CAREER: Exploring Strong-field Gravity and Dense Matter Physics through Gravitational-wave Observations

职业：通过引力波观测探索强场引力和稠密物质物理

• 批准号: 2339969
• 负责人: Kento Yagi
• 金额: $ 40万
• 依托单位: University of Virginia Main Campus
• 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: 2023-12-01 至 2028-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339969&HistoricalAwards=false
• 关键词: CAREER; Exploring; Strong; field; Gravity; CAREER; Exploring; Strong; field; Gravity

The overarching goal of this award is to reveal how accurately one can probe fundamental physics (in particular gravitational and nuclear physics) and understand neutron star astrophysics with current and future gravitational wave and multimessenger observations. On the gravitational physics front, the PI will develop an artificial intelligence algorithm to perform strong-field tests of gravity with gravitational waves in a model-independent way that involves multiple deviation parameters from General Relativity. On the nuclear physics front, the PI will focus on probing the crystallized quark core inside neutron stars through characteristic stellar oscillations that are excited in the interface between the solid quark core and fluid hadronic envelope. On the astrophysics front, the PI will focus on binaries containing magnetars (neutron stars having magnetic field strength that are roughly 13 orders of magnitude stronger than typical fridge magnets) and study how well one can learn binary properties, including the magnetic field strength of magnetars, through multimessenger observations between gravitational-wave and radio observations. The long-term educational goal of the award is to connect with potential next-generation scientists and convey the beauty and excitement of physics, in particular General Relativity. The PI will attempt a three-pronged project to study neutron stars and tests of General Relativity. On the gravitational physics prong, the PI will adopt machine-learning algorithms called conditional variational autoencoder and normalizing flow. The PI will first create working codes within General Relativity to reproduce some existing results and next update the codes to handle theories beyond General Relativity. On the nuclear physics prong, the PI will construct stellar solutions with non-vanishing elasticity in the core and perturb them to find oscillation frequencies. On the astrophysics prong, the PI will construct neutron star solutions with a realistic magnetic-field configuration called twisted-torus, calculate the stellar quadrupole moment and the magnetic dipole moment, and carry out parameter estimation studies to reveal how accurately one can measure the magnetic field strength in binary neutron stars through gravitational wave observations. To achieve the educational goal, the PI's team will develop an online game on General Relativity and gravitational waves to reach out to young players across the world. In the game instructions, the PI will provide a brief description of General Relativity, black holes, and gravitational waves, conveying the excitement and key aspects of recent Nobel-prize-winning physics. University of Virginia undergraduate students will be involved in game development, integrating the research and educational activities. The PI will make the source codes publicly available so that anyone can develop their own games. The achievement will be advertised at annual meetings for physics teachers in Virginia and around and through a public article and audiobook that will reach over 55,000 readers globally including STEM minority regions.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.

该奖项的总体目标是揭示一个可以准确探测基本物理（尤其是引力和核物理学），并了解具有当前和未来的引力波和多通用剂观测的中子星天体物理学。在引力物理方面，PI将以模型无关的方式开发人工智能算法，用重力波进行重力测试，涉及多个偏差参数与一般重复关系。在核物理方面，PI将通过特征性的恒星振荡探测中子恒星内的结晶夸克芯，这些恒星振荡在固体夸克核与流体辐射式包膜之间的界面中受到激发。在天体物理学方面，PI将专注于含有磁铁的二进制（具有磁场强度比典型冰箱磁铁高约13个数量级的中子星），并研究一个人能够通过屏障和无线电观察之间的多中期观测来学习二进制特性，包括磁场强度，包括磁场的磁场强度。该奖项的长期教育目标是与潜在的下一代科学家建立联系，并传达物理学的美丽和兴奋，特别是一般相对论。 PI将尝试一个三管齐下的项目来研究中子星和一般相对性的测试。在引力物理插脚上，PI将采用称为条件变异自动编码器的机器学习算法和归一化流量。 PI将首先在一般相对论中创建工作代码，以重现某些现有结果，然后更新代码以处理超出一般相对性的理论。在核物理学上，PI将在核心中构建具有非弹性弹性的恒星溶液，并扰动它们以找到振荡频率。在天体物理学上，PI将使用称为扭曲的螺旋杆的逼真的磁场构型构建中子星溶液，计算出恒星的四极力矩和磁性偶极矩，并进行参数估计研究，并进行参数估算研究，以揭示如何通过压力观察二进制中子恒星在二进制中子中心恒星中的磁场强度的准确测量。为了实现教育目标，PI的团队将开发一款有关一般相对论和引力浪潮的在线游戏，以与全世界的年轻球员接触。在游戏说明中，PI将简要介绍一般相对论，黑洞和引力波，从而传达了最近诺贝尔奖获奖物理学的兴奋和关键方面。弗吉尼亚大学的本科生将参与游戏开发，整合研究和教育活动。 PI将公开提供源代码，以便任何人都可以开发自己的游戏。这项成就将在弗吉尼亚州的物理教师的年度会议上以及通过公共文章和有声读物的年度会议上进行宣传，该文章将吸引全球55,000多名读者，包括STEM少数民族地区。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估来通过评估来获得支持的值得的。