Inferring astrophysical information from gravitational waves emitted by
compact binaries is one of the key science goals of gravitational-wave
astronomy. In order to reach the full scientific potential of
gravitational-wave experiments we require techniques to mitigate the cost of
Bayesian inference, especially as gravitational-wave signal models and analyses
become increasingly sophisticated and detailed. Reduced order models (ROMs) of
gravitational waveforms can significantly reduce the computational cost of
inference by removing redundant computations. In this paper we construct the
first reduced order models of gravitational-wave signals that include the
effects of spin-precession, inspiral, merger, and ringdown in compact object
binaries, and which are valid for component masses describing binary neutron
star, binary black hole and mixed binary systems. This work utilizes the
waveform model known as "IMRPhenomPv2". Our ROM enables the use of a fast
reduced order quadrature (ROQ) integration rule which allows us to approximate
Bayesian probability density functions at a greatly reduced computational cost.
We find that the ROQ rule can be used to speed up inference by factors as high
as 300 without introducing systematic bias. This corresponds to a reduction in
computational time from around half a year to a half a day, for the longest
duration/lowest mass signals. The ROM and ROQ rule are available with the main
inference library of the LIGO Scientific Collaboration, LALInference.

本文利用 IMRPhenomPv2 的波形模型构建了包括自旋进动、融合、环差的引力波信号的第一批简化模型，有效减少了计算复杂度，并使用 ROQ 方法加速了贝叶斯推断，使得长周期 / 低质量信号的计算时间由半年缩短为半天，该简化模型和 ROQ 方法已集成到 LALInference 推断库中。