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Spiking neuromorphic chip learns entangled quantum states
- Source :
- SciPost Phys. 12, 039 (2022)
- Publication Year :
- 2020
-
Abstract
- 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.<br />Comment: 9+13 pages, 4+2 figures; Submission to SciPost
Details
- Database :
- arXiv
- Journal :
- SciPost Phys. 12, 039 (2022)
- Publication Type :
- Report
- Accession number :
- edsarx.2008.01039
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.21468/SciPostPhys.12.1.039