Date of Award

Summer 2023

Document Type

Honors Thesis



First Advisor

Dr. Joel Sander

Second Advisor

Dr. Yongchen Sun

Third Advisor

Dr. Dongming Mei


Dark matter, detector, Python, remote monitoring, SNOLAB, SuperCDMS, uninterruptable power supply (UPS)


Detecting and understanding the nature of dark matter, matter which does not interact with light, is one of the biggest challenges facing physics today. The Super Cryogenic Dark Matter Search (SuperCDMS), located two kilometers underground at SNOLAB, utilizes extremely sensitive detectors kept at very low temperatures to search for dark matter. The direct detection of dark matter is aided by building experiments deep underground, with the challenges of accessing the SuperCDMS experiment at its location in SNOLAB necessitating remote monitoring. This thesis details the development of a program to remotely monitor the health of the SuperCDMS dark matter detectors’ uninterruptible power supply (UPS). The program was written in Python and utilizes several libraries to access information from the UPS webpage and determine whether a power failure has occurred. Further development is underway to connect the program to an online database and trigger an alarm in the case of power failure. Options for future UPS monitoring upgrades are described.



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