Deterministic Quantum Search for Arbitrary Initial Success Probabilities
Harishankar Mishra, Asvija Balasubramanyam, Gudapati Naresh Raghava

TL;DR
This paper introduces a deterministic quantum search algorithm that guarantees success regardless of initial success probability, maintaining quadratic speedup and enabling exact search of multiple targets with a circuit-level implementation.
Contribution
It presents a novel deterministic quantum search method that guarantees success for any initial probability, extending quantum search capabilities beyond probabilistic limitations.
Findings
Guarantees success for any initial success probability.
Maintains quadratic speedup of quantum search.
Enables exact search of multiple target states.
Abstract
Unstructured search remains as one of the significant challenges in computer science, as classical search algorithms become increasingly impractical for large-scale systems due to their linear time complexity. Quantum algorithms, notably Grover's algorithm, leverages quantum parallelism to achieve quadratic speedup over classical approaches. Its generalization, the amplitude amplification algorithm, extends this advantage to a broader class of search problems. However, both algorithms are inherently probabilistic and fail to guarantee success with certainty, also they offer no quantum advantage when the initial success probability exceeds 0.5. This work presents a deterministic quantum search algorithm that operates effectively for arbitrary initial success probabilities, providing guaranteed success in searching target states. The proposed approach introduces at most one additional…
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Taxonomy
TopicsQuantum Mechanics and Applications · Quantum Computing Algorithms and Architecture
