Cipher-Structure-Aware Variational Quantum Cryptanalysis: A Reversible Public-Diagnostic Framework
Year: 2026
Type: preprint
Abstract: We introduce a cipher-structure-aware variational framework for key recovery from public data in reduced block ciphers. Public S-box differential constraints and candidate-key-dependent inverse-round residuals are converted into phase separators through reversible compute-phase-uncompute circuits. The principal separator is a hybrid DDT construction that combines pairwise and synchronized multi-pair differential constraints before residual refinement. The construction is specified by public functions and does not require a key-indexed phase table in the physical circuit. We formalize the public-instance model, prove one-sided completeness of the structural diagnostics, and derive a conditional lower-tail bound for false-key diagnostic gaps under an explicitly stated sub-Gaussian moment condition. This statistical statement concerns the diagnostic landscape, not convergence of a finite-depth QAOA optimizer. On ten independent random three-pair instances of 16-bit simplified AES, an 18-layer Hybrid-DDT schedule reaches a mean public-consistent-key probability of 0.529785, with values from 0.388892 to 0.770937, ranks the correct key first in every run, and has largest observed false-key probability 0.008723. The result is a reduced-cipher mechanism study, not an attack on full AES.
Source: arXiv (Cornell University)
Author: Li, Xi
Institution: Henan University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7214332421