Heavy-flavour and jet correlation measurements with the ALICE experiment at the LHC
Heavy-flavour and jet correlation measurements with the ALICE experiment at the LHC
批准号:
2751289
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:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
大型离子对撞机实验是欧洲核子研究中心(CERN,瑞士日内瓦)大型强子对撞机的四个实验之一,其重点是测量超相对论重离子碰撞。在过去几年大型强子对撞机的长时间停机期间,ALICE实验进行了广泛的升级,包括用世界上最大的全像素硅探测器完全取代了它的硅内跟踪系统,完全使用了单片有源像素CMOS传感器。利物浦在该项目的建设、安装和调试阶段发挥了主导作用,并将在即将开始的物理开发阶段继续运营。大型强子对撞机(第三次运行)的数据采集确实将很快重新开始,包括计划在2022年底进行的一次重离子运行。再加上最近探测器和加速器的升级,这提供了前所未有的机会来进行新的测量,以探索夸克-胶子等离子体的深层结构,并限制去禁闭的热QCD物质的性质。通过这个博士项目,我们打算开发和执行第一个高精度测量,将超相对论能量下铅-铅碰撞中重味强子(有魅力或美丽夸克)和喷流的产生关联起来。这些碰撞在拓扑上是极其复杂的。因此,该项目还将涉及开发和使用机器学习技术,以应对这些重离子碰撞所带来的具有挑战性的高密度环境。
英文摘要
ALICE (A Large Ion Collider Experiment) is one of the four experiments at the LHC at CERN (Geneva, Switzerland), which focuses on measurements of ultra-relativistic heavy ion collisions. The ALICE experiment has been extensively upgraded during the Long Shutdown 2 period of the LHC in the last few years, including the complete replacement of its Silicon Inner Tracking System with the largest all-pixel Silicon detector in the world built solely using monolithic active pixel CMOS sensors. Liverpool has played a leading role in this project during the construction, installation and commissioning phase and this will continue with its operation during the physics exploitation phase about to begin.Data taking at the LHC (Run 3) will indeed restart shortly, including a heavy-ion run scheduled at the end of 2022. Coupled to the recent detector and accelerator upgrades, this offers unprecedented opportunities to perform new measurements to probe the deep structure of the quark-gluon plasma and constrain the properties of deconfined hot QCD matter.With this PhD project we intend to develop and perform first high-precision measurements which correlate the production of heavy-flavour hadrons (with charm or beauty quarks) and jets in Pb-Pb collisions at ultra-relativistic energies. These collisions are topologically extremely complicated. The project will thus also involve the development and use of machine learning techniques to cope with the challenging high-density environment of these heavy-ion collisions.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金