SEARCH FOR RARE LOW ENERGY INTERACTIONS IN LIQUID XENON DARK MATTER EXPERIMENTS

Dark matter constitutes a significant fraction of the Universe’s mass, yet its fundamental nature remains unknown. Liquid xenon-based time projection chambers (TPCs) have emerged as the most sensitive detectors in the search for weakly interacting massive particles (WIMPs) and other rare low-energy interactions. This thesis focuses on extending the reach of xenon detectors to new physics by addressing key background challenges and improving the sensitivity to rare signals.

A major aspect of this research involves the analysis of data from the XENON1T and XENONnT experiments. A dedicated search for particle interactions coinciding with gravitational wave (GW) events was performed, extending the multi-messenger astronomy frontier. Additionally, nuclear recoil calibration of XENONnT using a $^{88}$YBe photoneutron source was carried out to improve low-energy signal reconstruction. The analysis involved machine learning techniques such as Boosted Decision Trees (BDTs) to separate signal from accidental coincidence (AC) backgrounds. Furthermore, this work investigates the origin of single electrons and photons causing AC backgrounds, an important limiting factor in low-energy searches. This insight is critical for improving the background modeling and design of future xenon-based detectors.

The results of this thesis contribute to the ongoing effort to detect dark matter and other beyond-standard-model (BSM) particles. They also pave the way for more precise measurements of neutrino interactions and novel applications of liquid xenon TPCs in astroparticle physics