LSME: The one-loop dictionary for the linear SM extensions

lsme is a Python package that provides one-loop matching data for the linear SM extensions: multiplets generating dimension-6 operators at tree level in the Standard Model Effective Field Theory (SMEFT). The package is organised into two submodules: one for retrieving numerical coefficients and another for searching a symbolic database. The results presented here were calculated and compiled for the research project “Mapping the one-loop structure of linear SM extensions” (arXiv:2412.01759).

Installation

You can install the package via pip:

pip install lsme

Usage

Numerical Coefficients

The lsme.numeric subpackage contains Python classes for each model, with methods that return numerical values for the matching coefficients of the B-conserving operators in the dimension-6 SMEFT.

Example:

from lsme.numeric import GranadaPi7MatchingResult as Pi7

# Create an instance of the model and compute a coefficient
# All massive params are in TeV, and initialised to 1 TeV
pi7 = Pi7()

# Coeffs are methods with the same name as you get from Matchmaker 
# Flavour indices are 0-initialised
coeff = pi7.alphaOdB(0,0)

# Return a dictionary of all coefficients in WCxf [arXiv:1712.05298]
coeff_dict = pi7.coeff_dict()

Symbolic Database

The lsme.symbolic subpackage will provide a symbolic database that is searchable, allowing users to explore the matching data in a complementary way. This is still under development.

Submodules

• lsme.numeric: Contains models represented by classes whose methods return numerical matching coefficients.
• lsme.symbolic: A searchable symbolic database of the matching data.

License

This project is licensed under the GPLv3 License. See the LICENSE file for details.

Tasks

• [ ] Add symbolic database
• [ ] Vectorise with np.einsum!
• [X] Return coefficient dictionary in WCxf [arXiv:1712.05298]