Bibliometric Analysis and Visualization of Quantum Engineering Technology

Quantum computing is a revolutionary field of research in science and technology, which provides sophisticated processing capacity and computation in a finite time frame based on quantum mechanics. It has the great potential to offer more effective and faster solutions to overcome current processing constraints. Therefore, to address the global significance, relevance, and exponential growth, it is imperative to conduct a thorough investigation and promote advancements through rigorous scientometric analysis. The current article presents the knowledge mapping of rapidly expanding quantum computing research using the CiteSpace visualization tool. The foundation of research is the scientific literature on quantum computing extracted from the Scopus database, covering the period of 2008–2022. It provides publication patterns, citation structure, and in-depth keyword co-occurrence network analysis insights to extract emerging research areas. It illustrates a variety of empirical approaches to discover the status quo and evolution. The findings reveal that quantum algorithms serve as the fundamental basis for all research fields, and quantum machine learning is the most active research area nowadays.

I. Introduction

Quantum computing (QC) is a rapidly growing technology and drastically different from classical computing. Classical physics phenomena are applied in classical computers, whereas superposition, entanglement, and interference are quantum physics phenomena used in quantum computers. Bits are the unit of storage used by traditional computers, which is either in the state of 0 or the state of 1. In contrast, a quantum computer stores the information in quantum bits (qubits). A single qubit may contain both 0 and 1 concurrently, and this state is known as superposition state [1]. In a two-qubit system, it exists as a superposition of the = 4 possible states 00, 01, 10, and 11. For example, five qubits/bit can make = 32 states. Classical computers can select only one out of 32 states in their computing, whereas quantum computers processing five qubits will process all 32 states simultaneously. Instead of five bits, it needs 32 bits in a classical computer, i.e., N qubits = classical bits. This parallelism will increase the computational power exponentially in quantum computers [2]. The computational power will be helpful in machine learning (ML), financial modeling, medical drug design, and cryptography [3]. Quantum computers will provide optimality and enhance performance compared with classical computers because they reach their maximum speed and processing power, which comes to the eventual failure of Moore's law [4]. Research is underway to build a quantum computer. However, major challenges in building a commercially working quantum computer include scalability, error correction, qubit quality, decoherence, perfect isolation, and chip architecture [5], [6]. Scientists have been working on these challenges and striving to make efficient qubit-based quantum technologies for noise-resistant quantum communications (QCMs), effective quantum computations, and delicate quantum molecular simulations [7], [8]. Collaborations amongst physicists, material scientists, computer scientists, and engineers are necessary to build a strong basis and framework for studying quantum technologies. QC has received a surge of attention from researchers and countries [9]. Between 2019 and 2021, China made up to $11 billion in investments in QC, followed by Europe with$5 billion, the United States with $3 billion, and the United Kingdom with around$1.8 billion [10]. Further, the description of key terms will be used in the article given in Table I.