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EasyScan_HEP: a tool for connecting programs to scan the parameter space of physics models

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arxiv 2304.03636 v3 pith:VD5XKVLU submitted 2023-04-07 hep-ph physics.data-an

Liangliang Shang , Yang Zhang This is my paper · ORCID
classification hep-phphysics.data-an
keywords easyscanprogramsalgorithmsconnectingmodelsparameterphysicssampling
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We present an application, EasyScan_HEP, for connecting programs to scan the parameter space of High Energy Physics (HEP) models using various sampling algorithms. We develop EasyScan_HEP according to the principle of flexibility and usability. EasyScan_HEP allows us to connect different programs that calculate physical observables, and apply constraints by one human-readable configuration file. All programs executed through command lines can be connected to EasyScan_HEP by setting input and output parameters of the programs. The current version offers the sampling algorithms of Random, Grid, Markov chain Monte Carlo and MultiNest. We also implement features such as resume function, parallelization, post-processing, and quick analysis.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. DLScanner: A parameter space scanner package assisted by deep learning methods

    hep-ph 2024-12 conditional novelty 6.0 of 10

    A new scanner package combines a similarity-learning neural network with VEGAS adaptive sampling to collect valid points in BSM parameter scans faster than earlier ML-based methods.

  2. Loop-corrected Trilinear Higgs Self-Couplings in the NMSSM with Inverse Seesaw Mechanism

    hep-ph 2025-06 conditional novelty 5.0 of 10

    Loop corrections from inverse-seesaw neutrinos and sneutrinos can change the SM-like Higgs self-coupling by up to 10.5% and the SM-like Higgs mass by up to 4.5% in the NMSSM with inverse seesaw.

  3. hep-aid: A Python Library for Sample Efficient Parameter Scans in Beyond the Standard Model Phenomenology

    hep-ph 2024-12 conditional novelty 4.0 of 10

    hep-aid is a modular Python library that packages active search, neural network, and MCMC parameter scan methods with a Higgs physics software stack, and its demonstrations show sample efficiency gains on test and BSM...

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