Sign-embedding quantum algorithms deliver explicit block-encodings for Sylvester equations and related matrix problems with query complexity linear in inverse-conditioning parameters and logarithmic in error tolerance.
AI mathematician: Towards fully automated frontier mathematical research.arXiv preprint arXiv:2505.22451, 2025
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Human-AI collaboration expanded a meta-idea on rational approximation into sign-embedding quantum algorithms for matrix problems, with humans retaining final judgment on routes and refinements.
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Sign Embedding Quantum Algorithms for Matrix Equations and Matrix Functions
Sign-embedding quantum algorithms deliver explicit block-encodings for Sylvester equations and related matrix problems with query complexity linear in inverse-conditioning parameters and logarithmic in error tolerance.
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From Meta Idea to Advanced Mathematical Discovery -- Human-AI Co-Discovery of Sign-Embedding Quantum Algorithms
Human-AI collaboration expanded a meta-idea on rational approximation into sign-embedding quantum algorithms for matrix problems, with humans retaining final judgment on routes and refinements.