Channel coding against quantum jammers via minimax

2025-05-16

AI Summary

This work characterizes the capacity of fully quantum arbitrarily varying channels (FQAVCs) under infinite-dimensional quantum jammer attacks. Addressing the limitations of prior studies—namely, reliance on finite-dimensional jammers and symmetry assumptions—the paper introduces, for the first time, a minimax analytical framework that circumvents de Finetti reduction, enabling rigorous treatment of infinite-dimensional adversarial settings. Under two shared-resource models—entanglement assistance and shared randomness assistance—the authors prove that the FQAVC capacity equals the corresponding compound channel capacity in each case, thereby unifying adversarial and non-adversarial capacity bounds. This result overcomes the dimensional constraints inherent in classical arbitrarily varying channel (AVC) theory and earlier quantum AVC frameworks, establishing the first general, dimension-independent capacity theory for quantum communication resilient to quantum jamming.

Technology Category

• Machine Learning: Quantum Machine Learning
• Game Theory and Economic Paradigms: Adversarial Learning
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Measurement, analysis, and circumvention of Web censorship

Abstract

We introduce a minimax approach for characterizing the capacities of fully quantum arbitrarily varying channels (FQAVCs) under different shared resource models. In contrast to previous methods, our technique avoids de Finetti-type reductions, allowing us to treat quantum jammers with infinite-dimensional systems. Consequently, we show that the entanglement-assisted and shared-randomness-assisted capacities of FQAVCs match those of the corresponding compound channels, even in the presence of general quantum adversaries.

Problem

• Characterize capacities of fully quantum varying channels
• Handle quantum jammers with infinite-dimensional systems
• Match capacities of compound channels with adversaries

Innovation

• Minimax approach for quantum channel capacities
• Avoids de Finetti-type reductions
• Handles infinite-dimensional quantum jammers