用形式化工具证明量子熵的强数据处理不等式,为量子信息理论提供可机器验证的基础。
Lean-Quantum: Toward AI-Assisted Formalization of Quantum Information
- 构建基于Lean 4的量子信息形式化框架,支持算子理论与张量运算。
- 首次完整形式化夹层Rényi相对熵的数据处理不等式,推导出强子可加性。
- 为未来量子信息的AI辅助研究提供可验证的数学基础设施,适合形式化验证研究者。
量子信息理论建立在熵类量之上;其中,夹层Rényi相对熵是核心散度,其在量子通道下的数据处理不等式(DPI)是基石性结果。本文提出一个面向量子信息的Lean 4库,作为理论分析的可复用形式化基础设施。以该库为核心,我们形式化了有限维量子系统中正半定算子的夹层Rényi相对熵的DPI。该库提供与Mathlib兼容的基无关算子理论框架,涵盖有限维系统、态、通道、张量积、部分迹、Choi算子、Kraus表示及Stinespring表示等接口。同时构建了非交换迹不等式的基础设施,包括实连续函数演算下的算子单调性与凸性、块算子正性、Hilbert-Schmidt空间、Jensen算子不等式、广义视角、算子幂平均及Lieb-Ando迹不等式。在此基础上,我们形式化了熵相关关键成分:通过Young与逆Young不等式获得夹层拟熵的变分公式,实幂的张量积相容性,以及酉群上的Haar测度。这些共同构成对DPI的完整形式化,推出强子可加性,并补全广义量子Stein引理的最终缺失环节。本工作为未来量子信息理论的机器可验证与AI辅助研究奠定基础。
原文摘要 · Abstract (English)
Quantum information theory is built on entropic quantities; among them, the sandwiched Rényi relative entropy is a fundamental divergence with various applications, and its data processing inequality (DPI) under quantum channels is a cornerstone result. In this work, we present a Lean 4 library for quantum information, designed as a reusable formal infrastructure for theoretical analysis. As a central demonstration of the library, we formalize the DPI for the sandwiched Rényi relative entropy for positive semidefinite operators on finite-dimensional quantum systems. The library provides a basis-independent operator-theoretic framework for finite-dimensional quantum mechanics compatible with the standard mathematical library Mathlib, including reusable interfaces for finite-dimensional systems, states, channels, tensor products, partial traces, Choi operators, Kraus representations, and Stinespring representations. It also builds infrastructure for noncommutative trace inequalities, including operator monotonicity and convexity via the real continuous functional calculus, block-operator positivity, Hilbert-Schmidt operator spaces, Jensen's operator inequality, generalized perspectives, operator power means, and Lieb-Ando trace inequalities. On top of this framework, we formalize entropy-specific ingredients for the DPI: variational formulas for the sandwiched quasi-entropy via Young and reverse-Young inequalities, tensor-product compatibility of real powers, and Haar measures on unitary groups. Together, these components yield a Lean formalization of the DPI, give strong subadditivity as a corollary, and provide the last missing component needed to complete the Lean formalization of the generalized quantum Stein's lemma. More broadly, the development provides machine-checkable foundations for future formalized and AI-assisted research in quantum information theory.
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