An Introduction to Quantum Computing and Its Application

Michal Charemza

Marco Donald Migliore

Quantum computing is a cutting-edge paradigm in data processing that uses the principles of quantum mechanics to perform calculations. It has promising applications in various fields of engineering, including applied electromagnetism. Like any emerging technology, quantum computing has advantages and limitations that require in-depth understanding to make effective use in real-world engineering applications. This article aims to provide a simple and intuitive introduction to the fundamental principles of quantum computing, delving into the strengths and limitations inherent to this innovative technology and suggesting some applications of interest in the antennas and propagation community.

M M Hassan Mahmud, Goldsmith, Daniel

In this article, we present an introduction to quantum computing (QC) tailored for computing professionals such as programmers, machine learning engineers, and data scientists. Our approach abstracts away the physics underlying QC, which can be challenging to grasp, and frames it as a model of computation similar to, for instance, Turing machines. This helps readers grasp the fundamental principles of QC from a purely logical perspective. We begin by defining quantum states and qubits, establishing their mathematical representation and role in computation. We introduce fundamental concepts such as basis states, quantum gates, and tensor products, illustrating how these form the building blocks of quantum computation. Then we present the Deutsch-Josza algorithm, one of the simplest quantum algorithms that demonstrate how quantum computers can outperform classical computers. Finally, we provide guidance for further study, recommending resources for those interested in exploring quantum algorithms, implementations, and industry applications.

Gerard J Milburn

Elliot Catt, Marcus Hütter

In this technical report we give an elementary introduction to Quantum Computing for non-physicists. In this introduction we describe in detail some of the foundational Quantum Algorithms including: the Deutsch-Jozsa Algorithm, Shor's Algorithm, Grocer Search, and Quantum Counting Algorithm and briefly the Harrow-Lloyd Algorithm. Additionally we give an introduction to Solomonoff Induction, a theoretically optimal method for prediction. We then attempt to use Quantum computing to find better algorithms for the approximation of Solomonoff Induction. This is done by using techniques from other Quantum computing algorithms to achieve a speedup in computing the speed prior, which is an approximation of Solomonoff's prior, a key part of Solomonoff Induction. The major limiting factors are that the probabilities being computed are often so small that without a sufficient (often large) amount of trials, the error may be larger than the result. If a substantial speedup in the computation of an approximation of Solomonoff Induction can be achieved through quantum computing, then this can be applied to the field of intelligent agents as a key part of an approximation of the agent AIXI.

E. Gerjuoy