AI RESEARCH
A Quantum Search Approach to Magic Square Constraint Problems with Classical Benchmarking
arXiv CS.AI
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ArXi:2604.04786v1 Announce Type: cross This paper presents a quantum search approach to combinatorial constraint satisfaction problems, nstrated through the generation of magic squares. We reformulate magic square construction as a quantum search problem in which a reversible, constraint-sensitive oracle marks valid configurations for amplitude amplification via Grover's algorithm. Classical pre-processing using the Siamese construction and partial constraint checks generates a compact candidate domain before quantum encoding.