The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment that has a broad physics program, primarily including a high precision measurement of the neutrino oscillation parameters, as well as measurements of solar neutrinos, detection of supernova neutrinos, and searches for Beyond the Standard Model physics. This thesis details contributions to the commissioning and development of the readout subsystem of the data acquisition system (DAQ) so that data taking can begin immediately once the far detector is installed. As a result of testing and optimizations on different types of servers, we have an understanding and control over the varying server topologies between both Intel and AMD CPUs. We demonstrate that the highest-bandwidth servers can support twice the load than originally planned, meaning half the number of readout servers required to support the detectors.

On the physics side, this thesis also contributes to the collaboration’s low energy program with a study that addresses limitations of the DAQ to improve capabilities in the low energy regime (< 10 MeV). This study aims to maximize the sensitivity to solar neutrinos as the signal of interest, which would otherwise be overwhelmed by radiological backgrounds that would quickly fill the collaboration’s data storage capacity. A region-of-interest (ROI) filtering algorithm is used to zero-suppress data in regions of the detector with no activity. This allows for a lower threshold while respecting the data storage limits, to maximize the detection efficiency of solar neutrinos. When tested on simulations, the ROI demonstrates data reduction levels upwards of 90% depending on the parameter settings, with promising sensitivity to solar neutrinos.