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Proving olympiad geometry theorems on a superconducting quantum processor

Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide range of applications, and enhancing theorem-proving capabilities remains a central objective in artificial intelligence [3]. Although recent neuro-symbolic systems have achieved remarkable progress [4-7], their operation is ultimately constrained by classical computational architectures. Quantum computing [8], by contrast, enables information encoding and coherent parallelism beyond classical limits [9-14], raising the possibility of accelerating structured symbolic deduction [15]. Here we report the experimental realization of automated geomet...

AuthorsNing Wang, Zheng-Zhi Sun, Zhengyi Cui et al.
Primary categoryquant-ph
Published13 September 2026
Last updated at source13 September 2026
quant-phcs.AI
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