Quantum Circuit Design for Objective Function Maximization in Gate-Model Quantum Computers

TL;DR

This paper introduces QTAM, an algorithm for designing optimized, reduced quantum circuits that maximize a given objective function in gate-model quantum computers, balancing hardware constraints and computational goals.

Contribution

The paper presents the Quantum Triple Annealing Minimization (QTAM) algorithm for optimal quantum circuit design focused on objective function maximization.

Findings

QTAM effectively reduces circuit complexity while maximizing the objective function.

The method balances hardware constraints with computational efficiency.

Demonstrates improved performance in quantum circuit optimization.

Abstract

Gate-model quantum computers provide an experimentally implementable architecture for near term quantum computations. To design a reduced quantum circuit that can simulate a high complexity reference quantum circuit, an optimization should be taken on the number of input quantum states, on the unitary operations of the quantum circuit, and on the number of output measurement rounds. Besides the optimization of the physical layout of the hardware layer, the quantum computer should also solve difficult computational problems very efficiently. To yield a desired output system, a particular objective function associated with the computational problem fed into the quantum computer should be maximized. The reduced gate structure should be able to produce the maximized value of the objective function. These parallel requirements must be satisfied simultaneously, which makes the optimization difficult. Here, we demonstrate a method for designing quantum circuits for gate-model quantum computers and define the Quantum Triple Annealing Minimization (QTAM) algorithm. The aim of QTAM is to determine an optimal reduced topology for the quantum circuits in the hardware layer at the maximization of the objective function of an arbitrary computational problem.