| Jahr | 2020 |
| Autor(en) | Stefanie Czischek, Andreas Baumbach, Sebastian Billaudelle, Benjamin Cramer, Lukas Kades, Jan M. Pawlowski, Markus K. Oberthaler, Johannes Schemmel, Mihai A. Petrovici, Thomas Gasenzer, Martin Gärttner |
| Titel | Spiking neuromorphic chip learns entangled quantum states |
| KIP-Nummer | HD-KIP 20-59 |
| KIP-Gruppe(n) | F9,F20,F27,F30 |
| Dokumentart | Paper |
| Quelle | SciPost Phys. 12, 039 (2022) |
| doi | 10.21468/SciPostPhys.12.1.039 |
| Abstract (en) | The approximation of quantum states with artificial neural networks has gained a lot of attention during the last years. Meanwhile, analog neuromorphic chips, inspired by structural and dynamical properties of the biological brain, show a high energy efficiency in running artificial neural-network architectures for the profit of generative applications. This encourages employing such hardware systems as platforms for simulations of quantum systems. Here we report on the realization of a prototype using the latest spike-based BrainScaleS hardware allowing us to represent few-qubit maximally entangled quantum states with high fidelities. Bell correlations of pure and mixed two-qubit states are well captured by the analog hardware, demonstrating an important building block for simulating quantum systems with spiking neuromorphic chips. |
| bibtex | @article{czischek2020spiking,
author = {Stefanie Czischek, Andreas Baumbach, Sebastian Billaudelle, Benjamin Cramer, Lukas Kades, Jan M. Pawlowski, Markus K. Oberthaler, Johannes Schemmel, Mihai A. Petrovici, Thomas Gasenzer, Martin Gärttner},
title = {Spiking neuromorphic chip learns entangled quantum states},
journal = {SciPost Phys.},
year = {2022},
volume = {12},
pages = {039},
doi = {10.21468/SciPostPhys.12.1.039},
url = {https://arxiv.org/abs/2008.01039}
} |
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