mlsanityData to 14 Oct 2026

Lean-QIT: Towards a Formal Infrastructure for Quantum Information Theory

arXiv 2607.09632 ↗First posted 10 Jul 2026quant-ph cs.AIcited by 2

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Abstract (arXiv)

Quantum information theory (QIT) characterizes the capabilities and fundamental limits of quantum information processing, underpinning quantum communication, computation, and error correction. Formalizing its coding theorems requires connecting finite-block protocols, analytic inequalities, and asymptotic limits within a unified machine-checked framework. Existing developments, however, lack a reusable operational layer that defines codes, error criteria, achievable rates, and capacities independently of their information-theoretic characterizations. In this work, we present LeanQIT, a Lean 4 library for finite-dimensional QIT. It provides composable, kernel-checked interfaces for quantum states and channels, source and channel codes, finite-block performance criteria, hypothesis testing, one-shot quantities, and asymptotic rate constructions. Using this infrastructure, we formalize Schumacher's quantum source-coding theorem, the Holevo--Schumacher--Westmoreland classical-capacity theorem, and the entanglement-assisted classical-capacity theorem together with its strong converse. By separating operational definitions from analytic characterizations and exposing reusable achievability, converse, and asymptotic components, Lean-QIT provides a machine-readable foundation for formal QIT and a compositional knowledge substrate for emerging AI-assisted formalization, automated proof search, and agentic reasoning in quantum information and computation.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 7 of its 45 references that are in the map. First posted on arXiv 10 Jul 2026.

Builds on

7 of 45 references.

References · 7

  1. 2019The Lean mathematical librarycited by 134
  2. 2025A Formalization of the Generalized Quantum Stein's Lemma in Leancited by 7
  3. 2026AXLE: A Cloud Infrastructure for Lean 4 Theorem Proving Utilitiescited by 5
  4. 2026End-to-End Formalization of Quantum Error Correctioncited by 4
  5. 2022A Formally Certified End-to-End Implementation of Shor's Factorization Algorithmcited by 3
  6. 2026A Machine-Verified Proof of a Quantum-Optimization Conjecturecited by 3
  7. 2020Certified Quantum Computation in Isabelle/HOLcited by 2

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Citing papers per year: 2026: 2.

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  1. 2026Entanglement as Memory: Mechanistic Interpretability of Quantum Language Models
  2. 2026Qiskit QuantumKatas: Adapting Microsoft's Quantum Computing exercises for LLM evaluation
  3. 2025Quantum Data Encoding and Variational Algorithms: A Framework for Hybrid Quantum Classical Machine Learning
  4. 2025Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant
  5. 2026Neural Network Learning of One-Bit Protocols for Qubit Measurement Simulation
  6. 2025SAQR-QC: A Logic for Scalable but Approximate Quantitative Reasoning about Quantum Circuits ↗
  7. 2025Quantum Machine Unlearning: Foundations, Mechanisms, and Taxonomy
  8. 2025QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges