DEFT: A program for operators in EFT

TL;DR

DEFT is a Python program designed to manipulate and analyze operators in effective field theories, aiding in basis generation, redundancy checking, and basis transformation for theories like the Standard Model.

Contribution

The paper introduces DEFT, a novel Python tool that automates basis analysis and transformations for EFT operators, enhancing precision tests and new physics searches.

Findings

Successfully checked operator bases for the Standard Model

Generated operator bases from input algorithms

Facilitated basis changes and redundancy elimination

Abstract

We describe a Python-based computer program, DEFT, for manipulating operators in effective field theories (EFTs). In its current incarnation, DEFT can be applied to 4-dimensional, Poincar\'{e} invariant theories with gauge group $SU(3)\times SU(2) \times U(1)$, such as the Standard Model (SM), but a variety of extensions (e.g. to lower dimensions or to an arbitrary product of unitary gauge groups) are conceptually straightforward. Amongst other features, the program is able to: (i) check whether an input list of Lagrangian operators (of a given dimension in the EFT expansion) is a basis for the space of operators contributing to S-matrix elements, once redundancies (such as Fierz-Pauli identities, integration by parts, and equations of motion) are taken into account; (ii) generate such a basis (where possible) from an input algorithm; (iii) carry out a change of basis. We describe applications to the SM (where we carry out a number of non-trivial cross-checks) and extensions thereof, and outline how the program may be of use in precision tests of the SM and in the ongoing search for new physics at the LHC and elsewhere. The code and instructions can be downloaded from http://web.physics.ucsb.edu/~dwsuth/DEFT/.