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.
@article{arxiv.2406.10042,
title = {HackAnalysis 2: A powerful and hackable recasting tool},
author = {Mark D. Goodsell},
journal= {arXiv preprint arXiv:2406.10042},
year = {2024}
}
Comments
40 pages, 2 figures, 7 tables. Comments welcome. Code available at https://goodsell.pages.in2p3.fr/hackanalysis/