| title: README | |
| emoji: ☁️ | |
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| colorTo: red | |
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| # Fast calorimeter simulation | |
| Tools and studies for fast simulation of calorimeter showers: detailed | |
| Geant4 / DD4hep simulation, compact point-cloud representations of the showers, | |
| and their use as input to machine-learning-based fast simulation. | |
| This organization hosts the trained weights; the code is on | |
| [GitHub](https://github.com/fast-sim). | |
| <p align="center"> | |
| <img src="https://raw.githubusercontent.com/fast-sim/.github/main/profile/step2point-shower.png" alt="One 10 GeV photon shower in the Open Data Detector: 3,604 Geant4 steps, 365 points after merging within cells, 266 points after HDBSCAN clustering" width="900"> | |
| <br> | |
| <em>One photon shower as Geant4 steps and after two step2point compressions.</em> | |
| </p> | |
| ## Publications, code and data | |
| | Paper | Code | Data and weights | | |
| |---|---|---| | |
| | step2point dataset: Detailed shower simulation for data representation studies, [arXiv:2509.22340](https://arxiv.org/abs/2509.22340) ([CDS](https://cds.cern.ch/record/2948746)) | [`step2point`](https://github.com/fast-sim/step2point) | Zenodo, [doi:10.5281/zenodo.17199427](https://doi.org/10.5281/zenodo.17199427) | | |
| Library documentation: [fast-sim.github.io/step2point](https://fast-sim.github.io/step2point/) | |