Novel Design of Quantum Circuits for Representation of Grayscale Images

TL;DR

This paper proposes a new quantum circuit design for efficiently representing grayscale images using minimal qubits and real vector space considerations, potentially reducing complexity compared to existing methods.

Contribution

It introduces a novel quantum circuit construction tailored for image representation that leverages real vector space constraints to simplify implementation.

Findings

Reduces number of gates needed for image encoding

Uses fewer qubits by focusing on real vector space

Demonstrates feasibility of efficient quantum image representation

Abstract

The advent of Quantum Computing has influenced researchers around the world to solve multitudes of computational problems with the promising technology. Feasibility of solutions for computational problems, and representation of various information, may allow quantum computing to replace classical computer in near future. One such challenge is the representation of digital images in quantum computer. Several works have been done to make it possible. One such promising technique, named Quantum Probability Image Encoding, requires minimal number of qubits, where the intensity of n pixels is represented as the statevector of log_2(n) qubits. Though there exist quantum circuit design techniques to obtain arbitrary statevector, they consider statevector in general Hilbert space. But for image data, considering only real vector space is sufficient, that may constraint the circuit in smaller gate set, and possibly can reduce number of gates required. In this paper, construction of such quantum circuits has been proposed.