Systematic review of MBSE applications in quantum computing research

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.

Headnote

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 Distribution (QKD) is a known method of communication for exchanging encryption keys using a quantum channel and guarantees security [5]. QKD provides an example of the knowledge gaps that occur in the integration, implementation, and scalability of quantum systems [6]. If QKD is utilized to develop a quantum-based algorithm, it must be seamlessly integrated into the existing system infrastructure. Thus, there must be a predetermined protection plan for all data throughout each stage of the integration process. Secondly, the implementation stage presents the challenge of budgeting long-term hardware and software that will maintain the speed of quantum technology advancements over time. Finally, the scalability of QKD and other quantum applications across global networks will pose a huge challenge because the integrity of the system must remain intact over space and time [5,6]. With these advancements, it is more important than ever to manage the complexity of the systems. Model based systems engineering (MBSE) is a formalized application that is being proposed to manage the integration and scalability of applications such as QKD. MBSE applies systems theory and design principles in investigating complex and dynamic systems. It presents potential benefits including traceability of requirements, models, and documentation to support the behavior and structure of a system [7]. MBSE is relevant especially for early technologies that integrate various systems and processes because it enables complex systems to be designed, integrated and optimized efficiently. Examples of early technologies that were theoretical and used systems engineering include: space travel, defense systems and digital twins [8]. In completing a systematic literature review (SLR) and exploring existing literature that includes both MB SE and quantum computing, academic researchers and industry professionals working in the quantum field will gain insight into what has already been done and how to best move forward with implementing MBSE principles in their work. Ultimately, this will allow the quantum field of research and experimentation to progress further and more quickly through the principles outlined by the MBSE methodology,

The purpose of this research is to present a bibliometric analysis that addresses the trends for the integration of MBSE in system solutions that utilize quantum computing. This study proposes the application of MBSE methodology and procedures to assist in the transition from classical computational systems to those developed using quantum-based algorithms. As quantum technologies evolve, so do their operational requirements, system architecture, and technological capabilities. Using MBSE as a framework for the execution of quantum development will enable engineering managers to quickly and accurately update the design and risks associated with this methodology [9].

2. Background

In recent years, developments in quantum technology have continued to gain interest globally. By combining the manipulation of foundational principles of quantum mechanics, including quantum entanglement, superposition, and tunnelling with technological ventures, quantum computing has emerged in its potential to outperform the most advanced classical supercomputers [10, 11]. This technology theoretically can redefine capabilities in cybersecurity, telecommunications, computational speed of datasets, medicinal particle sensing and behavior, forecasting, and modeling [12,13]. Consequently, competition to further quantum technology has surged as sectors in government, energy, supply chain, and finance industries race to invest. While the theoretical applications of quantum technology are widely known, the limitations to harnessing its potential include hardware qubit limitations, system sensitivity to noise and external environments. This presents challenges in quantum decoherence, error correction, reliability, and scalability [14]. Past research suggests the use of mechanical and technical innovation to enhance quantum node networks, miniaturize hardware, and develop quantum stabilizer codes that have successfully hurdled decoherence barriers as well as deficiencies in scalability and error correction [15]. Nonetheless, from the overarching perspective of lifecycle development and system traceability, little has been done to address these limitations.

Model-Based Systems Engineering (MBSE) is a methodology that that explore requirements, behavior, and structure of the system. MBSE is also used for domain-agnostic systems, that is, it allows for discipline-specific views of a system, including describing and defining the ontology, semantics and syntax used. This helps maintain a model repository that leads to improved communication, visualization, and model analysis [16]. MBSE is proposed to improve quantum performance by introducing standardization and repeatability. Advancements in quantum technology overseen by MBSE may be better equipped to embrace, execute, and respond to new technical solutions. The systematic literature review of this paper offers a structured, methodical approach to investigate the applicability of MBSE in quantum development in the past and the need for its use in future evolutions. A bibliometric analysis is then employed to quantify the investigation, derive evidence-based conclusions, and verify the applicability of MBSE.

3. Methodology

A systematic literature review (SLR) adapted from Tranfield et al [17] and Higgins & Green [18] is a useful methodology for investigating the trends and developments of scientific research in a field. This SLR for this study was based on the systematic review protocol seen in Table 1. For this research paper, a bibliometric analysis was used to investigate significant publication patterns, research methods and notable authorship characteristics in the application of MBSE to quantum computing.

The platform used for identifying the papers was Elsevier's Engineering Village database, Compendex, was used to capture the papers used for the scoping set. The scoping set helped in identifying studies based on the review protocol presented in Table 1. The capture rate used for the scoping set was 70% which means based on the search term, we were able to identify 7 out of 10 papers used for the analysis [19]. The initial search results from the platforms were 64 papers. After evaluating articles using their title and abstract and applying the exclusion criteria (as seen in Table 1) in the review protocol, the final paper set was 10 papers (published from 2009-2023). The team started collecting the attributes of the final paper set into an Excel database to get information about author characteristics, publication characteristics and research characteristics which is discussed in the next section.

4. Results and Discussion

This section discusses the characteristics of the final paper set based on authorship, publication quantity and research methods commonly used in the application of MBSE to quantum computing. It is worth mentioning that the final paper set of this analysis is sufficient to justify a SLR and draw significant conclusions that attest to the relevance of MBSE utilized in quantum computing. The key contribution of this review is that we identified an emerging domain; how MBSE is being used in quantum computing, trends in this field, bibliometrics of publications; therefore, setting the foundation for future work. Also, the number of papers needed for a systematic literature review (SLR) can vary depending on the research question, the scope of the review, and the field of study, as long as the selection process is systematic, reproducible, and well-documented.

4.1 Publication Trends

As seen in Figure 1 from the SLR, this shows that there is not an increasing publication trend that employs the use of MBSE in quantum computing. Figure 2 showing citations per year was calculated based on the total number of citations divided by the number of years since articles were published. Citations per year revealed that only one author from the selected literature was cited 3 times per year, but the others were only cited one time or none at all.

The most cited paper per year was Bonilla's [20] "Complexity Measure for Engineering Systems Incorporating System States and Behavior" which discusses the quantification of engineering system complexity derived from molecular quantum mechanics. This suggests that the visibility of the work in the area of quantum computing and MBSE needs to be improved. More collaborations with systems engineering professionals may also boost significant development of this research area.

4.2 Authors and Industries

As seen in Figure 3 visualizing the most common authors from the literature in the SLR, over half of the authors appear in 3 or more articles of literature, so the pool of researchers is relatively small and the topics of quantum computing and MBSE is a distinctively niche field.

Figure 4 reveals that this small group of researchers also strongly represents the Information Technology (IT) industry. Although applications of MBSE in quantum computing far transcend the realm of IT, it is necessary that research on these topics be further carried out by other domains and sectors in different industries.

4.3 Research Methods

As seen in Figure 5, a systematic assessment of the data collection and analysis methodologies employed within the sources revealed a dominant occurrence of secondary data, simulation, conceptual frameworks, and (math) modeling.

The lack of quantitative analysis such as regression, correlation, and descriptive statistics used among the sources implies limited availability of large datasets regarding MBSE and quantum technologies. Consequently, the high prevalence of secondary data reaffirms this limitation. Conceptual frameworks further enable the introduction of new MBSE applications by defining research questions and familiarizing readers with interconnections of past and present assumptions.

Figure 5 also outlines a small, yet significant pattern of case study and scenario analysis used to run simulated modeling and verify the usability of MSBE concepts in a quantum scope. Without substantial datasets to conduct field tests or query participants, test cases are often employed to actualize the functionality of theoretical MBSE frameworks. Also, none of the models have been validated. The results of these simulated tests, specifically and most commonly those involving SysML [20-25], may demonstrate the readiness of MBSE to be further evaluated in a real-world environment.

4.4 Use of MBSE in quantum computing

The articles used in the SLR were evaluated on their inclusion of 5 different MBSE principles (use of SysML, models, provided requirements, ran simulations, tested scenarios). As shown in Figure 6, 40% of the articles included all these principles, and 80% of the articles contained at least 4 out of 5.

Therefore, there was strong use of MBSE in the studied literature. Although there is not a high volume of literature that includes both quantum computing and MBSE, the strength of the presence of MBSE in the studied literature exemplifies the possibility MBSE possesses to transform the realm of quantum computing.

5. Conclusion

This research highlights the results of a SLR and bibliometric analysis of MBSE applications in quantum computing, identifies research gaps and proposed action for future work. The bibliometric analysis shows that although the use of MBSE in quantum computing applications started in 2008, the trend of interest in this area seems to be constant, neither increasing nor decreasing. This may be because the potential of quantum computing is still mostly theoretical. Here are the key findings from the SLR.

* The publications are mostly theoretical with the academic community leading the investigation and development of MBSE applications in quantum computing.

* Conceptual frameworks, modeling and simulation are the most used data analysis tools in this research area, suggesting that the articles are focused on understanding the structure of the systems.

* None of the models have been validated, which suggests that the contributions to this research area have been theoretical.

* The average citations per year are very low and suggest that the impact of the research area is not yet significant.

* In most of the publications, there was a strong use of MBSE techniques, tools and methods.

While MBSE applications are used to support quantum computing by exploring requirements, behavior, and structure of the system, the research area is very niche and is not well developed based on the assessment of the field. To advance this field, there needs to be more collaborations to improve the theoretical frameworks and concepts. This can be done by employing MBSE, which has the potential to improve the research area through requirements traceability, models, and documentation to support the behavior and structure of a quantum computing system.

This study is not without its limitations as this SLR is limited to the publications indexed on Compendex. Also, publications that didn't have a full-text available or were not in English language were not considered for the study. In addition, our final paper set was 10 because we used only one platform (Compendex). By using more platforms, we can draw data from more papers to further discuss the maturity of the field. In addition, the final paper set only considered theoretical applications in quantum computing. The future work on this project will be a more comprehensive search on other platforms. Furthermore, by investigating specific areas like SysML to model quantum computing, this may give more insights into this field of research.

References

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