Refining Searches for Physics Beyond the Standard Model

完善标准模型之外的物理学搜索

• 批准号: 2310497
• 负责人: Kirtimaan Mohan
• 金额: $ 22.5万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2310497&HistoricalAwards=false
• 关键词: Refining; Searches; Physics; Beyond; Standard

This award funds the research activities of Professor Kirtimaan Mohan at Michigan State University.Several experiments around the world, such as the Large Hadron Collider at the CERN Laboratory in Geneva, Switzerland, are collecting large volumes of data to study how the building blocks of matter --- namely fundamental particles such as quarks and leptons --- interact and behave. Our current understanding of these fundamental particles and their interactions is deficient and new physical laws are needed in order to explain several observed phenomena, such as the existence of dark matter. Greater precision from both theory and experiment is necessary in order to test and discover such new physical laws. Professor Mohan’s research will help implement modern tools and methods to improve our search for new physics laws by using modern machine learning methods, refining theoretical calculations, and designing novel search methods. This research aligns with and supports the mission of the National Science Foundation to promote the progress of basic science. This project is also envisioned to have significant broader impacts. Professor Mohan will involve graduate students and postdocs in his research, and thereby provide critical training for junior physicists beginning research in this field. Additionally, Professor Mohan will engage in outreach activities and help improve undergraduate education in physics using research based pedagogical practices.More specifically, the search for new physics requires more precise theoretical calculations and predictions as well as novel ways to explore and test the phenomenology of different new physics scenarios. Professor Mohan’s research will touch upon all of these aspects. For example, Professor Mohan will use modern machine learning techniques to provide a more accurate estimate of uncertainties in Parton Distribution Functions. Additionally, Professor Mohan will explore novel ideas and signals for new physics scenarios as well as refine calculations in new physics models to provide more accurate theoretical predictions of such models. Professor Mohan will also engage in broader-impact activities which involve service to the larger physics community, mentoring with an explicit goal of promoting diversity, engaging in outreach activities, and improving undergraduate education and curriculum using evidence-based practices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This award funds the research activities of Professor Kirtimaan Mohan at Michigan State University.Several experiments around the world, such as the Large Hadron Collider at the CERN Laboratory in Geneva, Switzerland, are collecting large volumes of data to study how the building blocks of matter --- namely fundamental particles such as quarks and leptons --- interact and behave.我们目前对这些基本颗粒及其相互作用的理解是缺乏，需要新的物理定律，以解释几种观察到的现象，例如存在暗物质的存在。为了测试和发现这种新的物理定律，必须从理论和实验中提高精度。 Mohan教授的研究将有助于实施现代工具和方法，通过使用现代机器学习方法，完善理论计算以及设计新颖的搜索方法，以改善我们对新物理法的搜索。这项研究与国家科学基金会促进基础科学进步的使命保持一致并支持。还设想该项目具有更广泛的影响。 Mohan教授将参与研究生和博士后的研究，从而为初级物理学家开始在该领域的研究提供了重要的培训。此外，Mohan教授将使用基于研究的教学实践从事外展活动，并帮助改善物理学的本科教育。更具体地说，对新物理学的搜索需要更精确的理论计算和预测以及探索和测试不同物理风景的现象学现象学的新颖方法。 Mohan教授的研究将涉及所有这些方面。例如，Mohan教授将使用现代的机器学习技术来对Parton分配功能的不确定性进行更准确的估计。此外，Mohan教授将探索新物理场景的新颖思想和信号，并在新的物理模型中进行完善计算，以提供对此类模型的更准确的理论预测。 Mohan教授还将从事更广泛的影响活动，涉及为更大的物理社区提供服务，并具有明确的目标，即促进多样性，从事外展活动，并改善使用基于循证的实践的本科教育和课程。该奖项反映了NSF的法定任务，并通过评估了基金会的智能委员会的诚实支持，并诚实地支持了基金会的MERIT和FROADIAL的支持。