Feedback-driven quantum reservoir computing for time-series analysis

• URL: http://arxiv.org/abs/2406.15783v2
• Date: Fri, 13 Sep 2024 14:50:31 GMT
• Title: Feedback-driven quantum reservoir computing for time-series analysis
• Authors: Kaito Kobayashi, Keisuke Fujii, Naoki Yamamoto,
• Abstract summary: Quantum reservoir computing (QRC) is a promising computational paradigm that leverages quantum systems as a computational resource for nonlinear information processing. We propose a feedback-driven QRC framework for time-series analysis. We demonstrate that our QRC successfully acquires the fading-memory property through the feedback connections.
• Score: 1.1920094285063136
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum reservoir computing (QRC) is a highly promising computational paradigm that leverages quantum systems as a computational resource for nonlinear information processing. While its application to time-series analysis is eagerly anticipated, prevailing approaches suffer from the collapse of the quantum state upon measurement, resulting in the erasure of temporal input memories. Neither repeated initializations nor weak measurements offer a fundamental solution, as the former escalates the time complexity while the latter restricts the information extraction from the Hilbert space. To address this issue, we propose the feedback-driven QRC framework. This methodology employs projective measurements on all qubits for unrestricted access to the quantum state, with the measurement outcomes subsequently fed back into the reservoir to restore the memory of prior inputs. We demonstrate that our QRC successfully acquires the fading-memory property through the feedback connections, a critical element in time-series processing. Notably, analysis of measurement trajectories reveal three distinct phases depending on the feedback strength, with the memory performance maximized at the edge of chaos. We also evaluate the predictive capabilities of our QRC, demonstrating its suitability for forecasting signals originating from quantum spin systems.

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