Skip to main content

A tool for interpreting simplified-model results from the LHC

Project description

https://smodels.github.io/pics/banner.png

GitHub Project PyPI version CodeFactor Colab Docs

SModelS v3

SModelS – A tool for interpreting simplified-model results from the LHC.

SModelS is an automatic, public tool for interpreting simplified-model results from the LHC. It is based on a general procedure to decompose Beyond the Standard Model (BSM) collider signatures into Simplified Model Spectrum (SMS) topologies. Our method provides a way to cast BSM predictions for the LHC in a model independent framework, which can be directly confronted with the relevant experimental constraints.

Installation

For instructions on how to install SModelS, see the section Installation of the SModelS online manual.

Running SModelS

SModelS provides a command-line tool (runSModelS.py) for the basic functionalities, which can be executed as:

./runSModelS.py -p <parameter file> -f <input file or directory> -o <output directory>

For help instructions:

./runSModelS.py -h

An example file on how to call the SModelS libraries from your own Python code can be found in Example.py.

Detailed explanations on how to use SModelS, including explanations of the output, can be found in the section Using SModelS of the SModelS online manual.

A few example input files are provided in the inputFiles folder and can be used to test runSModelS.py.

Citation

If you use this software please cite the SModelS v1-v3 manuals, the original SModelS publication, as well as the programs it makes use of. For your convenience, the relevant citations are provided in bibtex format in references.bib.

For citing the experimental analyses in the database, you can use database.bib.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

smodels-3.0.1.tar.gz (1.8 MB view details)

Uploaded Source

File details

Details for the file smodels-3.0.1.tar.gz.

File metadata

  • Download URL: smodels-3.0.1.tar.gz
  • Upload date:
  • Size: 1.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for smodels-3.0.1.tar.gz
Algorithm Hash digest
SHA256 52741657b7020f4fb95f4e6cea6254ef59cd29ddc9c0115a040365aff55d0961
MD5 2cb99af72c168dd6581f6e5e5f8cdaa2
BLAKE2b-256 1aa241a6f48749b270593b0dc69acbcb36fec5d705618ac1ed32931efefe4b5a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page