Asymptotically faster quantum algorithms to solve multivariate quadratic equations

This paper designs and analyzes a quantum algorithm to solve a system of $m$ quadratic equations in $n$ variables over a finite field ${\bf F}_q$. In the case $m=n$ and $q=2$, under standard assumptions, the algorithm takes time $2^{(t+o(1))n}$ on a mesh-connected computer of area $2^{(a+o(1))n}$, where $t\approx 0.45743$ and $a\approx 0.01467$. The area-time product has asymptotic exponent $t+a\approx 0.47210$. For comparison, the area-time product of Grover\u27s algorithm has asymptotic exponent $0.50000$. Parallelizing Grover\u27s algorithm to reach asymptotic time exponent $0.45743$ requires asymptotic area exponent $0.08514$, much larger than $0.01467$

A Brief Review on Mathematical Tools Applicable to Quantum Computing for Modelling and Optimization Problems in Engineering

Since its emergence, quantum computing has enabled a wide spectrum of new possibilities and advantages, including its efficiency in accelerating computational processes exponentially. This has directed much research towards completely novel ways of solving a wide variety of engineering problems, especially through describing quantum versions of many mathematical tools such as Fourier and Laplace transforms, differential equations, systems of linear equations, and optimization techniques, among others. Exploration and development in this direction will revolutionize the world of engineering. In this manuscript, we review the state of the art of these emerging techniques from the perspective of quantum computer development and performance optimization, with a focus on the most common mathematical tools that support engineering applications. This review focuses on the application of these mathematical tools to quantum computer development and performance improvement/optimization. It also identifies the challenges and limitations related to the exploitation of quantum computing and outlines the main opportunities for future contributions. This review aims at offering a valuable reference for researchers in fields of engineering that are likely to turn to quantum computing for solutions. Doi: 10.28991/ESJ-2023-07-01-020 Full Text: PD