Quantum automated theorem proving
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Abstract (arXiv)
Automated theorem proving, or more broadly automated reasoning, aims at using computer programs to automatically prove or disprove mathematical theorems and logical statements. It takes on an essential role across a vast array of applications and the quest for enhanced theorem-proving capabilities remains a prominent pursuit in artificial intelligence. Here, we propose a generic framework for quantum automated theorem proving, where the intrinsic quantum superposition and entanglement features would lead to potential advantages. In particular, we introduce quantum representations of knowledge bases and propose corresponding reasoning algorithms for a variety of tasks. We show how automated reasoning can be achieved with quantum resolution in both propositional and first-order logic with quadratically reduced query complexity. In addition, we propose the quantum algebraic proving method for geometric theorems, extending Wu's algebraic approach beyond the classical setting. Through concrete examples, including geometry problems from the International Mathematical Olympiad, we demonstrate how a quantum computer may prove geometric theorems with quadratic better query complexity. Our results establish a primary approach towards building quantum automatic theorem provers, which would be crucial for practical applications of both near-term and future quantum technologies.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 11 of its 81 references that are in the map. First posted on arXiv 12 Jan 2026.
Builds on
11 of 81 references.
References · 11
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
- 2018Supervised learning with quantum enhanced feature spacescited by 654
- 2020A rigorous and robust quantum speed-up in supervised machine learningcited by 270
- 2023Challenges and Opportunities in Quantum Machine Learningcited by 202
- 2021Quantum advantage in learning from experimentscited by 186
- 2021Quantum machine learning beyond kernel methodscited by 91
- 2016Quantum-enhanced machine learningcited by 79
- 2015A formal proof of the Kepler conjecturecited by 42
- 2022Experimental quantum adversarial learning with programmable superconducting qubitscited by 38
- 2024Wu's Method can Boost Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometrycited by 11
- 2021Efficient Floating Point Arithmetic for Quantum Computerscited by 1
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Citing papers per year: 2026: 1.
1 paper.