Detecting extreme mass ratio inspirals with LISA using time-frequency methods II: search characterization

TL;DR

This paper evaluates a time-frequency spectrogram method for detecting extreme mass ratio inspirals (EMRIs) with LISA, demonstrating its effectiveness across various waveforms and distances up to 3 Gpc, and discusses potential improvements.

Contribution

It provides a comprehensive Monte Carlo analysis of the time-frequency detection method's performance for a range of EMRI waveforms and distances, extending previous work with more realistic noise statistics.

Findings

EMRIs can be detected up to 1-3 Gpc depending on parameters

The method shows robustness across different waveforms

Potential improvements to the algorithm are discussed

Abstract

The inspirals of stellar-mass compact objects into supermassive black holes constitute some of the most important sources for LISA. Detection of these sources using fully coherent matched filtering is computationally intractable, so alternative approaches are required. In a previous paper (Wen and Gair 2005, gr-qc/0502100), we outlined a detection method based on looking for excess power in a time-frequency spectrogram of the LISA data. The performance of the algorithm was assessed using a single `typical' trial waveform and approximations to the noise statistics. In this paper we present results of Monte Carlo simulations of the search noise statistics and examine its performance in detecting a wider range of trial waveforms. We show that typical extreme mass ratio inspirals (EMRIs) can be detected at distances of up to 1--3 Gpc, depending on the source parameters. We also discuss some remaining issues with the technique and possible ways in which the algorithm can be improved.