SciPost Submission Page
Quantum reservoir probing: an inverse paradigm of quantum reservoir computing for exploring quantum many-body physics
by Kaito Kobayashi, Yukitoshi Motome
Submission summary
| Authors (as registered SciPost users): | Kaito Kobayashi |
| Submission information | |
|---|---|
| Preprint Link: | scipost_202407_00044v4 (pdf) |
| Date submitted: | 2025-04-22 13:17 |
| Submitted by: | Kobayashi, Kaito |
| Submitted to: | SciPost Physics |
| Ontological classification | |
|---|---|
| Academic field: | Physics |
| Specialties: |
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| Approaches: | Theoretical, Computational |
Abstract
Quantum reservoir computing (QRC) is a brain-inspired computational paradigm that exploits the natural dynamics of a quantum system for information processing. To date, a multitude of quantum systems have been utilized in the QRC, with diverse computational capabilities demonstrated accordingly. This study proposes a reciprocal research direction: probing quantum systems themselves through their information processing performance in the QRC framework. Building upon this concept, here we develop quantum reservoir probing (QRP), an inverse extension of the QRC. The QRP establishes an operator-level linkage between physical properties and performance in computing. A systematic scan of this correspondence reveals the intrinsic quantum dynamics of the reservoir system from computational and informational perspectives. Unifying quantum information and quantum matter, the QRP holds great promise as a potent tool for exploring various aspects of quantum many-body physics. In this study, we specifically apply it to analyze information propagation in a one-dimensional quantum Ising chain. We demonstrate that the QRP not only distinguishes between ballistic and diffusive information propagation, reflecting the system's dynamical characteristics, but also identifies system-specific information propagation channels, a distinct advantage over conventional methods.
Author indications on fulfilling journal expectations
- Provide a novel and synergetic link between different research areas.
- Open a new pathway in an existing or a new research direction, with clear potential for multi-pronged follow-up work
- Detail a groundbreaking theoretical/experimental/computational discovery
- Present a breakthrough on a previously-identified and long-standing research stumbling block
Author comments upon resubmission
Our detailed responses to the reviewers’ comments are provided in the attached PDF file (reply.pdf), available in the “Reports on this Submission” section of our SciPost Submission Page.
Sincerely,
Kaito Kobayashi and Yukitoshi Motome
List of changes
Sec. 2
[1] We added a new subsection Sec. 2.3, titled “General remarks on the QRP”.
[2] 1st paragraph in Sec. 2.3: We added a discussion clarifying our choice of zero‑delay tasks and highlighting how finite‑delay tasks can probe memory‑related phenomena, including ergodicity.
[3] 1st paragraph in Sec. 2.3: We added descriptions to emphasize the importance of the flexibility to choose read-out operators.
[4] 1st paragraph in Sec. 2.3: We added a sentence introducing the applicability of the QRP to quantitative analysis, such as perturbative effects.
Sec. 4
[5] 3rd paragraph in Sec. 4: We modified the discussion about the QRP configurations according to the addition of Sec. 2.3.
Others
[6] We refined the phrasing for improved clarity and precision.
[7] We added a reference [51].