Optimizing StackSlide setup and data selection for continuous-gravitational-wave searches in realistic detector data

TL;DR

This paper enhances the optimization of StackSlide searches for continuous gravitational waves by incorporating realistic data conditions like gaps and noise variations, and introduces data selection algorithms to improve sensitivity.

Contribution

It extends previous ideal-condition optimization methods to realistic data scenarios and proposes new data selection algorithms for better sensitivity in gravitational wave searches.

Findings

Numerical optimization reproduces ideal-condition results.

Relaxed data conditions favor a compact data selection algorithm.

Compact data selection yields higher sensitivity than greedy methods.

Abstract

The search for continuous gravitational waves in a wide parameter space at fixed computing cost is most efficiently done with semicoherent methods, e.g. StackSlide, due to the prohibitive computing cost of the fully coherent search strategies. Prix&Shaltev arXiv:1201.4321 have developed a semi-analytic method for finding \emph{optimal} StackSlide parameters at fixed computing cost under ideal data conditions, i.e. gap-less data and constant noise floor. In this work we consider more realistic conditions by allowing for gaps in the data and changes in noise level. We show how the sensitivity optimization can be decoupled from the data selection problem. To find optimal semicoherent search parameters we apply a numerical optimization using as example the semicoherent StackSlide search. We also describe three different data selection algorithms. Thus the outcome of the numerical optimization consists of the optimal search parameters and the selected dataset. We first test the numerical optimization procedure under ideal conditions and show that we can reproduce the results of the analytical method. Then we gradually relax the conditions on the data and find that a compact data selection algorithm yields higher sensitivity compared to a greedy data selection procedure.