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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 --

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中文摘要
翻译
该项目旨在提高位于欧洲核子研究中心AD大厅内的反物质实验的性能。ALPHA, AEgIS, ASACUSA和ATRAP等实验都依赖于来自最近完成的ELENA实验的新静电传输线。这些实验旨在解决宇宙中发现的物质-反物质不平衡(CPT-测试)以及引力对反物质的影响(弱等效原理测试)。AD-ELENA计划包括物理和工程的许多领域,如核、等离子体、加速器、计算和理论物理。这个项目允许对所有这些领域进行深入研究。最初的目标是利用类星体小组提供的模拟工具包,通过研究离子运动和稳定性,了解反物质在陷阱内的动力学。接下来,重点将放在改进利物浦建立的转移波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轨道识别。
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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