GW231123: A Case for Binary Microlensing in a Strong Lensing Field

TL;DR

This paper proposes a binary microlensing model within a strong lensing galaxy to explain GW231123's unusual properties, using a neural network for efficient waveform generation, and finds that this model aligns the source's parameters with known black hole populations.

Contribution

It introduces a novel binary lensing model embedded in a galaxy and develops a neural network to rapidly generate waveforms, improving the interpretation of GW231123.

Findings

Binary lensing model explains observed properties of GW231123.

Neural network accelerates waveform generation to milliseconds.

Inferred black hole masses and spins align with known populations.

Abstract

The unusual properties of GW231123, including component masses within the pair-instability mass gap ($137^{+22}_{-17}\mathrm{M}_\odot$ and $103^{+20}_{-52}\mathrm{M}_\odot$ at 90\% credible intervals) and extremely large spins near the Kerr limit, have challenged standard formation scenarios. While gravitational lensing has been proposed as an explanation, current millilensing studies suggest the signal consists of three overlapping images, a configuration that exceeds the predictions of the isolated point-mass lens model. In this work, we investigate a binary lens model embedded within a strong lensing galaxy. This is the simplest model that not only naturally produces the observed number of images but also aligns with the fact that microlensing objects usually reside in galaxies. To overcome the high computational cost of the diffraction integral required for wave optics, we constructed a Transformer-based neural network that accurately generates lensing waveforms within milliseconds per waveform. Using the NRSur7dq4 waveform model, we find primary and secondary lens masses of $714^{+239}_{-309} \mathrm{M}_\odot$ and $87^{+139}_{-73} \mathrm{M}_\odot$, respectively. We also find a strong lensing magnification of $5.56^{+2.78}_{-1.98}$ (at 90\% credible intervals) and a Bayes factor of $\log_{10}B^\mathrm{Binary}_\mathrm{Single}\simeq1.34$. This result underscores the necessity of considering multi-body and environmental effects in microlensing studies. More crucially, under this embedded binary lens interpretation, the inferred source-frame binary black hole masses ($80.0^{+21.3}_{-14.4} \mathrm{M}_\odot$ and $62.0^{+19.8}_{-29.4} \mathrm{M}_\odot$) and spins ($0.37^{+0.51}_{-0.33}$ and $0.40^{+0.52}_{-0.35}$) shift to values consistent with the current population constrained from O1--O3.