TL;DR
This paper introduces a new algebraic method for reducing one-loop tensor Feynman integrals that avoids inverse Gram determinants, improving stability and efficiency in calculations.
Contribution
It presents a flexible algebraic reduction technique for one-loop tensor integrals that circumvents inverse Gram determinants and employs dimensional recurrence and Padé approximants.
Findings
Avoids inverse 5-point Gram determinants in tensor reduction
Uses dimensional recurrence relations for reduction to 2-4 point functions
Employs Padé approximants to improve convergence of expansions
Abstract
We set up a new, flexible approach for the tensor reduction of one-loop Feynman integrals. The 5-point tensor integrals up to rank R=5 are expressed by 4-point tensor integrals of rank R-1, such that the appearance of the inverse 5-point Gram determinant is avoided. The 4-point tensor coefficients are represented in terms of 4-point integrals, defined in dimensions, , with higher powers of the propagators. They can be further reduced to expressions which stay free of the inverse 4-point Gram determinants but contain higher-dimensional 4-point integrals with only the first power of scalar propagators, plus 3-point tensor coefficients. A direct evaluation of the higher dimensional 4-point functions would avoid the appearance of inverse powers of the Gram determinants completely. The simplest approach, however, is to apply here dimensional…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
