4 papers
Enabling stable preservation of ML algorithms in high-energy physics with petrifyML
Andy Buckley, Louie Corpe, Martin Habedank +1
Machine learning (ML) in high-energy physics (HEP) has moved in the LHC era from an internal detail of experiment software, to an unavoidable public component of many physics data…
Open LHC Monte Carlo Event Generation
Enrico Bothmann, Jon Butterworth, Shu Chen +16
The LHC physics programme involves a vast amount of Monte Carlo event simulation. This paper reviews current efforts towards sharing the generated events as Open Data. Open Event G…
Constraints On New Theories Using Rivet : CONTUR version 3 release note
Andy Buckley, Jon Butterworth, Joseph Egan +7
The CONTUR toolkit exploits RIVET and its library of more than a thousand energy-frontier differential cross-section measurements from the Large Hadron Collider to allow rapid limi…
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…