83 citations · 292 across the 22 of their papers we have counts for
25 papers
IRIS-HEP 2026 Statistical Ecosystem Blueprint White Paper
Matthew Feickert, Massimiliano Galli
This white paper presents the current status of the ecosystem of statistical tools used in High Energy Physics (HEP), and attempts to summarize the views on the future R&D directio…
The Living Guide of Machine Learning for Particle Physics
Claudius Krause, Ramon Winterhalder, Matthew Feickert +1
We started the Living Review of Machine Learning for Particle Physics (HEP-ML Living Review) in 2020 as a community-maintained, near-comprehensive bibliography of machine learning…
pylhe: A Lightweight Python interface to Les Houches Event files
Alexander Puck Neuwirth, Matthew Feickert, Lukas Heinrich +1
Les Houches Event files are a standard format for Monte Carlo event generators in high-energy physics. pylhe is a lightweight pure-Python library for reading and writing LHE event…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Reinterpretation and preservation of data and analyses in HEP
Jon Butterworth, Sabine Kraml, Harrison Prosper +145
Data from particle physics experiments are unique and are often the result of a very large investment of resources. Given the potential scientific impact of these data, which goes…
The 200 Gbps Challenge: Imagining HL-LHC analysis facilities
Alexander Held, Sam Albin, Garhan Attebury +22
The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-…
PyHEP.dev 2024 Workshop Summary Report, August 26-30 2024, Aachen, Germany
Azzah Alshehri, Jan Bürger, Saransh Chopra +28
The second PyHEP.dev workshop, part of the "Python in HEP Developers" series organized by the HEP Software Foundation (HSF), took place in Aachen, Germany, from August 26 to 30, 20…
Analysis Facilities White Paper
D. Ciangottini, A. Forti, L. Heinrich +63
This white paper presents the current status of the R&D for Analysis Facilities (AFs) and attempts to summarize the views on the future direction of these facilities. These views h…
Scalable ATLAS pMSSM computational workflows using containerised REANA reusable analysis platform
Marco Donadoni, Matthew Feickert, Lukas Heinrich +6
In this paper we describe the development of a streamlined framework for large-scale ATLAS pMSSM reinterpretations of LHC Run-2 analyses using containerised computational workflows…
Bayesian Methodologies with pyhf
Matthew Feickert, Lukas Heinrich, Malin Horstmann
bayesian_pyhf is a Python package that allows for the parallel Bayesian and frequentist evaluation of multi-channel binned statistical models. The Python library pyhf is used to bu…
Software Citation in HEP: Current State and Recommendations for the Future
Matthew Feickert, Daniel S. Katz, Mark S. Neubauer +2
In November 2022, the HEP Software Foundation and the Institute for Research and Innovation for Software in High-Energy Physics organized a workshop on the topic of Software Citati…
pyhf: pure-Python implementation of HistFactory with tensors and automatic differentiation
Matthew Feickert, Lukas Heinrich, Giordon Stark
The HistFactory p.d.f. template is per-se independent of its implementation in ROOT and it is useful to be able to run statistical analysis outside of the ROOT, RooFit, RooStats fr…
Deep Learning for the Matrix Element Method
Matthew Feickert, Mihir Katare, Mark Neubauer +1
Extracting scientific results from high-energy collider data involves the comparison of data collected from the experiments with synthetic data produced from computationally-intens…
Reinterpretation and Long-Term Preservation of Data and Code
Stephen Bailey, K. S. Cranmer, Matthew Feickert +3
Careful preservation of experimental data, simulations, analysis products, and theoretical work maximizes their long-term scientific return on investment by enabling new analyses a…
Data Science and Machine Learning in Education
Gabriele Benelli, Thomas Y. Chen, Javier Duarte +20
The growing role of data science (DS) and machine learning (ML) in high-energy physics (HEP) is well established and pertinent given the complex detectors, large data, sets and sop…
Data and Analysis Preservation, Recasting, and Reinterpretation
Stephen Bailey, Christian Bierlich, Andy Buckley +15
We make the case for the systematic, reliable preservation of event-wise data, derived data products, and executable analysis code. This preservation enables the analyses' long-ter…
Publishing statistical models: Getting the most out of particle physics experiments
Kyle Cranmer, Sabine Kraml, Harrison B. Prosper +30
The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In…
Learning from the Pandemic: the Future of Meetings in HEP and Beyond
Mark S. Neubauer, Todd Adams, Jennifer Adelman-McCarthy +36
The COVID-19 pandemic has by-and-large prevented in-person meetings since March 2020. While the increasing deployment of effective vaccines around the world is a very positive deve…
Distributed statistical inference with pyhf enabled through funcX
Matthew Feickert, Lukas Heinrich, Giordon Stark +1
In High Energy Physics facilities that provide High Performance Computing environments provide an opportunity to efficiently perform the statistical inference required for analysis…
Software Training in HEP
Sudhir Malik, Samuel Meehan, Kilian Lieret +44
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020…
A Living Review of Machine Learning for Particle Physics
Matthew Feickert, Benjamin Nachman
Modern machine learning techniques, including deep learning, are rapidly being applied, adapted, and developed for high energy physics. Given the fast pace of this research, we hav…
Software Sustainability & High Energy Physics
Daniel S. Katz, Sudhir Malik, Mark S. Neubauer +16
New facilities of the 2020s, such as the High Luminosity Large Hadron Collider (HL-LHC), will be relevant through at least the 2030s. This means that their software efforts and tho…
The Scikit HEP Project -- overview and prospects
Eduardo Rodrigues, Benjamin Krikler, Chris Burr +9
Scikit-HEP is a community-driven and community-oriented project with the goal of providing an ecosystem for particle physics data analysis in Python. Scikit-HEP is a toolset of app…
Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2
Waleed Abdallah, Shehu AbdusSalam, Azar Ahmadov +139
We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpret…