Numerical relativity surrogate models for exotic compact objects: the case of head-on mergers of equal-mass Proca stars
arxiv(2024)
摘要
We present several high-accuracy surrogate models for gravitational-wave
signals from equal-mass head-on mergers of Proca stars, computed through the
Newman-Penrose scalar ψ_4. We also discuss the current state of the model
extensions to mergers of Proca stars with different masses, and the particular
challenges that these present. The models are divided in two main categories:
two-stage and monolithic. In the two-stage models, a dimensional reduction
algorithm is applied to embed the data in a reduced feature space, which is
then interpolated in terms of the physical parameters. For the monolithic
models, a single neural network is trained to predict the waveform from the
input physical parameter. Our model displays mismatches below 10^-3 with
respect to the original numerical waveforms. Finally, we demonstrate the usage
of our model in full Bayesian parameter inference through the accurate recovery
of numerical relativity signals injected in zero-noise, together with the
analysis of GW190521. For the latter, we observe excellent agreement with
existing results that make use of full numerical relativity.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要