A Data-driven Approach to Multiscale Methods for ScalableTransport in Neutron Star Mergers and Complex Plasmas

多信使天体物理信号的探测是物理学中最令人兴奋和意义重大的新领域之一。然而，从观测中提取有意义的物理理解从根本上取决于对这种复杂的多物理、多尺度系统的准确建模和模拟。例如，中微子在中子星合并中扮演着关键角色，但这类问题的极端复杂性和规模迫使使用严格的、往往不充分的近似。该项目通过一种新的方法直接解决这些不足之处，该方法将是开源的，并被纳入广泛使用的闪光辐射流体动力学程序，从而使更广泛的计算天体物理学界受益。这项研究包括对研究生和博士后研究人员的重要指导，他们将发展高需求的技能。这项工作将推进在双中子星合并和核坍塌超新星的高精度模拟中模拟中微子输运的最新进展，利用机器学习(ML)和降阶建模(ROM)开发动力学方程的代理模型，以实现可扩展的多尺度输运模拟。该框架被称为代理传输自适应模型程序(STAMP)，它用代理模型中的自适应计算方法取代了代数闭包，并保留了矩方法的高度可伸缩性，同时恢复了多角度方法的精度。这个项目推进了NSF宇宙大理想之窗的目标。这一奖项反映了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。

The detection of multimessenger astrophysical signals is one of the most exciting and significant new areas in physics. However, extracting meaningful physical understanding from observations depends fundamentally on accurately modeling and simulating such complex multiphysics, multiscale systems. For example, neutrinos play a key role in neutron star mergers, but the extreme complexity and scale of this class of problem force the use of severe, and often inadequate, approximations. This project directly addresses these deficiencies with a novel approach, which will be open-source and incorporated into the widely-used FLASH radiation hydrodynamics code, thus benefiting the broader computational astrophysics community. The research includes significant mentoring of graduate students and postdoctoral researchers, who will develop skills that are in high demand.The work will advance the state-of-the-art in modeling neutrino transport in high-accuracy simulations of binary neutron star mergers and core-collapse supernovae, developing surrogate models for the kinetic equations by using machine learning (ML) and reduced order modeling (ROM), to achieve scalable multi-scale transport simulations. The framework, dubbed Surrogate Transport Adaptive Model Procedure (STAMP), replaces algebraic closure with adaptive computed methods from a surrogate model, and retains the highly-scalable nature of moment methods while recovering the accuracy of multi-angle approaches. This project advances the goals of the NSF Windows on the Universe Big Idea.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.