MLPF results on the simulated CLIC dataset

Updates over the previous version:

updated validation outputs for the cluster-based model

fixed a bug with how the PF candidates were stored

added single particle gun samples to validation

added new timing runs

for the baseline algo, included memory information

run the GNN model up to ~10k inputs

added hypertuning summary tables

Trained models and evaluation results for the upcoming paper "Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors", https://doi.org/10.48550/arXiv.2309.06782.

The archive contains the following subfolders:

clusters_best_tuned_gnn_clic_v130

MLPF GNN model configs and weight files after hypertuning

the inputs are reconstructed tracks and Pandora clusters

the outputs are reconstructed PF candidates

trained on tt and qq v1.3.0 (1M events each)

hits

MLPF GNN model configs and weight files

inputs are reconstructed tracks and calorimeter hits

outputs are reconstructed PF candidates

trained on tt, qq and gun samples (K0L, gamma, pi+-, pi0, neutron, ele, mu) v1.2.0

training was restarted several times from previous checkpoints

hypertuning

GNN and transformer model before and after hypertuning

summary tables of the hypertuning runs

timing

scaling study of baseline PF with number of gun particles on CPU

scaling study of GNN model with number of input elements on GPU

gpu_scaling

the scaling study of model training on multiple accelerator cards

The training dataset is available at

Pata, Joosep, Wulff, Eric, Duarte, Javier, Mokhtar, Farouk, Zhang, Mengke, Girone, Maria, & Southwick, David. (2023). Simulated datasets for detector and particle flow reconstruction: CLIC detector (1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8260741