Characterization and Enhancement of Dark Matter Detection Efficiency in BREAD

The Broadband Reflector Experiment for Axion Detection (BREAD) searches for particle dark matter within a gigahertz to terahertz frequency range using a coaxial parabolic reflector. The present work characterized and enhanced the detection efficiency in the versions of BREAD operating at these two frequency extremes—InfraBREAD and GigaBREAD. InfraBREAD will search for dark matter-produced infrared photons with a 1mm² single-photon counting quantum sensor. However, these high frequency photons are emitted incoherently, which can smear the detection focal point beyond the photosensor area. Through ray-tracing simulations, we identify a novel optical configuration of lenses and reflectors to refocus the smeared signal even in the presence of experimental misalignments, improving the average detection efficiency by 10% with a maximal local increase of 55%. GigaBREAD, by contrast, searches for gigahertz photons which form coherent standing waves between the reflector and a horn antenna. For its first-ever data taking run, we measured the GigaBREAD blackbody radiation spectrum and calculated the system noise temperature to determine the signal sensitivity to gigahertz resonant modes, eventually leading to the world-leading dark photon exclusion limit of 10^-12 in [10.7, 12.5] GHz.