Neuromorphic quantum computing
Quantum computation builds on the use of correlations. Correlations could also play a central role for artificial intelligence, neuromorphic computing or “biological computing.” As a step toward a systematic exploration of “correlated computing” we demonstrate that neuromorphic computing can perform...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
31 October 2022
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| In: |
Physical review
Year: 2022, Jahrgang: 106, Heft: 4, Pages: 1-12 |
| ISSN: | 2470-0053 |
| DOI: | 10.1103/PhysRevE.106.045311 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1103/PhysRevE.106.045311 Verlag, lizenzpflichtig, Volltext: https://link.aps.org/doi/10.1103/PhysRevE.106.045311 
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| Verfasserangaben: | Christian Pehle, Christof Wetterich |
MARC
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| 520 | |a Quantum computation builds on the use of correlations. Correlations could also play a central role for artificial intelligence, neuromorphic computing or “biological computing.” As a step toward a systematic exploration of “correlated computing” we demonstrate that neuromorphic computing can perform quantum operations. Spiking neurons in the active or silent states are connected to the two states of Ising spins. A quantum density matrix is constructed from the expectation values and correlations of the Ising spins. We show for a two qubit system that quantum gates can be learned as a change of parameters for neural network dynamics. These changes respect restrictions which ensure the quantum correlations. Our proposal for probabilistic computing goes beyond Markov chains and is not based on transition probabilities. Constraints on classical probability distributions relate changes made in one part of the system to other parts, similar to entangled quantum systems. | ||
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