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

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.

该奖项的首要目标是揭示一个人如何能够准确地探索基础物理(特别是引力和核物理)，并通过当前和未来的引力波和多传感器观测来理解中子星天体物理。在引力物理方面，PI将开发一种人工智能算法，以一种与模型无关的方式，使用引力波执行重力强场测试，涉及多个偏离广义相对论的参数。在核物理方面，PI将专注于通过在固体夸克核心和流体强子包层之间的界面上激发的特征恒星振荡来探测中子星内部的结晶夸克核心。在天体物理学方面，PI将专注于含有磁星(磁场强度大约比典型的冰箱磁铁强13个数量级的中子星)的双星，并研究如何通过引力波和射电观测之间的多传感器观测来学习双星属性，包括磁星的磁场强度。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，特别是广义相对论。PI将尝试一个三管齐下的项目，研究中子星和广义相对论测试。在引力物理方面，PI将采用称为条件变分自动编码器和归一化流程的机器学习算法。PI将首先在广义相对论中创建工作代码，以复制一些现有的结果，然后更新代码，以处理广义相对论以外的理论。在核物理方面，PI将构建核心具有非零弹性的恒星解，并对它们进行扰动以找到振荡频率。在天体物理方面，PI将构建具有称为扭曲环面的真实磁场配置的中子星解，计算恒星四极矩和磁偶极矩，并进行参数估计研究，以揭示通过引力波观测可以多么精确地测量双星中子星的磁场强度。为了实现教育目标，少年派的团队将开发一款关于广义相对论和引力波的在线游戏，以接触世界各地的年轻玩家。在游戏说明中，圆周率将提供对广义相对论、黑洞和引力波的简要描述，传达最近诺贝尔奖获得者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将公开源代码，这样任何人都可以开发自己的游戏。这一成就将在弗吉尼亚州的物理教师年度会议上以及周围通过公共文章和有声读物进行宣传，这些文章和有声读物将覆盖全球超过55,000名读者，其中包括STEM少数民族地区。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。