Continuous gravitational wave searches from neutron stars and exotic sources in ground-based interferometric data

This thesis focuses on developing and applying robust data analysis methods for the detection of continuous gravitational waves (CWs), using both real and simulated data. It addresses challenges in the search strategies: targeted searches, where source parameters should be perfectly constrained; narrowband searches, where source position is well constrained but rotational parameters not; and all-sky searches, which scan broad parameter spaces to find unknown sources. Specific attention is given to optimising follow-up procedures and computational efficiency. First, we reviews gravitational wave (GW) theory, detection principles, and current CW search methodologies. My scientific contributions begin with a novel semicoherent targeted search for CW sources in binary systems. This method tunes the coherence time by accounting for orbital parameter uncertainties and is tested on a set of targets from the ATNF catalogue. Next, improvements to the 5n-vector narrowband pipeline are presented. With my contributions, the pipeline now handles sources in binary systems with well-known orbital parameters and scans over the second derivative of CW frequency. These features are used in three applied searches. The final part of the thesis focuses on follow-up techniques for all-sky search candidates. One chapter presents an optimised follow-up pipeline using a Markov Chain Monte Carlo (MCMC) approach with pyfstat, developed in collaboration with the LIGO group at UIB. This work demonstrates significant computational savings (up to two orders of magnitude) while maintaining high detection efficiency. The last chapter discusses the application of these optimisations to the follow-up of Frequency-Hough (FH) candidates. A total of 109 candidates from an FH all-sky search are processed through standard procedures and then using pyfstat in a second stage. No CW signals were detected in these searches. The thesis concludes by summarising findings and outlining future research directions.