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Machine-learned, GPU-accelerated particle flow reconstruction

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Overview

MLPF focuses on developing full event reconstruction based on computationally scalable and flexible end-to-end ML models.

High-level overview

Dataset compatibility table

The following table specifies which version of the jpata/particleflow software should be used with which version of the tensorflow datasets.

Code CMS dataset CLIC dataset
1.9.0 2.4.0 2.2.0
2.0.0 2.4.0 2.3.0

MLPF on open datasets

PF reconstruction

Open datasets:

The following datasets are available to reproduce the studies. They include full Geant4 simulation and reconstruction based on the CLIC detector. We have no affiliation with the CLIC collaboration, therefore these datasets are to be used only for computational studies and come with no warranty.

MLPF development in CMS

PF reconstruction MLPF reconstruction

PUPPI jets in ttbar

Initial development with Delphes

Number of reconstructed particles Scaling of the inference time

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Machine-learned, GPU-accelerated particle flow reconstruction

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  • Jupyter Notebook 47.1%
  • Python 43.3%
  • Shell 8.5%
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