PyHEP 2022 (virtual) Workshop

Session

Plenary Session Tueday

Sep 13, 2022, 2:00 PM

4. iminuit: fitting models to data

Hans Peter Dembinski (TU Dortmund)

9/13/22, 2:00 PM

Tutorial

iminuit is a Pythonic wrapper to the MINUIT2 C++ library which is part of the ROOT framework, but does not require ROOT to be installed. iminuit is a rather simple low-level library to do fitting compared to zfit or pyhf, but its simplicity also makes it is very flexible and easy to learn. The tutorial will cover how to do typical HEP fits with iminuit, typical pitfalls, and how to resolve...

42. Skyhook: Managing Columnar Data Within Storage

Jayjeet Chakraborty

9/13/22, 3:00 PM

Lightning talk

The advent of high-speed network and storage devices like RDMA-enabled networks and NVMe SSDs, the fundamental bottleneck in any data management system has shifted from the I/O layer to the CPU layer resulting in reduced scalability and performance. This issue is quite prominent in systems reading popular data formats like Parquet and ORC which involve CPU intensive tasks like decoding and...

24. The Particle & DecayLanguage packages

Eduardo Rodrigues (University of Liverpool (GB))

9/13/22, 3:10 PM

Lightning talk

An overview of the Particle & DecayLanguage packages is given. Particle provides a pythonic interface to the Particle Data Group particle data tables and particle identification codes, with extended particle information and extra goodies. DecayLanguage provides tools to parse so-called .dec decay files, and describe, manipulate and visualise decay chains. DecayLanguage also implements a...

22. PhaseSpace + DecayLanguage

Simon Thor (CERN)

9/13/22, 3:20 PM

Lightning talk

PhaseSpace is a Python package used for simulations of n-body decays and uses TensorFlow as the computational backend.
During this lightning talk, I will present a new feature in PhaseSpace: importing and simulating decays created using DecayLanguage, a package used for describing decays of particles. This...

32. Constructing HEP vectors and analyzing HEP data using Vector

Saransh Chopra (Cluster Innovation Centre, University of Delhi)

9/13/22, 3:30 PM

Notebook talk

Vector is a Python library for 2D, 3D, and Lorentz vectors, including arrays of vectors, designed to solve common physics problems in a NumPy-like way. Vector currently supports pure Python Object, NumPy, Awkward, and Numba-based (Numba-Object, Numba-Awkward) backends.

This talk will focus on introducing Vector and its backends to the HEP community through a data analysis pipeline. The...

35. Matplotlib with HSF Training

Alexander Moreno Briceño (Universidad Antonio Nariño)

9/13/22, 4:30 PM

Tutorial

Based on the Matplotlib for HEP workshop developed by HSF Training, we will present a short introduction to matplotlib and perform an HEP analysis using ATLAS and CMS open data in order to get publishable plots. We will also use mplhep, a matplotlib wrapper for easy plotting required in HEP. This tutorial aims to present a subset of the complete matplotlib training module and requires a...

27. Lessons learned converting a production-grade Python CMS analysis to distributed RDataFrame

Tommaso Tedeschi (Universita e INFN, Perugia (IT)), Vincenzo Eduardo Padulano (Valencia Polytechnic University (ES))

9/13/22, 5:30 PM

Notebook talk

The high-level and lazy programming model offered by RDataFrame has proven to be both user-friendly while at the same time providing satisfactory performance for many HEP analysis use cases. With the addition of a Pythonic layer for automatic distribution of workloads to multiple machines, RDataFrame can easily serve as a swiss knife tool for developing a full production-scale analysis with an...