Hopfield networks on certain curved spaces (CP^{d-1}) can store far more patterns than traditional vector networks, with capacity growing with the space dimension.
Quantum-stabilized patterns in a vector Hopfield network
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abstract
We introduce the quantum vector Hopfield network, in which patterns are formed by orientations of quantum vector spins; quantum dynamics arise intrinsically from the non-commutativity of the spin operators. We derive the equations of state and the phase diagrams for this network as well as its classical counterpart. We find that quantum fluctuations, surprisingly, stabilize the stored patterns. Both the critical retrieval temperature and the target pattern overlap are enhanced relative to the classical network. Additionally, we find that this enhancement grows with pattern loading up to network capacity. We interpret this effect as an analog of quantum order-by-disorder, a mechanism by which quantum fluctuations promote the formation of ordered phases. These findings offer a new route to quantum-enhanced associative memory.
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cond-mat.stat-mech 1years
2026 1verdicts
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High-Capacity Generalized Hopfield Networks
Hopfield networks on certain curved spaces (CP^{d-1}) can store far more patterns than traditional vector networks, with capacity growing with the space dimension.