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arXiv · 2608.13342

Quantum-Inspired Phase Bicoherence Spectroscopy: A Framework for Detecting Universal Textural Angular Order Across Multi-Modal Complex Datasets

Zheng Xing·Chan-Tong Lam·Xiaochen Yuan
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Abstract

Classical image analysis routinely discards structurally meaningful orientation signatures encoded within Fourier phase, which are easily corrupted by local cellular rotation. Although quantum-inspired data processing offers new avenues for complex signal characterization, practical tools for directly extracting gauge-invariant angular correlations without explicit phase reconstruction remain scarce. Here we introduce Quantum Phase Bicoherence (QPBC) spectroscopy, a novel quantum-interferometric framework for capturing gauge-invariant angular order. The method embeds image angular sectors into a nine-qubit entangled state and probes three-body bicoherence via an ancilla, yielding 16 interpretable readout channels. We validate our framework on three independent public multi-modal imaging datasets covering fluorescence (BBBC021), bright-field (BBBC041) and histopathology (PathMNIST). QPBC consistently resolves angular-phase order and discriminates distinct biological phenotypes with high statistical significance. After principal-axis alignment, the optimal probing frequency universally converges, driven by Fourier directional sensitivity; negative-control experiments fully eliminate discriminative capacity, demonstrating frequency tuning acts as an on-off switch. Cross-dataset benchmarks confirm QPBC outperforms conventional Fourier-phase statistics, where inherent inversion symmetry serves as a built-in pipeline self-check. QPBC delivers a universal, classically unachievable quantitative texture observable, establishes interpretable quantum morphometry, and broadens the toolbox for quantum-inspired analysis applicable to diverse multi-modal microscopic measurements.

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Zheng Xing, Chan-Tong Lam, Xiaochen Yuan. 2026-08-13. Quantum-Inspired Phase Bicoherence Spectroscopy: A Framework for Detecting Universal Textural Angular Order Across Multi-Modal Complex Datasets. https://arxiv.org/abs/2608.13342

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