Enhancing the Scan Rate for Axion Dark Matter: Quantum Noise Evasion and Maximally Informative Analysis

Dark matter axions, particles whose hypothesized existence could resolve two of the largest outstanding mysteries in physics, are made difficult to detect by their extremely feeble coupling to ordinary matter. The axion haloscope, first realized experimentally three decades ago, remains among the most viable detection platforms, but even today’s leading technology would optimisti-cally require many millennia to scan commonly targeted portions of axion parameter space. Today’s axion direct detection community is searching therefore not just for the elusive particles, but for technologies and innovations that will permit more efficient searches. In this thesis, I present two such innovations. First, the resource of quantum squeezing sequesters the noise of a haloscope measurement into unmeasured observables, improving the sensitivity bandwidth and hence the scan rate of the detector, its primary figure of merit. Second, valuable information pertinent to the existence of the axion is discarded by the standard hypothesis testing framework used to look for axions. An alternative, Bayesian analysis utilizes the full information content of the haloscope measurement, yielding a tangible speedup at zero operational or hardware cost. Together, these innovations are used improve threefold the scan rate of a dark matter search performed by the Haloscope At Yale Sensitive To Axion Cold dark matter (HAYSTAC) experiment.