Debiasing Standard Siren Inference of the Hubble Constant with Marginal Neural Ratio Estimation

TL;DR

This paper introduces a novel simulation-based inference method using marginal neural ratio estimation to debias Hubble constant measurements from gravitational wave standard sirens, accounting for anisotropic emission biases.

Contribution

It presents a new SBI framework that includes GW-only detected mergers, effectively correcting for systematic biases in $H_0$ inference from BNS mergers.

Findings

Corrects approximately 90% of bias in $H_0$ estimation.

Includes GW-only detected mergers in the analysis.

Enables debiased $H_0$ inference with extensive EM follow-up data.

Abstract

Gravitational wave (GW) standard sirens may resolve the Hubble tension, provided that standard siren inference of $H_0$ is free from systematic biases. However, standard sirens from binary neutron star (BNS) mergers suffer from two sources of systematic bias, one arising from the anisotropy of GW emission, and the other from the anisotropy of electromagnetic (EM) emission from the kilonova. For an observed sample of BNS mergers, the traditional Bayesian approach to debiasing involves the direct computation of the detection likelihood. This is infeasible for large samples of detected BNS merger due to the high dimensionality of the parameter space governing merger detection. In this study, we bypass this computation by fitting the Hubble constant to forward simulations of the observed GW and EM data under a simulation-based inference (SBI) framework using marginal neural ratio estimation. A key innovation of our method is the inclusion of BNS mergers which were only detected in GW, which allows for estimation of the bias introduced by EM anisotropy. Our method corrects for $\sim$90$\%$ of the bias in the inferred value of $H_0$ when telescope follow-up observations of BNS mergers have extensive tiling of the merger localization region, using known telescope sensitivities and assuming a model of kilonova emission. Our SBI-based method thus enables a debiased inference of the Hubble constant of BNS mergers, including both mergers with detected EM counterparts and those without.