Achievements and Challenges in Quantum Software Engineering
DOI:
https://doi.org/10.15407/intechsys.2025.04.045Keywords:
information technology, quantum software, software engineering, quantum computersAbstract
Introduction. Quantum computers have been developing rapidly in recent decades, as they use the principles of quantum mechanics to process information and have the potential to perform certain tasks much faster than classical computers. There are at least two groups of problems where quantum computers can outperform classical computers, namely: 1) problems requiring a large amount of parallel computing, such as optimization, encryption, big data analysis, artificial intelligence, machine learning, etc.; 2) problems requiring efficient and accurate modeling of quantum phenomena in fields such as physics, chemistry, biology, physiology, medicine and materials science, etc., which is key to creating new materials, supporting advanced aeronautics and biotechnology, producing new vaccines, and finding treatments for various diseases, etc.
Although for now quantum computers still belong to the so-called “noisy midscale quantum computers”, there is every reason to believe that the huge efforts and investments directed by the scientific community and business to develop stable quantum processors will allow these computers to go beyond the quantum era of mid-scale computing in the coming years. This opens up new, practically unlimited possibilities for quantum computers in all areas of human activity and at the same time significantly complicates the problem of effective use of their enormous computing power. Solving this problem is impossible without the availability of appropriate specification and verification methods, tools and processes for developing quantum software, which must be planned, designed, coded, evaluated, tested, convenient to use, etc. Since quantum computing differs from classical computing at a fundamental level, and the architecture of quantum computers is not a von Neumann architecture, it is practically impossible to transfer all the achievements of classical software engineering to the quantum sphere. Therefore, in recent years, all developed countries have significantly increased financial and resource investments in the creation of a new scientific direction “Quantum Software Engineering”, which should study concepts, principles, processes and develop recommendations for the development, support and advancement of quantum programs and be aimed at improving their quality and reusability through the systematic application of quantum software development principles at all stages of the life cycle, from the initial analysis of requirements to decommissioning.
The purpose of the paper is to study the features of quantum computing, the architecture of hybrid quantum-classical computing systems and the basic principles of quantum software engineering, analyze its most active areas, existing successes and challenges in this field for the near future.
Methods. The analysis of recent achievements in the field of quantum software engineering is carried out and it is shown that the development of quantum software requires, for the most part, fundamentally new methods and approaches compared to classical software development.
Results and conclusions. Due to the fundamental differences between classical and quantum computing, the application of methods and tools of well-developed classical software engineering to the development of quantum software is mostly pointless. Currently, there is an urgent need to create a new fundamental discipline “Quantum Software Engineering” with the broad involvement of both scientific and industrial circles in this process. The first steps in this direction have already been taken. There are some successes, but many unresolved problems and open questions remain. This paper presents the basic principles and theoretical background for the need to develop “Quantum Software Engineering”, as well as discusses existing problems and analyzes achievements in this field, which is used to identify necessary breakthroughs and future research directions.
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