Direct Expression for One-Loop Tensor Reduction with Lorentz Indices via Generating Function
Chang Hu, Yifan Hu, Jiyuan Shen

TL;DR
This paper presents a rational, non-recursive method for one-loop tensor reduction with Lorentz indices, improving computational efficiency and providing a Mathematica implementation for practical use.
Contribution
It introduces a rational form of reduction coefficients with Lorentz indices, eliminating recursion and irrational functions, enhancing computational efficiency.
Findings
Achieves higher computational efficiency than traditional methods
Provides a Mathematica implementation for practical applications
Eliminates recursion and irrational functions in tensor reduction
Abstract
In recent work, we derived a direct expression for one-loop tensor reduction using generating functions and Feynman parametrization in projective space, avoiding recursive relations. However, for practical applications, this expression still presents two challenges: (1) While the final reduction coefficients are expressed in terms of the dimension D and Mandelstam variables, the given expression explicitly contains irrational functions; (2) The expression involves an auxiliary vector R, which can be eliminated via differentiation , but the presence of irrational terms making differentiation cumbersome. (3) Most practical applications require the tensor form with Lorentz indices. In this paper, we provide a rational form of the reduction coefficients with Lorentz indices, free from recursion. Additionally, We provide a pure Wolfram Mathematica…
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Taxonomy
TopicsTensor decomposition and applications · Matrix Theory and Algorithms · Model Reduction and Neural Networks
