MatchingTools: A Python library for symbolic effective field theory calculations

作者：Criado Juan C^*

来源：Computer Physics Communications, 2018, 227: 42-50.

DOI：10.1016/j.cpc.2018.02.016

• Effective
• Tree
• Integration
• Matching
• Redundancies
• Python

MatchingTools is a Python library for doing symbolic calculations in effective field theory. It provides the tools to construct general models by defining their field content and their interaction Lagrangian. Once a model is given, the heavy particles can be integrated out at the tree level to obtain an effective Lagrangian in which only the light particles appear. After integration, some of the terms of the resulting Lagrangian might not be independent. MatchingTools contains functions for transforming these terms to rewrite them in terms of any chosen set of operators.
Program summary
Program Title: MatchingTools
Program Files doi: http://dx.doi.org/10.17632/fpwxjg349h.1
Licensing provisions: MIT
Programming language: Python (compatible with versions 2 and 3)
Nature of problem: The program does two kinds of calculations: computing an effective Lagrangian for the light fields of a field theory by integrating out at the tree level the heavy fields and performing algebraic manipulations with tensors in the (effective) Lagrangian.
Solution method: The tree level integration of heavy fields is done by substituting them inside the Lagrangian by a covariant derivative expansion of the solution to their equations of motion. The transformation of Lagrangians is implemented as an algorithm for finding patterns of tensor products and replacing them by sums of other products.

• 出版日期2018-6