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Photoniques

Quantum computing: promises, achievements and challenges

Thomas Ayral

Published Jan 1, 2025• 0 citations
Publisher

Abstract

Quantum computers regularly make the headlines, with optimistic claims (often issued by companies large and small) alternating with pessimistic rebuttals (often by academic labs): sometimes they supposedly solve outstanding hard computational problems, sometimes their performances are dwarfed by classical machines. The goal of this article is to shed light on this back-and-forth, and explain what quantum computing could really be useful for.

DOI
10.1051/photon/202513166

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Quantum computers regularly make the headlines, with optimistic claims (often issued by companies large and small) alternating with pessimistic rebuttals (often by academic labs): sometimes they supposedly solve outstanding hard computational problems, sometimes their performances are dwarfed by classical machines. The goal of this article is to shed light on this back-and-forth, and explain what quantum computing could really be useful for.
We are on the verge of a new era in computation, one that operates on the strange and wonderful rules of the quantum world. This article explores the story of quantum computing, a technology that promises to solve problems far beyond the reach of today's fastest supercomputers. We'll journey from the core ideas that make it all possible—concepts like superposition and entanglement—to the incredible machines being built in labs around the world. We'll see how these machines are being programmed and witness the first hints of their power in fields like medicine, materials science, and cybersecurity. Finally, we'll take an honest look at the immense challenges that still lie ahead on the path to building a truly powerful quantum computer. This is a story of human ingenuity pushing the boundaries of science, a tale of the immense potential and practical hurdles of the coming quantum age.
Quantum computing promises to have a tremendous advantage over its classical counterpart for solving computationally hard problems, yet remains in a relatively early stage for practical applications owing to the limited capabilities of today’s quantum computers. The approach to the special purposes of quantum computers by exploiting the special-purpose physics-inspired or quantum-inspired computers is emerging as a novel alternative to its quantum counterpart in tackling hard problems in high-performance computing. Inspired by physics, the Ising machine — a type of special-purpose computer that implements or emulates physics or quantum effects of the Ising model to speed up finding solutions to optimization problems — has recently become an active research area in the field of combinatorial optimization. This paper is to address the key enabling software and hardware technology underlying physics-inspired optimization using Ising machines in the unified quadratic unconstrained binary optimization (QUBO) framework for modeling and solving computationally hard combinatorial optimization problems, and with an aim to shed some light on the challenges and opportunities associated with the ever-growing landscape of this novel high-performance computing.
Quantum computing is the process of performing calculations using quantum mechanics. This field studies the quantum behavior of certain subatomic particles for subsequent use in performing calculations, as well as for large-scale information processing. These capabilities can give quantum computers an advantage in terms of computational time and cost over classical computers. Nowadays, there are scientific challenges that are impossible to perform by classical computation due to computational complexity or the time the calculation would take, and quantum computation is one of the possible answers. However, current quantum devices have not yet the necessary qubits and are not fault-tolerant enough to achieve these goals. Nonetheless, there are other fields like machine learning or chemistry where quantum computation could be useful with current quantum devices. This manuscript aims to present a Systematic Literature Review of the papers published between 2017 and 2023 to identify, analyze and classify the different algorithms used in quantum machine learning and their applications. Consequently, this study identified 94 articles that used quantum machine learning techniques and algorithms. The main types of found algorithms are quantum implementations of classical machine learning algorithms, such as support vector machines or the k-nearest neighbor model, and classical deep learning algorithms, like quantum neural networks. Many articles try to solve problems currently answered by classical machine learning but using quantum devices and algorithms. Even though results are promising, quantum machine learning is far from achieving its full potential. An improvement in the quantum hardware is required since the existing quantum computers lack enough quality, speed, and scale to allow quantum computing to achieve its full potential.
This brief overview of quantum computing gives an intuitive, albeit incomplete view of why it shows promise over any known classical approach to computing. The difficulty of making a qubit which allows us to protect and control quantum information will be illustrated in an overview of existing quantum technologies, including ions, superconducting qubits, spins and defects in solids. Finally, I will review a few of the problems which may benefit most from quantum computing and why many in industry are excited by the prospects.
“The sun shone, having no alternative, on the nothing new.” Samuel Beckett's acclaimed opening words for Murphy appear to be somehow pessimistic. Yet actually, quite often, a distinctive control over light beams puts forward a path to the new. This book takes a glance over some of those paths. Exploring the natural phenomena around us and across the Universe; pushing the limits of our understanding of Nature; and using the knowledge acquired to diagnose and cure disease, and to create devices and machines that make life safer, healthier, and more fulfilling is a program that many, throughout history, have found as captivating as compelling. Advancing such programs requires tools, which must be more and more sophisticated as the limits of knowledge move farther from our own scale and intuition. Really small or really large things, as well as really fast or really slow events, are particularly challenging, as neither our senses nor our ordinary gadgets are equipped to tackle them. We need powerful tools and technologies to enter such territories. The farther we aim to reach, the higher the performances that our toolkit must deliver. Light is one of these wonderful tools. It is ubiquitous and universal, and can be outstandingly accurate and precise. During the past decades we have learnt not only how to generate and control light in exquisite ways – especially since the invention of the laser half a century ago – but also how to transmit it and display it in ways that used to be the realm of science fiction and novels. As a result, light-based technologies are, literally, everywhere. And what is available today is just the beginning. The book consists of sixteen chapters of the same length and structure, each addressing a particular scientific and technological challenge in which some of the multifaceted existing light–matter interactions take a leading role. Readers can go through the chapters following any order they want. Each chapter opens with a short story that aims at motivating a context in which the overall challenge to be addressed has an impact.