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We present a rapid parameter estimation framework for compact binarycoalescence (CBC) signals observed by the LIGO-Virgo-KAGRA (LVK) detectornetwork. The goal of our framework is to enable optimal source localization ofbinary neutron star (BNS) signals in low latency, as well as improve theoverall scalability of full CBC parameter estimation analyses. Our framework isbased on the reduced order quadrature (ROQ) technique, and resolves itsshortcomings by utilizing multiple ROQ bases in a single parameter estimationrun. We have also developed sets of compact ROQ bases for various waveformmodels, IMRPhenomD, IMRPhenomPv2, IMRPhenomPv2$\_$NRTidalv2, and IMRPhenomXPHM.We benchmark our framework with hundreds of simulated observations of BNSsignals by the LIGO-Virgo detector network, and demonstrate that it providesaccurate and unbiased estimates on BNS source location, with a median analysistime of $6$ minutes. The median searched area is reduced by around 30$\%$compared to estimates produced by BAYESTAR: from $21.8\,\mathrm{deg^2}$ to$16.6\,\mathrm{deg^2}$. Our framework also enables detailed parameterestimation taking into account gravitational-wave higher multipole moments, thetidal deformation of colliding objects, and detector calibration errors ofamplitude and phase with the time scale of hours. Our rapid parameterestimation technique has been implemented in one of the LVK parameterestimation engines, BILBY, and is being employed by the automated parameterestimation analysis of the LVK alert system.

Rapid localization and inference on compact binary coalescences with the Advanced LIGO-Virgo-KAGRA gravitational-wave detector network