Quantum Algorithm for Researching the Nearest (QARN)

TL;DR

This paper introduces a quantum algorithm that enhances the search for the nearest value in data sets by increasing success probability and optimizing oracle calls, improving speed and efficiency in quantum search tasks.

Contribution

It proposes a novel quantum algorithm that improves nearest value search by reducing undesirable outcomes and optimizing oracle usage without extra qubits.

Findings

Increased probability of finding the nearest value.

Reduced undesirable outcomes in the search process.

Oracle implementation requiring only a single call without ancilla qubits.

Abstract

The search task is one of the most difficult when it comes to execution speed, and reducing the latter is important both when working with large data and with small samples, if they need to be processed frequently and in a limited time. Grover's algorithm gave hope to quantum computing and served as an excellent base for all possible implementations and modifications. In this paper, we propose a slightly different algorithm that increases the probability of finding the nearest value by reducing the probability of undesirable values in a controlled manner (in proportion to their difference from the desired value), as well as implementing an oracle that requires a single call without an additional ancilla qubit to redistribute the amplitudes.