Quantum mechanics can find a needle in a haystack every time
Fatemeh Mohit, Joshua Guanzon, Jaden McKinlay, Till J. Weinhold, Casey R. Myers, Marcelo P. Almeida, Markus Rambach, Andrew G. White

TL;DR
This paper demonstrates a deterministic version of Grover's quantum search algorithm implemented on a photonic chip, achieving near-perfect success rates and outperforming the original probabilistic version.
Contribution
The authors realize a deterministic Grover's algorithm on a photonic integrated circuit, showing improved robustness and success probability over the traditional probabilistic approach.
Findings
Achieved an average success probability of 99.77%.
Demonstrated robustness against technological imperfections.
Successfully implemented on databases of 4 to 10 elements.
Abstract
Grover's algorithm is one of the pioneering demonstrations of the advantages of quantum computing over its classical counterpart, providing - at most - a quadratic speed-up over the classical solution for unstructured database search. The original formulation of Grover's algorithm is non-deterministic, finding the answer with a probability that varies with the size of the search space and the number of marked elements. A recent reformulation introduced a deterministic form of Grover's algorithm that - in principle - finds the answer with certainty. Here we realise the deterministic Grover's algorithm on a programmable photonic integrated circuit, finding that it not only outperforms the original Grover's algorithm as predicted, but is also markedly more robust against technological imperfections. We explore databases of 4 to 10 elements, with every choice of a single marked element,…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Mechanics and Applications · Neural Networks and Reservoir Computing
