Conveners
Plenary session Tuesday
- Oksana Shadura (University of Nebraska Lincoln (US))
- Eduardo Rodrigues (University of Liverpool (GB))
This is a short course in intermediate Python. Attendees will learn about using packages, decorators, and code acceleration in Numba and pybind11.
We discuss and justify the application of Python's Bokeh library to non-interactive and interactive visualization. A comparison between Bokeh and some widely used alternatives is made. We include a tutorial covering the key aspects necessary to create virtually any interactive plot needed in HEP, and provide custom examples and code.
pyhf is a pure-python implementation of the HistFactory statistical model for multi-bin histogram-based analysis with interval estimation based on asymptotic formulas. pyhf supports modern computational graph libraries such as JAX, PyTorch, and TensorFlow to leverage features such as auto-differentiation and hardware acceleration on GPUs to reduce the time to inference. pyhf is also well...
The cabinetry library provides a Python-based solution for building and steering binned template fits. It implements a declarative approach to construct statistical models. The instructions for building all template histograms required for a statistical model are executed using other libraries in the pythonic HEP ecosystem. Instructions can additionally be injected via custom code, which is...
Uproot provides an easy way to get data from ROOT files into arrays and DataFrames, and Awkward Array lets you manipulate arrays of complex data types. This tutorial starts at the beginning, showing how an Uproot + Awkward Array (+ Hist + Vector) workflow differs from ROOT based workflows, how to extract objects and arrays from ROOT files, how to apply cuts and restructure arrays, and it ends...
Jet finding is an essential step in the process of Jet analysis. The currently available interfaces cannot take multiple events in one function call, which introduces a significant overhead. To remedy this problem, we present an interface for FastJet using Awkward Arrays to represent multiple events in one array.
The package depends on other SCIKIT-HEP packages like Vector and by...
The INFERence-aware Neural Optimisation (INFERNO) algorithm (de Castro and Dorigo, 2018 https://www.sciencedirect.com/science/article/pii/S0010465519301948), allows one to fully optimise neural networks for the task of statistical inference by including the effects of systematic uncertainties in the training. This has significant advantages for work in HEP, where the uncertainties are often...
The Standard Model Effective Field Theory (SMEFT) extends the SM with higher-dimensional operators each scaled by a dimensionless Wilson Coefficient $c_i$ to model scenarios of new physics at some large scale $\Lambda$. Thus effects of new physics in the LHC data may be sought by fitting the $c_i$ to appropriate LHC data. Differential cross sections have numerous advantages as the inputs to...
