Development of a novel reaction plane detector for event plane measurements in heavy ion collisions at the large hadron collider

Phipps, Michael

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https://hdl.handle.net/2142/115322 Copy

Description

Title

Development of a novel reaction plane detector for event plane measurements in heavy ion collisions at the large hadron collider

Author(s)

Phipps, Michael

Issue Date

2022-01-10

Director of Research (if dissertation) or Advisor (if thesis)

• Grosse Perdekamp, Matthias
• Sickles, Anne

Doctoral Committee Chair(s)

Giannetta, Russ

Committee Member(s)

Leite Noronha, Jorge

Department of Study

Physics

Discipline

Physics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Event plane
• reaction plane detector
• zero degree calorimeter
• RPD
• ZDC
• spectator-based event plane
• spectator neutrons
• heavy ion collisions

Abstract

When ATLAS begins taking heavy ion data again in Run 3 it will do so with the ability to make spectator-based event plane measurements for the first time. This is due to the experiment's new Reaction Plane Detector (RPD), developed at the University of Illinois. The RPD will be installed in the far-forward region of ATLAS on either arm, between the first and second Zero Degree Calorimeter (ZDC) modules. It will sit at $|\eta|$ $>$ 8.3 in a region that is sensitive to neutral spectators from the collision system. This provides sensitivity to the collision's $\Psi_{1}$ event plane. Furthermore, the large rapidity gap between this forward region and the central detectors provides a relatively clean environment, largely free from biases due to non-flow effects. It also features a novel design that should allow it to survive and make successful measurements in an extremely challenging radiation environment. In this thesis, the development of the detector is detailed along with performance projections for physics observables. This starts with a review of past $\Psi_{1}$-based physics measurements. The radiation levels expected during Runs 3 and 4 are then quantified and radiation studies discussed that led to the selection of the detector's radiation hard active material. Then the design itself will be presented and features and biases of this design explored through simulation. This allows for performance-based design optimization and provides the level of understanding necessary to reconstruct the detector's response as precisely as possible. A number of machine learning-based approaches to this reconstruction will be presented that allow for resolution improvements of up to 12$\%$. These competitive simulation-based projection results will be compared to the resolutions to which other experiments have measured $\Psi_{1}$, and finally, projections will be presented for several Run 4 optimization strategies that may boost performance by an additional 35$\%$.

Graduation Semester

2022-05

Type of Resource

Thesis

Copyright and License Information

Copyright 2021 Michael Phipps

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