Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Measuring the neutron star equation of state with gravitational waves:
  the first forty binary neutron star mergers   Gravitational waves from binary neutron star coalescences contain rich
information about matter at supranuclear densities encoded by the neutron star
equation of state. We can measure the equation of state by analyzing the tidal
interactions between neutron stars, which is quantified by the tidal
deformability. Multiple merger events are required to probe the equation of
state over a range of neutron star masses. The more events included in the
analysis, the stronger the constraints on the equation of state. In this paper,
we build on previous work to explore the constraints that LIGO and Virgo are
likely to place on the neutron star equation of state by combining the first
forty binary neutron star detections, a milestone we project to be reached
during the first year of accumulated design-sensitivity data. We carry out
Bayesian inference on a realistic mock dataset of binaries to obtain posterior
distributions for neutron star tidal parameters. In order to combine posterior
samples from multiple observations, we employ a random forest regressor, which
allows us to efficiently interpolate the likelihood distribution. Assuming a
merger rate of 1540 Gpc$^{-3}$ yr$^{-1}$ and a LIGO-Virgo detector network
operating for one year at the sensitivity of the third-observation run, plus an
additional eight months of design sensitivity, we find that the radius of a 1.4
$M_\odot$ neutron star can be constrained to $\sim 10$% at 90% confidence. At
the same time, the pressure at twice the nuclear saturation density can be
constrained to $\sim 45$ % at 90% confidence. Finally, we add an appendix
following publication of the paper in the journal, showing the posterior
distribution of the maximum neutron star mass allowed by the equation of state.
We find that the maximum mass can be constrained to $\sim 0.3$ $M_\odot$ at 90%
confidence.

30
The categories of this paper are: q-alg
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom