Quantum distributed computing applied to grover’s search algorithm

Abstract

Grover’s Algorithm finds a unique element in an unsorted stock of N-elements in √ N queries through quantum search. A singlequery solution can also be designed, but with an overhead of N log2 N steps to prepare and post process the query, which is worse than the classical N/2 queries. We show here that by distributing the computing load on a set of quantum computers, we achieve better information theoretic bounds and relaxed space scaling. Howsoever small one quantum computing node is, by virtue of networking and sharing of data, we can virtually work with a sufficiently large qubit space.