PyHEP 2023 - "Python in HEP" Users Workshop (online)

Session

Plenary Session Thursday

12 Oct 2023, 14:00

Conveners

Plenary Session Thursday

• Matthew Feickert (University of Wisconsin Madison (US))
• Eduardo Rodrigues (University of Liverpool (GB))

7. Unified and semantic processing for heterogeneous Monte-Carlo data

Jacan Chaplais

12/10/2023, 14:00

Tutorial

This talk presents a comprehensive toolset tailored to high energy physics (HEP) research, comprising graphicle, showerpipe, colliderscope, and heparchy. Each component integrates into a cohesive workflow, addressing distinct stages of HEP data analysis.

These tools fill a niche within the HEP software ecosystem in Python by offering unified representations of Monte-Carlo event...

8. Spey: smooth inference for reinterpretation studies

Jack Y. Araz (IPPP - Durham University)

12/10/2023, 14:30

Notebook talk

Statistical models are at the heart of any empirical study for hypothesis testing. We present a new cross-platform Python-based package which employs different likelihood prescriptions through a plug-in system. This framework empowers users to propose, examine, and publish new likelihood prescriptions without developing software infrastructure, ultimately unifying and generalising different...

27. Python based detector simulation software - RASER

Dr Suyu Xiao (Shandong Institute of Advanced Technology, Jinan, China), Xin Shi (Chinese Academy of Sciences (CN))

12/10/2023, 15:00

Lightning talk

We developed a fast simulation software for semi-conductor detector in python - RASER (RAdiation SEmi-conductoR). RASER aims to estimate both spatial and timing resolution for semiconductor (silicon and SiC for now) detectors, providing predicts for detector design. It works relied on Geant4 and DEVSIM. Nonuniform charge deposition is solved from Geant4. The python bindings for Geant4 depends...

25. Workshop close-out

Eduardo Rodrigues (University of Liverpool (GB))

12/10/2023, 15:10

18. ML4EFT: unbinned multivariate observables for global SMEFT analyses

Maeve Una Madigan

Notebook talk

We present ML4EFT, an open source framework for the integration of unbinned observables into global fits of particle physics data. Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the SMEFT, often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of...