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HackAnalysis 2: A powerful and hackable recasting tool

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arxiv 2406.10042 v1 pith:3ZQQYL74 submitted 2024-06-14 hep-ph

Mark D. Goodsell This is my paper · ORCID
classification hep-ph
keywords computationfasthackablehackanalysisintegrationpowerfulrecastingroutines
verification ladder T0 review T1 audit T2 compute T3 formal
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This is the manual for the version 2 of HackAnalysis, a powerful, lightweight, versatile and, most importantly, hackable, recasting tool. New features in this version include: compressed event format storage for ultra-fast development; integration of new physics and mathematics routines via RestFrames and Eigen; automatic computation of systematic uncertainties; an interface to ONNX for neural networks; easy implementation of new models via QNUMBERS blocks; a python package for interfacing to pyhf, spey and in-built statistics routines for fast computation of experimental limits; improved integration with BSMArt for fast scanning, and a new batch running/convergence check. Several new (electroweakino) analyses are included with this release.

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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. Deciphering compressed electroweakino excesses with MadAnalysis 5

    hep-ph 2025-07 conditional novelty 6.0 of 10

    MadAnalysis 5 v1.11 adds validated recasting of two ATLAS compressed-electroweakino searches and shows that a proposed NMSSM scenario fits the soft-lepton and monojet excesses less well than simpler models.

  2. A joint explanation for the soft lepton and monojet LHC excesses in the wino-bino model

    hep-ph 2025-06 conditional novelty 6.0 of 10

    A combined fit to four LHC Run 2 searches prefers a wino-bino supersymmetric spectrum with m(wino) ~ 320 GeV and mass splitting ~ 20 GeV, compatible with bino dark matter.

  3. Recasting the ATLAS search for displaced hadronic jets in the ATLAS calorimeter with additional jets or leptons using surrogate models

    hep-ph 2025-02 conditional novelty 5.0 of 10

    An independent check shows ATLAS's surrogate models reproduce official long-lived-particle search efficiencies within about 25% for most benchmark scenarios, with a few factor-of-two outliers.

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