A Fast Measurement based fixed-point Quantum Search Algorithm
Ashish Mani, C Patvardhan

TL;DR
This paper introduces a faster, measurement-based fixed-point quantum search algorithm that improves success probability and efficiency over existing methods, with minimal additional resources and complexity.
Contribution
A novel stopping scheme for quantum search that estimates proximity to targets via measurement, simplifying and enhancing fixed-point search performance.
Findings
Achieves success probability > 50% for target ratios less than half
Simpler and more efficient than quantum counting and fixed-point schemes
Maintains same order of complexity as Grover's algorithm, with slight slowdown
Abstract
Generic quantum search algorithm searches for target entity in an unsorted database by repeatedly applying canonical Grover's quantum rotation transform to reach near the vicinity of the target entity represented by a basis state in the Hilbert space associated with the qubits. Thus, when qubits are measured, there is a high probability of finding the target entity. However, the number of times quantum rotation transform is to be applied for reaching near the vicinity of the target is a function of the number of target entities present in the unsorted database, which is generally unknown. A wrong estimate of the number of target entities can lead to overshooting or undershooting the targets, thus reducing the success probability. Some proposals have been made to overcome this limitation. These proposals either employ quantum counting to estimate the number of solutions or fixed point…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum-Dot Cellular Automata
