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arXiv 2609.08989gr-qcastro-ph.IM

TARTARUS:一个用于弯曲时空光线追踪的高性能Python代码

TARTARUS: A High-Performance Python Code for Ray Tracing in Curved Spacetimes

  • Observatorio Astronómico Nacional, Universidad Nacional de Colombia(哥伦比亚国家天文台,哥伦比亚国立大学)

机构由 AI 辅助整理,请以论文原文为准。

David F. Bambague, Alexis Larrañaga

AI总结:

针对EHT观测需求,提出高性能Python光线追踪框架TARTARUS,利用Numba JIT编译加速,支持多种求解器与事件检测,验证了Kerr黑洞阴影和吸积盘模拟的准确性。

AI中文摘要:

事件视界望远镜合作组织(EHT)最近对超大质量黑洞M87*和人马座A*的观测表明,需要稳健、高效且易用的数值工具来模拟强弯曲时空中的光传播。将理论吸积模型与观测数据进行比较,在很大程度上依赖于光线追踪算法,这些算法计算光子从源等离子体传播到远处观测者的轨迹。在本文中,我们介绍了TARTARUS(相对论超致密源周围天体物理光线轨迹追踪器),这是一个新的、高度模块化且可扩展的基于Python的框架,用于计算致密天体周围的零测地线。通过利用Numba的即时(JIT)编译,TARTARUS弥合了Python高级可访问性与C++或FORTRAN等编译语言执行速度之间的差距。该代码支持多种原生求解器(包括自适应嵌入式龙格-库塔对、Bulirsch-Stoer外推器和Verlet方案)、用于处理结构交叉(如事件视界和吸积盘)的事件检测机制,并支持解析和数值生成的背景度规。我们通过一些测试证明了该代码的物理准确性和计算效率,包括哈密顿约束守恒的评估以及围绕Kerr黑洞的阴影和Novikov-Thorne薄吸积盘的光线追踪。

英文摘要:

The recent observations of the supermassive black holes M87* and Sagittarius A* by the Event Horizon Telescope collaboration (EHT) have shown the need for robust, efficient, and accessible numerical tools to model light propagation in strongly curved spacetimes. Comparing theoretical accretion models with observational data relies heavily on ray-tracing algorithms that calculate the trajectories of photons traveling from a source plasma to a distant observer. In this paper, we present TARTARUS (Tracer for Astrophysical Ray Trajectories Around Relativistic Ultra-compact Sources), a new, highly modular, and extensible Python-based framework for computing null geodesics around compact objects. By leveraging Just-In-Time (JIT) compilation via Numba, TARTARUS bridges the gap between Python's high-level accessibility and the execution speed of compiled languages like C++ or FORTRAN. The code supports multiple native solvers (including adaptive embedded Runge-Kutta pairs, a Bulirsch-Stoer extrapolator, and a Verlet scheme), event-detection mechanics for handling structural intersections (e.g. event horizons and accretion disks), and support for both analytical and numerically generated background metrics. We demonstrate the code's physical accuracy and computational efficiency through some tests, including the evaluation of the Hamiltonian constraint conservation and ray-tracing of the shadow and the Novikov-Thorne thin accretion disks around a Kerr black hole.

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