Generating tailored high frequency features in core collapse supernova gravitational wave signals applicable in LIGO interferometric studies

TL;DR

This paper presents a computationally efficient analytical model to generate high-frequency gravitational wave signals from core-collapse supernovae, aiding LIGO data analysis and detection efforts.

Contribution

It introduces a novel analytical approach that simulates high-frequency features in supernova gravitational waves with minimal computational resources.

Findings

Generated signals match LIGO spectral data

Model replicates characteristic frequency growth over time

Effective for gravitational wave transient analysis

Abstract

In this article, we introduce a methodology based on an analytical model of a damped harmonic oscillator subject to random forcing to generate transient gravitational wave signals. Such a model incorporates a simulated linear high-frequency component that mirrors the growing characteristic frequency over time observed in numerical simulations of core-collapse supernova gravitational wave signals. Unlike traditional numerical simulations, the method proposed in this study requires minimal computational resources, which makes it particularly advantageous for tasks such as data analysis, detection, and reconstruction of gravitational wave transients. To verify the physical accuracy of the generated signals, they are compared against the amplitude spectral of current LIGO interferometers and a 3D numerical simulation of a core-collapse supernova gravitational wave signal from the Andresen et al. 2017 model s15.nr. The results indicate that this approach is effective in generating scalable signals that align with LIGO interferometric data, offering potential utility in various gravitational wave transient investigations.