Searching for Low Energy Neutrinos and Beam Exotics with Scintillation

用闪烁寻找低能中微子和束流奇异物质

• 批准号: 2192017
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2192017
• 关键词: Searching; Low; Energy; Neutrinos; Beam

Liquid argon Time Projection Chambers(LArTPC) are becoming widely used asneutrino detectors thanks to their excellent position and energy resolution.The UK has major involvement in the next generation DUNE LArTPC, which willbe built in the next decade as well as the Short Baseline Near Detector, whichis set to take data in 2020. LArTPCs use mostly ionization charge toreconstruct events, but argon is also a proficient scintillator. The Manchestergroup is at the forefront of developing the methods of using scintillation lightto perform state-of-the art physics measurements, particularly those thatwould be difficult to perform using only ionization charge i.e. requiring fasttiming or having low energy deposits.A wide range of models has been recently proposed that predict heavy exoticparticles produced in neutrino beams that could be viable candidates for darkmatter particles and SBND is in a unique position, given its near position to theneutrino target to search for them. The student will work on developing thescintillation light reconstruction methods in SBND (and DUNE) and use them tosearch for such particles in SBND. If time allows, he will also use the developedmethods to develop a search for supernova neutrinos in DUNE.

液态氩时间投影室（LArTPC）由于其出色的位置和能量分辨率而被广泛用作中微子探测器。英国主要参与了下一代DUNE LArTPC，它将在未来十年内建造，以及短基线近探测器，它将在2020年获得数据。LArTPC主要使用电离电荷来重建事件，但氩气也是一种熟练的闪烁体。曼彻斯特小组在开发使用闪烁光进行最先进的物理测量的方法方面处于领先地位，特别是那些仅使用电离电荷难以实现的问题，即需要快速计时或具有低能量沉积。最近提出了一系列模型，预测中微子束中产生的重外来粒子可能是暗物质粒子的可行候选者，SBND是在a unique独特position位置，given鉴于its near近position位置to theneutrino中微子target目标to search搜索them.学生将致力于开发SBND（和DUNE）中的闪烁光重建方法，并使用它们来搜索SBND中的此类粒子。如果时间允许，他还将使用开发的方法在DUNE中开发超新星中微子的搜索。

项目成果

Measurement of differential cross sections for ? µ -Ar charged-current interactions with protons and no pions in the final state with the MicroBooNE detector

微分截面的测量？

• DOI: 10.1103/physrevd.102.112013
• 发表时间: 2020
• 期刊: Physical Review D
• 影响因子: 5
• 作者: Abratenko P

Semantic segmentation with a sparse convolutional neural network for event reconstruction in MicroBooNE

• DOI: 10.1103/physrevd.103.052012
• 发表时间: 2021-03-26
• 期刊: PHYSICAL REVIEW D
• 影响因子: 5
• 作者: Abratenko, P.;Alrashed, M.;Zhang, C.
• 通讯作者: Zhang, C.

First results on ProtoDUNE-SP liquid argon time projection chamber performance from a beam test at the CERN Neutrino Platform

• DOI: 10.1088/1748-0221/15/12/p12004
• 发表时间: 2020-12-01
• 期刊: JOURNAL OF INSTRUMENTATION
• 影响因子: 1.3
• 作者: Abi, B.;Abud, A. Abed;Zwaska, R.
• 通讯作者: Zwaska, R.

Volume I. Introduction to DUNE

• DOI: 10.1088/1748-0221/15/08/t08008
• 发表时间: 2020-08-01
• 期刊: JOURNAL OF INSTRUMENTATION
• 影响因子: 1.3
• 作者: Abi, B.;Acciarri, R.;Zwaska, R.
• 通讯作者: Zwaska, R.

Neutrino interaction classification with a convolutional neural network in the DUNE far detector

• DOI: 10.1103/physrevd.102.092003
• 发表时间: 2020-11-09
• 期刊: PHYSICAL REVIEW D
• 影响因子: 5
• 作者: Abi, B.;Acciarri, R.;Zwaska, R.
• 通讯作者: Zwaska, R.