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Gravitational-wave observations of binary neutron star coalescences constrainthe neutron-star equation of state by enabling measurement of the tidaldeformation of each neutron star. This deformation is determined by the tidaldeformability parameter $\Lambda$, which was constrained using the first binaryneutron star gravitational-wave observation, GW170817. Now, with themeasurement of the second binary neutron star, GW190425, we can combinedifferent gravitational-wave measurements to obtain tighter constraints on theneutron-star equation of state. In this paper, we combine data from GW170817and GW190425 to place constraints on the neutron-star equation of state. Tofacilitate this calculation, we derive interpolated marginalized likelihoodsfor each event using a machine learning algorithm. These likelihoods, which wemake publicly available, allow for results from multiple gravitational-wavesignals to be easily combined. Using these new data products, we find that theradius of a fiducial 1.4 $M_\odot$ neutron star is constrained to$11.6^{+1.6}_{-0.9}$ km at 90% confidence and the pressure at twice the nuclearsaturation density is constrained to $3.1^{+3.1}_{-1.3}\times10^{34}$dyne/cm$^2$ at 90% confidence. This result is dominated by GW170817 and isconsistent with findings from other works.

A scalable random forest regressor for combining neutron-star equation of state measurements: A case study with GW170817 and GW190425