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This paper establishes a fundamental information-theoretic limit for quantum-assisted statistical inference, proving that pure state encodings maximize accuracy while identifying equiangular tight frames as the unique symmetric optimal solutions for low-dimensional systems. By linking encoding quality directly to maximal quantum leakage, the work provides a universal, task-agnostic metric for evaluating classical-to-quantum data conversion strategies. These theoretical bounds are critical for advancing practical quantum machine learning architectures where resource constraints necessitate efficient encoding schemes.
An Information-Theoretic Principle for Optimal Quantum Encoding: Tight Frames and Equiangular Ensembles
arXiv:2607.01564v2 Announce Type: replace Abstract: Optimal encoding of classical data for quantum-assisted statistical inference is investigated from an information-theoretic perspective. We prove that the accuracy of any quantum-computing inference procedure is upper bounded by the maximal quantum leakage from the classical data through its quantum encoding, establishing leakage as a universal, task-agnostic quality measure for encoders. The optimal encoding strategy, i.e., an encoding strategy that maximizes the maximal quantum leakage, is proved to be attained by pure states. When there are enough qubits, basis encoding is proved to be universally optimal. However, when the dimension of the system is small, phase encoding is optimal. For the latter, the optimal encoding is not unique. That is, any tight frame, any ensemble whose average state is the maximally mixed state, is in fact optimal. Within tight frames, equiangular tight frames (ETFs) are distinguished as the uniquely symmetric optimal encodings, i.e., they saturate the Welch lower bound on pairwise overlaps. Prominent special cases are the qubit trine, the regular simplex, and symmetric informationally complete positive operator-valued measures (SIC-POVMs), for which the ETF structure and explicit codeword constructions are provided. Numerical examples are presented to validate the theoretical predictions.
Abstract:Optimal encoding of classical data for quantum-assisted statistical inference is investigated from an information-theoretic perspective. We prove that the accuracy of any quantum-computing inference procedure is upper bounded by the maximal quantum leakage from the classical data through its quantum encoding, establishing leakage as a universal, task-agnostic quality measure for encoders. The optimal encoding strategy, i.e., an encoding strategy that maximizes the maximal quantum leakage, is proved to be attained by pure states. When there are enough qubits, basis encoding is proved to be universally optimal. However, when the dimension of the system is small, phase encoding is optimal. For the latter, the optimal encoding is not unique. That is, any tight frame, any ensemble whose average state is the maximally mixed state, is in fact optimal. Within tight frames, equiangular tight frames (ETFs) are distinguished as the uniquely symmetric optimal encodings, i.e., they saturate the Welch lower bound on pairwise overlaps. Prominent special cases are the qubit trine, the regular simplex, and symmetric informationally complete positive operator-valued measures (SIC-POVMs), for which the ETF structure and explicit codeword constructions are provided. Numerical examples are presented to validate the theoretical predictions.
Quantum Physics (quant-ph); Information Theory (cs.IT)
arXiv:2607.01564 [quant-ph]
(or arXiv:2607.01564v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2607.01564 Focus to learn more arXiv-issued DOI via DataCite
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