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First page of Lean-Quantum: Toward AI-Assisted Formalization of Quantum Information

Lean-Quantum: Toward AI-Assisted Formalization of Quantum Information

Kazumi Kasaura, Kei Tsukamoto, Kento Mori, Risa Mizuno, Takahiro Namatame, Yuta Oriike, Masaya Taniguchi, Sho Sonoda, Hayata Yamasaki

quant-ph Jul 6, 2026 · v1 cs.AI
Presents a Lean 4 library for finite-dimensional quantum information and formalizes the data processing inequality for the sandwiched Rényi relative entropy.
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.

Quantum information theory relies on entropic quantities like the sandwiched Rényi relative entropy and its data processing inequality (DPI) under quantum channels, but these results lacked machine-checkable formal foundations.

A Lean 4 library provides a basis-independent operator-theoretic framework for finite-dimensional quantum mechanics compatible with Mathlib, including systems, states, channels, tensor products, partial traces, Choi operators, Kraus and Stinespring representations. It builds noncommutative trace-inequality infrastructure via the real continuous functional calculus, Jensen's operator inequality, generalized perspectives, operator power means, and Lieb–Ando inequalities. Entropy-specific ingredients such as variational formulas via Young and reverse-Young inequalities and Haar measures on unitary groups are formalized. The DPI proof reorganizes the Frank–Lieb strategy into reusable intermediate interfaces.

The DPI for the sandwiched Rényi relative entropy for positive semidefinite operators is formalized in Lean, yielding strong subadditivity as a corollary and supplying the last missing component to complete a Lean formalization of the generalized quantum Stein's lemma.