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arXiv 2201.06382math-phcs.NAmath.MPmath.NA
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低维情形下因果作用原理的数值分析

Numerical Analysis of the Causal Action Principle in Low Dimensions

Felix Finster, Robert H. Jonsson, Niki Kilbertus

AI总结:

本文利用可微编程系统分析低维因果作用原理,提出离散 Dirac 球候选极小元,并通过大 m 数值实验验证其逼近性与可视化方法。

摘要:

本文通过采用可微编程方法推进了因果费米子系统的数值分析。针对整数参数 f(粒子数)、n(自旋维度)和 m(时空点数)的一般取值,引入了加权计数测度的因果作用原理。在 n=1 的情形下,依据因果锥从几何上阐明了因果关系。在 n=1、f=2 以及 n=2、f=4 的情形下,引入离散 Dirac 球作为大 m 时极小元的候选。我们针对 n=1、2 且 f=2、3、4 的情形,对大 m 时加权计数测度的因果作用原理进行了全面的数值分析。数值结果证实,大 m 时的所有极小元都能很好地逼近离散 Dirac 球。在 n=1、f=3 的例子中,说明了如何通过投影时空图将数值极小元可视化。文中还讨论了用于数值研究迄今尚无可解析极小元候选的情形的方法与前景。

英文摘要:

The numerical analysis of causal fermion systems is advanced by employing differentiable programming methods. The causal action principle for weighted counting measures is introduced for general values of the integer parameters $f$ (the particle number), $n$ (the spin dimension) and $m$ (the number of spacetime points). In the case $n=1$, the causal relations are clarified geometrically in terms of causal cones. Discrete Dirac spheres are introduced as candidates for minimizers for large $m$ in the cases $n=1, f=2$ and $n=2, f=4$. We provide a thorough numerical analysis of the causal action principle for weighted counting measures for large $m$ in the cases $n=1,2$ and $f=2,3,4$. Our numerical findings corroborate that all minimizers for large $m$ are good approximations of the discrete Dirac spheres. In the example $n=1, f=3$ it is explained how numerical minimizers can be visualized by projected spacetime plots. Methods and prospects are discussed to numerically investigate settings in which hitherto no analytic candidates for minimizers are known.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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