Quantum reservoir networks based on decoherence-free subspaces

V. V. Akshay; M. V. Altaisky; N. E. Kaputkina

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arXiv · 2605.27427

Quantum reservoir networks based on decoherence-free subspaces

V. V. Akshay·M. V. Altaisky·N. E. Kaputkina

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Abstract

We present numerical simulation of a six-qubit quantum reservoir network with an output implemented on a 5-dimensional decoherence-free subspace (DFS), working as a classifier between entangled and product states of the input quantum system, fed to the reservoir during a finite learning time. Since the dynamics of DFS is not affected by external fluctuations, no cooling is required, and the proposed model seems a promising candidate for future quantum artificial intelligence systems working at room temperatures and free of huge energy consumption.

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BibTeX RIS

V. V. Akshay, M. V. Altaisky, N. E. Kaputkina. 2026-05-21. Quantum reservoir networks based on decoherence-free subspaces. https://arxiv.org/abs/2605.27427

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