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Computational Techniques for the Dir...

Qin, Juehang.

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Computational Techniques for the Direct Detection of Dark Matter.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational Techniques for the Direct Detection of Dark Matter./
作者:	Qin, Juehang.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	169 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
Contained By:	Dissertations Abstracts International85-01B.
標題:	Isotopes. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30540034
ISBN:	9798379870188

Computational Techniques for the Direct Detection of Dark Matter.
Qin, Juehang.

Computational Techniques for the Direct Detection of Dark Matter. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 169 p.

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

Thesis (Ph.D.)--Purdue University, 2023.

Dark matter makes up a vast majority of the matter in the universe, however, the composition of dark matter is unknown. One approach to uncover the composition of dark matter is via the direct detection of dark matter. This thesis focuses on the use of computational techniques to enhance or enable the direct detection of dark matter by the XENON experiment and the Windchime project.First, a software veto for radon chain backgrounds using measurements of the convective motion in XENON1T is detailed and demonstrated. It is shown that this can reduce the radon chain background in the XENON1T and XENONnT detectors, and with potential for improved performance in larger detectors with reduced convection. The design and operation of a 88Y-Be photo-neutron source is then discussed. It is shown that in the calibration data collected there is a significant population of neutron events that can be used to calibrate the detector response. Following that is a discussion of the methods to conduct analysis and make sensitivity projections for the Windchime project. A semi-analytical method for sensitivity projections that does not require a full simulation of the sensor array is shown, and both Bayesian and frequentist approaches to track-finding in sensor arrays are demonstrated. The latter includes an estimate of the look-elsewhere effect in such a dark matter search. This leads to an exploration of the use of Gaussian random fields for the estimation of the look-elsewhere effect, wherein it is shown that Gaussian random fields can be sampled quickly to compute the look-elsewhere effect corrections.

ISBN: 9798379870188Subjects--Topical Terms:

664463
Isotopes.

Computational Techniques for the Direct Detection of Dark Matter.
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