Memory-Nonlinearity Trade-off across Quantum Reservoir Computing Frameworks
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866918401850474496 |
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| author | Čindrak, Saud Giebeler, Lara Götting, Niclas Gies, Christopher Lüdge, Kathy |
| author_facet | Čindrak, Saud Giebeler, Lara Götting, Niclas Gies, Christopher Lüdge, Kathy |
| contents | Quantum reservoir computing (QRC) harnesses driven quantum dynamics for time-series processing, yet the mechanisms behind the differing performance levels across its many implementations remain unclear. We show that apparently unrelated approaches-including memory restriction, weak measurements, operation near the edge of quantum chaos, and dissipative dynamics-are in fact governed by the same underlying principle, namely a tunable balance between memory retention and nonlinear response. Using the information processing capacity, a dynamical measure from nonlinear systems theory, we place these behaviors in a unified framework and identify the regimes in which quantum reservoirs surpass the standard protocol. Our results reveal a fundamental connection between memory and nonlinear response. This provides a general design principle for enhanced information processing and enables systematic analysis and optimization inspired by classical dynamical quantifiers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_21371 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Memory-Nonlinearity Trade-off across Quantum Reservoir Computing Frameworks Čindrak, Saud Giebeler, Lara Götting, Niclas Gies, Christopher Lüdge, Kathy Quantum Physics Quantum reservoir computing (QRC) harnesses driven quantum dynamics for time-series processing, yet the mechanisms behind the differing performance levels across its many implementations remain unclear. We show that apparently unrelated approaches-including memory restriction, weak measurements, operation near the edge of quantum chaos, and dissipative dynamics-are in fact governed by the same underlying principle, namely a tunable balance between memory retention and nonlinear response. Using the information processing capacity, a dynamical measure from nonlinear systems theory, we place these behaviors in a unified framework and identify the regimes in which quantum reservoirs surpass the standard protocol. Our results reveal a fundamental connection between memory and nonlinear response. This provides a general design principle for enhanced information processing and enables systematic analysis and optimization inspired by classical dynamical quantifiers. |
| title | Memory-Nonlinearity Trade-off across Quantum Reservoir Computing Frameworks |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2603.21371 |