Eq. \ref{['Eq:whiten']}.