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Cryogenic cooling of the test masses of interferometric gravitational wavedetectors is a promising way to reduce thermal noise. However, cryogeniccooling limits the incident power to the test masses, which limits the freedomof shaping the quantum noise. Cryogenic cooling also requires short and thicksuspension fibers to extract heat, which could result in the worsening ofthermal noise. Therefore, careful tuning of multiple parameters is necessary indesigning the sensitivity of cryogenic gravitational wave detectors. Here, wepropose the use of particle swarm optimization to optimize the parameters ofthese detectors. We apply it for designing the sensitivity of the KAGRAdetector, and show that binary neutron star inspiral range can be improved by10%, just by retuning seven parameters of existing components. We also showthat the sky localization of GW170817-like binaries can be further improved bya factor of 1.6 averaged across the sky. Our results show that particle swarmoptimization is useful for designing future gravitational wave detectors withhigher dimensionality in the parameter space.

Particle swarm optimization of the sensitivity of a cryogenic gravitational wave detector