IRIS-HEP Fellow: Oleksii Kiva
Fellowship dates: Jul – Oct, 2022
Jul – Oct, 2023
Home Institution: Igor Sikorsky Kyiv Polytechnic Institute
Project: Developing an automatic pruning utility for statistical models in HistFactory format
In pyhf, large-scale statistical models employed in HEP experiments are constructed using a modular approach to build a parametrized family of complex probability density functions from more primitive conceptual building blocks. It is often useful to make the model more lightweight in order to speed-up the derivation of maximum-likelihood estimates of its parameters. What's already available in pyhf is only helpful if one manually decides and specifies exactly what blocks to remove ('prune') from the statistical model. The goal of this project is to devise, implement, document and integrate into the pyhf library framework a tool that will automatically decide how to reduce the statistical model in HistFactory format, given its pyhf-specification and some ‘pruning’ criteria for the blocks.More information: My project proposal
Mentors:
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Alexander Held (University of Wisconsin-Madison)
Project: Developing an automatic differentiation and initial parameters optimisation pipeline for the particle shower model
During the HEP-experiment it is always interesting to trace the evolution of particle and energy distribution in the detector material, i. e., where the particles initially hit the material, what was happening in between and where they were eventually absorbed. Such distributions heavily depend on experimental conditions like detector geometry. The goal of this project is to develop a differentiable simulation and optimization pipeline to solve an inverse problem to the one described above. The problem of finding the best, in a certain sense, geometry of detector material and optimal starting conditions for the experiment, given the target properties of particle hits inside a detector.More information: My project proposal
Mentors:
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Lukas Heinrich (TUM)
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Michael Kagan (SLAC)
- 18 Oct 2023 - "Novel edge classification architectures for charged particle tracking with graph neural networks", Oleksii Kiva, IRIS-HEP Fellows Presentations 2023 Recording: Novel edge classification architectures for charged particle tracking with graph neural networks
Current Status
Bachelor of applied mathematics
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