A hidden bottleneck in classical and quantum linear reservoir computing

Fuente: arXiv
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Hauptverfasser: Nokkala, Johannes, Centrone, Federico, Arzani, Francesco
Format: Preprint
Veröffentlicht: 2026
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author Nokkala, Johannes
Centrone, Federico
Arzani, Francesco
author_facet Nokkala, Johannes
Centrone, Federico
Arzani, Francesco
contents We identify a hidden bottleneck in the information processing capacity of linear reservoir computers. When the measured features evolve linearly in the reservoir and the output is formed by linear readout with bias, we show that the capacity available at any fixed delay is limited by what is already present in the preprocessed input. Linear reservoir dynamics can therefore redistribute features, but cannot create new fixed-delay expressive power on their own. This limitation is hidden by global capacity measures, since contributions from different delays can accumulate even when each individual delay is strongly constrained. As an experimentally important realization of this general result, we derive the corresponding Gaussian limit for covariance-based continuous-variable quantum reservoirs. Numerical experiments show that experimentally accessible single-photon operations surpass this limit, establishing them as a genuine resource for quantum reservoir computing. The resulting excess capacity also provides an operational witness of non-Gaussian processing in black-box continuous-variable systems under minimal assumptions.
format Preprint
id arxiv_https___arxiv_org_abs_2605_29071
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A hidden bottleneck in classical and quantum linear reservoir computing
Nokkala, Johannes
Centrone, Federico
Arzani, Francesco
Quantum Physics
We identify a hidden bottleneck in the information processing capacity of linear reservoir computers. When the measured features evolve linearly in the reservoir and the output is formed by linear readout with bias, we show that the capacity available at any fixed delay is limited by what is already present in the preprocessed input. Linear reservoir dynamics can therefore redistribute features, but cannot create new fixed-delay expressive power on their own. This limitation is hidden by global capacity measures, since contributions from different delays can accumulate even when each individual delay is strongly constrained. As an experimentally important realization of this general result, we derive the corresponding Gaussian limit for covariance-based continuous-variable quantum reservoirs. Numerical experiments show that experimentally accessible single-photon operations surpass this limit, establishing them as a genuine resource for quantum reservoir computing. The resulting excess capacity also provides an operational witness of non-Gaussian processing in black-box continuous-variable systems under minimal assumptions.
title A hidden bottleneck in classical and quantum linear reservoir computing
topic Quantum Physics
url https://arxiv.org/abs/2605.29071