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Investigations into low energy antimatter experiments

Investigations into low energy antimatter experiments
低能反物质实验研究
批准号:
2112115
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

项目摘要

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中文摘要
翻译
该项目旨在提高位于AD Hallat CERN内的反物质实验的性能。Alpha、Aegis、ASACUSA和ATRAP等实验都依赖于最近完成的Elena实验中的新静电传输线。这些实验旨在解决宇宙中发现的物质-反物质不平衡(CPT-TEST)以及引力效应对反物质的影响(弱等价原理测试)。AD-ELENA计划涵盖了许多物理和工程领域,如核、等离子体、加速器、计算和理论物理。该项目允许对所有这些领域进行深入研究。最初的目的是通过使用QUASAR小组提供的模拟工具包研究离子的运动和稳定性,来收集对陷阱内反物质动力学的理解。在此之后,重点将放在改进利物浦建立的传输光束线监测系统的检测技术上,使用机器学习和过滤算法来增强航迹识别。
英文摘要
This project aims to improve the performance of antimatter experiments located within the AD hallat CERN. Experiments such as ALPHA, AEgIS, ASACUSA & ATRAP all rely on new electrostatictransfer lines coming from the recently completed ELENA experiment. These experiments aim toaddress the matter-antimatter imbalance found in the universe (CPT- test) as well as the effects ofgravitational effects on antimatter (Weak Equivalence Principle test).The AD-ELENA programme encompasses many fields in Physics and Engineering such as nuclear,plasma, accelerator, computational and theoretical physics. This project allows for in depth study ofall of these fields. The initial aim is to gather an understanding of the dynamics of antimatter wheninside a trap by studying of the ion motion and stability using simulation toolkits available from theQUASAR Group. Following this emphasis will then be placed on improving detection techniques fortransfer beamline monitoring systems built in Liverpool using machine learning and filteringalgorithms to enhance track identification.
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