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Abstract
Quantum computing is commonly described as a type of computation that uses the principles of quantum mechanics to process information. Specifically, quantum computers can handle complexity efficiently using superposition and enhanced problem-solving capabilities as a result of its utilization of the quantum bit instead of the bit used in classical computing. In the age of digital manipulation, the capabilities of quantum computers have allowed for a more holistic understanding of quantum computers' ability to bring about solutions to cybersecurity, banking and finance, and advanced manufacturing systems. Some of the most prevalent challenges to develop quantum algorithms include benchmarking and error mitigation techniques necessary for software development and hardware implementation and interfacing. To address this shortcoming, Model-Based Systems Engineering (MBSE) is being proposed to develop a framework through a formalized application of modeling to support system requirements and traceability and create models to support system behavior and how quantum machines will interact with the software and hardware to increase stakeholder understanding. Other MBSE techniques like recursive validation and verification throughout the project lifecycle ensure that quantum-based projects reach the highest level of development. This research uses a systematic literature review methodology for evidence-informed research through bibliometric analysis. Therefore, the aim of this literature review is to identify past and current trends in existing research that applies MBSE methods to quantum computing. This paper will identify where MBSE has been used to add value in quantum computing and set priorities for future work.
Keywords
quantum computing, MBSE, systematic literature review, bibliometric analysis
1. Introduction
Quantum computing harnesses ideas from classical information theory, computer science, and quantum physics [1]. Over the past 30 years, quantum computing research has evolved from the experimental manipulation of quantum bits to a potential solution for economic, industrial, and social change [2]. Even more importantly, recent advancements in quantum hardware, algorithm development, and quantum programming languages have brought the technology closer to more practical applications than ever before [3].
While there have been advancements in quantum computing, there are still key knowledge gaps that must be addressed. Quantum computing has the potential to revolutionize various fields by solving complex algorithms far beyond the capabilities of the classical computer, but this feat does not come without risks and challenges [5]. Quantum Key...