Q-Edge: Symmetry-Reduced Quantum Simulation of Structured Extreme Dependence

Abstract:High-dimensional simulation of multivariate extremes is fundamentally limited by the combinatorial complexity of dependence, often more than by the scarcity of extreme observations. We show that symmetry admits a lossless orbit-space representation that preserves structured extreme dependence while replacing an exponentially large dependence space with a compact set of symmetry classes. Based on this principle, we develop Q-Edge (Quantum Extreme Dependence Engine), a symmetry-reduced quantum framework that operates directly in orbit space, enabling scalable simulation and digital twins of structured extreme systems. By transferring symmetry into the data representation rather than the quantum circuit, Q-Edge allows unconstrained quantum generative models to exploit dramatically reduced state spaces. For a 30-dimensional problem, approximately 1.6 million angular states collapse to 256 orbit states, reducing the required quantum representation from about 21 qubits to 8. Our results establish a general computational principle for scalable quantum simulation of structured extreme dependence.

Quantum Physics (quant-ph); Machine Learning (stat.ML)

arXiv:2609.03706 [quant-ph]

(or arXiv:2609.03706v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.03706 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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