CaltechTHESIS
  A Caltech Library Service

Physically-Motivated Modeling of Kinetic Inductance Phonon-Mediated Detector for Light Dark Matter Searches

Citation

Cap, Chi Lan (2025) Physically-Motivated Modeling of Kinetic Inductance Phonon-Mediated Detector for Light Dark Matter Searches. Senior thesis (Major), California Institute of Technology. doi:10.7907/nd6z-1y53. https://resolver.caltech.edu/CaltechTHESIS:06172025-193756039

Abstract

The properties of dark matter (DM) is one of the most exciting mysteries in astrophysics, and they are important in understanding cosmological structure formation and could potentially reveal new physics. Direct searches for DM necessitate using ultra-sensitive quantum sensors, one of which is the kinetic inductance phonon-meditated detector (KIPM). Understanding KIPM response is vital to understanding the device's energy resolution. Here, we present a physically-motivated model of KIPM response based on quasiparticle and phonon lifetimes. We examine its adherence to experimental data in three formulations, which either six, five, or four time constants. We examined the temperature-dependence of these time constants and compare them to the results of previous models. All three models fit to data at below 75 mK, with successful fits up to 150 mK in some cases; the five time constants model presents the closest match of temperature-dependence of quasiparticle and phonon lifetimes to existing knowledge, while goodness of fit indicates that the six time constant model have the potential to fit high temperature data better. This paper detailed both the behaviors of the physically-motivated models as well as fitting considerations for the behaviors of the fit.

Item Type:Thesis (Senior thesis (Major))
Subject Keywords:astrophysics; cosmology; dark matter; dark matter searches; light dark matter
Degree Grantor:California Institute of Technology
Division:Physics, Mathematics and Astronomy
Major Option:Astrophysics
Awards:Mary A. Earl McKinney Prize in Literature, 2025. Bonnie Cashin Prize for Imaginative Thinking, 2022.
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Golwala, Sunil
Thesis Committee:
  • None, None
Defense Date:27 May 2025
Non-Caltech Author Email:lanchi.cap (AT) gmail.com
Record Number:CaltechTHESIS:06172025-193756039
Persistent URL:https://resolver.caltech.edu/CaltechTHESIS:06172025-193756039
DOI:10.7907/nd6z-1y53
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:17465
Collection:CaltechTHESIS
Deposited By: Chi Cap
Deposited On:17 Jun 2025 22:59
Last Modified:17 Jun 2025 23:00

Thesis Files

[img] PDF - Final Version
See Usage Policy.

10MB

Repository Staff Only: item control page