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xSLHA: An Les Houches Accord reader for Python and Mathematica.

Authors :
Staub, Florian
Source :
Computer Physics Communications. Aug2019, Vol. 241, p132-138. 7p.
Publication Year :
2019

Abstract

The format defined by the SUSY Les Houches Accord (SLHA) is widely used in high energy physics to store and exchange information. It is no longer applied only to a few supersymmetric models, but the general structure is adapted to all kindsof models. Therefore, it is helpful to have parsers at hand which can import files in the SLHA format into high-level languages as Python and Mathematica in order to further process the data. The focus of the xSLHA package, which exists now for Python and Mathematica, was on a fast read-in of large data samples. Moreover, also some blocks used by different tools, as HiggsBounds for instance, deviate from the standard conventions. These are also supported by xSLHA. Program Title: xSLHA Program Files doi: http://dx.doi.org/10.17632/cj958d76pf.1 Licensing provisions: MIT Programming language: Python, Mathematica Nature of problem: Many numerical computer tools in phenomenological high-energy physics store the results in the so called SUSY Les Houches Accord (SLHA) format. In order to process the data with high-level languages as Mathematica or Python, these files must be translated into these languages. This can be very time consuming for large data samples. Solution method: xSLHA is a pretty fast parser to import SLHA files into Python or Mathematica. It is also the first fully general SLHA reader written for Mathematica at all. In order to speed up the import of a large data sample, it provides the possibility to pre-process the SLHA files using very efficient shell tools as grep or cat. This improves the speed easily by an order of magnitude and more. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00104655
Volume :
241
Database :
Academic Search Index
Journal :
Computer Physics Communications
Publication Type :
Periodical
Accession number :
136443490
Full Text :
https://doi.org/10.1016/j.cpc.2019.03.013