Collaboration enhances dark matter detection by upgrading detector hardware and analyzing data, suggesting improved insights.
On behalf of the DEAP collaboration SNOLAB and the McDonald Institute at Queen’s, the DEAP-3600 experiment employs a vessel filled with liquid argon to detect dark matter. [1] When argon atoms are excited by particle interactions, they emit ultraviolet light, which is subsequently detected by an array of sensors surrounding the vessel. This emitted light is analyzed to identify the nature of the interactions. During this summer, I had the opportunity to work on hardware upgrades for the detector, aimed at enhancing the filtration process to reduce background counts. This experience allowed me to gain a comprehensive understanding of the detector's hardware components and to physically install and assist in the installation of several key components. Following these upgrades, I analyzed a subset of the data collected by the detector during its vacuum stage. Utilizing tools such as DEAPDISPLAY, I conducted a detailed visual inspection of specific runs, manually categorizing events to improve our understanding and analysis of the data. This hands-on experience provided valuable insights into both the hardware and data analysis aspects of the detector system. [1]
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Aarchi Shah (2025) studied this question.
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