Quantum Reservoir Autoencoder for Blind Decryption: Two-Phase Protocol and Noise Resilience

Quantum Physics [Submitted on 12 Mar 2026] Quantum Reservoir Autoencoder for Blind Decryption: Two-Phase Protocol and Noise Resilience Hikaru Wakaura, Taiki Tanimae We instantiate the quantum reservoir autoencoder (QRA) with a noise-induced reservoir employing reset noise channels and address two open problems: noise-resilient reversibility and blind decryption. For a single-ciphertext protocol with 10 data qubits and random (non-optimized) reset probabilities, the open-system reservoir suppresses shot-noise sensitivity by ten orders of magnitude, yielding mean-squared error (MSE) \sim 10^{-14} compared with \sim 10^{-3} without reset channels (N_{\mathrm{shots}} = 1000). A two-phase protocol trains per-position decoding weights from M shared training plaintexts and decrypts previously unseen messages at MSE \sim 10^{-4}, with no statistically significant performance difference among ideal, shot-noise, and reset-plus-shot-noise conditions (p > 0.05, 16 seeds). Experiments at N_q = 5, 7, and 10 reveal a sharp phase transition at plaintext length N_c \approx N_q(N_q{+}1)/2 + 8, providing a design rule for the minimum qubit count. Two blind decoder variants that lack ground-truth targets -- a single-ciphertext cross-path iteration (MSE \approx 0.3) and a multi-sample regression variant (MSE \approx 0.53, worse than random) -- establish that shared training data is the irreducible requirement for blind decryption. A comparison with variational quantum circuit baselines shows that the fixed-reservoir analytic-readout architecture is dramatically more noise-robust: a quantum recurrent neural network protocol is completely destroyed under depolarizing noise, whereas the QRA remains invariant. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2603.12303 [quant-ph]   (or arXiv:2603.12303v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2603.12303 Focus to learn more Submission history From: Hikaru Wakaura [view email] [v1] Thu, 12 Mar 2026 07:05:46 UTC (316 KB) Access Paper: HTML (experimental) view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-03 References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)