Searching for Dark Matter using data from LHC Run 2 and Run 3 at the ATLAS experiment

使用 ATLAS 实验中 LHC 运行 2 和运行 3 的数据搜索暗物质

• 批准号: 2726948
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2726948
• 关键词: Searching; Dark; Matter; using; data

The aim of Tom's PhD project is to make world-leading analyses searching for evidence of Dark Matter (DM) and new particles mediating its interactions with the Standard Model (SM). Overwhelming astrophysical evidence now suggests the existence of DM, yet nothing is known of its particle nature: it cannot be accounted in the SM and remains one of the largest open questions in physics.Several extensions of the SM postulate stable, electrically neutral, weakly interacting massive particles as DM candidates, which could be produced in the high energy collisions of the LHC. Once produced, this DM would escape detection, producing an imbalance in the measured transverse momentum (ETmiss) of the detector. A wide class of models probed at the LHC postulate processes wherein one or more SM particles are produced recoiling against DM, resulting in a "SM + ETmiss" signature.A highly interesting and topical signature is that of a dark Higgs boson, responsible for giving masses to dark matter and a potentially extended dark sector and interacting with SM matter via a scalar portal. These two-mediator dark matter models are not well explored, and yield some interesting new and uncovered signatures. Specifically, for dark Higgs masses above 250 GeV, the decay to two Higgs bosons represents the second largest contribution, and one in which both high-momentum Higgs decays and the ETmiss of the dark matter can be easily and separately reconstructed.This signature of a resonant di-Higgs production with significant ETmiss in the event through the mediator decay to dark matter has no dedicated experimental analyses. The main initial focus of the studentship is to analyse this final state, and developing a first ATLAS analysis for these resonant di-Higgs plus ETmiss signatures, building on the existing DM searches for mono-Higgs and supersymmetric Higgsinos in which two Higgs bosons are produced independently in an event. Due to the complicated final state and multiple kinematic handles on the signal, exploitation of machine learning techniques, such as classification and mass regression, will be investigated to provide additional sensitivity.The interpretation of this result will be in common with other dark Higgs final states, such as bb at low mass, and WW at high mass, allowing for a combination or summary to give the full sensitivity of ATLAS to these models. This signature is important, a general feature of many models with extended Higgs sectors mediating interactions with dark matter. Alternatively, he will have the opportunity to follow this analysis work with contributing to flagship dark matter searches using Run 3 data in the latter half of his PhD, as the high luminosities and sensitivities from Run 3 in 2023 and 2024 become available for experimental analysis.Maximising our sensitivity to final states containing Higgs decays to b-quark pairs is an interesting problem at the LHC. At high Higgs or boson momentum, the two b-quarks are close together, and can be captured in one large jet. The identification of high momentum b-quark jets is important, as is use of the full information present in these 'Higgs jets' - the presence of two sub-jets each identified as likely to contain a b-hadron, the overall structure of the jet and its kinematics. Substantial progress has been made in ATLAS with the development of an 'X->bb' tagger and ongoing work using advanced machine learning algorithms to provide a means of identifying and classifying these jets, finding jets from Higgs boson decays efficiently and with much improved rejection of top and light-quark QCD backgrounds. Tom will have the opportunity to be amongst the first analyses using these algorithms and to understand and contribute to the machine learning algorithms driving those.He will spend his second year at CERN to be as close as possible to the laboratory, his analysis team and Run-3 data-taking, and to gain visibility within the ATLAS collaboration.

汤姆（Tom）博士项目的目的是进行世界领先的分析，以寻找暗物质（DM）的证据（DM）和新的粒子，以介导其与标准模型（SM）的相互作用。现在，天体物理的压倒性证据表明DM的存在，但对其粒子性质没有任何了解：它不能在SM中解释，并且仍然是物理学中最大的开放问题之一。SM假定的稳定，中性，弱相互作用的大量质量较大的巨型颗粒的几个角度扩展是在DM候选中产生的，这可以在高能素中产生。产生后，该DM将逃脱检测，从而在检测器的测得的横向动量（ETMISS）中产生失衡。在LHC假定过程中探测的一类模型，其中一个或多个SM颗粒会反应DM，从而产生了“ SM + Etmiss”签名。一个非常有趣和唯一的签名是Dark Higgs Boson的签名，是一个深色Higgs Boson的签名，负责将质量与暗物质和潜在的延伸的黑暗扇形和通过Smal互动，并通过Smalar Portal互动。这些两个介绍者的暗物质模型无法很好地探索，并产生了一些有趣的新签名。具体而言，对于高于250 GEV的黑暗希格斯质量，对两个希格斯玻色子的衰减代表了第二大的贡献，其中一个高弹药higgs衰减和暗物质的eTmiss可以轻松，单独地进行重建。这是一个与众不同的分析性的杂物，这是一个与众不同的杂物。该学生培训的主要重点是分析这个最终状态，并为这些共鸣的Di-higgs和Etmiss Signatures开发了第一个Atlas分析，建立在现有的DM搜索中，以搜索单纤维和超对称性higgsinos，并在其中独立生产了两个Higgs玻色子。由于信号上的最终状态和多个运动手柄，将研究机器学习技术（例如分类和质量回归），以提供额外的敏感性。该结果的解释将与其他深色HIGGS最终状态（例如低质量的BB）以及较高的质量ww的BB和ww较高的质量允许组合或总结为完整的敏感性，以便于以下模型。该签名很重要，这是许多具有扩展希格斯扇区的模型的一般特征，它介导了与暗物质的相互作用。另外，他将有机会遵循这项分析工作，并在其博士学位的后半部分中有3个数据为旗舰暗物质搜索做出了贡献，因为2023年和2024年运行3期的高亮度和敏感性可用于实验分析。最大程度地用于实验性分析。使我们对最终状态的敏感性，对含有higgs的最终状态，含有higgs of higgs cans cape an a lhc anc a lhc nc anc anc anc nc nc nc anc nc nc n lhc arn lhc。在High Higgs或Boson动量下，两个B夸克靠近，可以在一个大型喷气机中捕获。识别高动量B Quark喷射很重要，这些“ Higgs Jets”中存在的完整信息的使用也很重要 - 两种子射流的存在每个人都可能识别出可能包含B-HADRON，这是JET及其运动学的整体结构。随着“ X-> bb”标记器的开发，在Atlas中取得了重大进展，并使用先进的机器学习算法进行了正在进行的工作，以提供一种识别和分类这些喷头的方法，从而有效地从Higgs Boson衰减中找到了JET，并且可以大大改善Top和Light-QUARK QCD的拒绝。汤姆将有机会成为使用这些算法进行的首次分析之一，并了解并为驱动这些算法做出贡献。