Ian Sohl, University of Utah
Physical Sciences
Current software in the High Altitude Water Cherenkov (HAWC) Telescope data collection system only triggers saving of events that pass a specified number of hits and energy. Our analysis of the untriggered (and unsaved) data will identify the number of potentially significant events that are bypassed by the existing software. By the application of a sorting function onto current Monte Carlo generated data, we can categorize incoming events into various types of particles, primarily muons, while also filtering out randomized noise from the photomultiplier tubes used in HAWC. Due to the relatively low rate and energy of the photomultiplier tube noise, many of the significant events for the untriggered set are potential useful particles. Our triggering algorithm, based on the energy, timing and saturation of the tanks is primarily focused on separating muons from the bulk of data. These raw rate data for small events are a relatively unexplored area for HAWC and measurements can be useful for a variety of calibration tasks for the telescope. They can be useful for understanding the impact of the atmosphere on the telescope’s data collection, as well as the triggering of the photomultiplier tubes through secondary sources. This untriggered data can also be used in a variety of useful forms not directly related to HAWC’s primary usage goals, primarily solar physics. Due to the relatively low energy and hit count from solar events, most of the data are thrown away by the triggering algorithm.