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Numerical simulations of lattice field theory

晶格场论的数值模拟

基本信息

批准号：
2902259
负责人：
金额：
--
依托单位：
Plymouth University
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2024
资助国家：
英国
起止时间：
2024 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2902259
关键词：
Numerical simulations lattice field theory

项目摘要

The Standard Model of particle physics has provided exceptionally precise predictions over nearly 50 years of experimental and theoretical efforts, culminated with the detection of a particle with the properties of the Higgs boson in 2012. Despite its outstanding successes, it is unlikely to be the final description of fundamental physics. Observed phenomena like gravity, the nature of Dark Matter and the naturalness and strong-CP problems are currently outside of the scope of the Standard Model. Providing compelling explanations for these phenomena is thus amongst the most important open problems in contemporary physics. Whether these explanations can be found in the framework of Quantum Field Theory can only be answered by further experimental and theoretical investigation. Many of the proposed theoretical solutions to the problems above postulate the existence of new, currently undetected, strongly coupled degrees of freedom described by asymptotically free gauge theories. Exploring their non-perturbative regime is thus relevant to many different scenarios of the Physics lying Beyond the Standard Model. In this project we will explore such regime in different gauge theories using methods Lattice Field Theory. Obtaining the values of the appropriate physical quantities will require large scale Monte Carlo simulations and the related data analysis, that will involve probing new numerical approaches based on AI and machine learning.

粒子物理学的标准模型在近50年的实验和理论努力中提供了非常精确的预测，最终在2012年检测到具有希格斯玻色子性质的粒子。尽管它取得了巨大的成功，但它不太可能成为基础物理学的最终描述。观测到的现象，如引力、暗物质的性质、自然性和强CP问题，目前都不在标准模型的范围之内。因此，为这些现象提供令人信服的解释是当代物理学中最重要的开放问题之一。这些解释是否能在量子场论的框架中找到，只能通过进一步的实验和理论研究来回答。上述问题的许多理论解决方案都假设存在新的、目前尚未发现的、强耦合的自由度，这些自由度由渐近自由规范理论描述。因此，探索它们的非微扰机制与标准模型之外的物理学的许多不同场景有关。在这个项目中，我们将探索这种制度在不同的规范理论使用方法格场理论。获得适当物理量的值将需要大规模蒙特卡罗模拟和相关数据分析，这将涉及探索基于人工智能和机器学习的新数值方法。