#### Welcome to the QuantHEP project website

**QuantHEP – Quantum Computing Solutions for High-Energy Physics** is a research project whose key goal is to develop quantum algorithms as a solution to the increasingly challenging, and soon intractable, problem of analysing and simulating events from large particle-physics experiments.

Project **QuantHEP **bring together researchers from the Physics of Information and Quantum Technologies Group at Instituto de Telecomunicações in Portugal, from the National Institute for Nuclear Physics in Italy, and from the Quantum Computing Group of the University of Latvia.

**QuantHEP **is funded through QuantERA, the European cofund programme in Quantum Technologies.

#### News

M. Trenti, L. Sestini, A. Gianelle, D. Zuliani, T. Felser, D. Lucchesi, S. Montangero, **Quantum-inspired Machine Learning on high-energy physics data**, arXiv:2004.13747 (2020). Get PDF

*arXiv*: 2004.13747, 2020.

```
@article{m.2020quantum,
title={Quantum-inspired Machine Learning on high-energy physics data},
author={M., Trenti and L., Sestini and A., Gianelle and D., Zuliani and T., Felser and D., Lucchesi and S., Montagero },
journal={arXiv},
year={2020},
pages={2004.13747}
}
```

G. Magnifico, M. Dalmonte, P. Facchi, S. Pascazio, F.V. Pepe, E. Ercolessi,** Real Time Dynamics and Confinement in the Zn Schwinger-Weyl lattice model for 1+1 QED**, arXiv:1909.04821 (2019). Get PDF

*arXiv*: 1909.04821, 2019.

```
@article{g.2019real,
title={Real Time Dynamics and Confinement in the Zn Schwinger-Weyl lattice model for 1+1 QED},
author={G., Magnifico and M., Dalmonte and P., Facchi and S., Pascazio and F.V., Pepe and E., Ercolessi},
journal={arXiv},
year={2019},
pages={1909.04821}
}
```