Quantum computing, albeit readily available as hardware or emulated on the cloud, is still far from being available in general regarding complex programming paradigms and learning curves. This vision paper introduces Classi|Q⟩, a translation framework idea to bridge Classical and Quantum Computing by translating high-level programming languages, e.g., Python or C++, into a low-level language, e.g., Quantum Assembly. Our idea paper serves as a blueprint for ongoing efforts in quantum software engineering, offering a roadmap for further Classi|Q⟩ development to meet the diverse needs of researchers and practitioners. Classi|Q⟩ is designed to empower researchers and practitioners with no prior quantum experience to harness the potential of hybrid quantum computation. We also discuss future enhancements to Classi|Q⟩, including support for additional quantum languages, improved optimization strategies, and integration with emerging quantum computing platforms.
Quantum computing, albeit readily available as hardware or emulated on the cloud, is still far from being available in general regarding complex programming paradigms and learning curves. This vision paper introduces Classi|Q⟩, a translation framework idea to bridge Classical and Quantum Computing by translating high-level programming languages, e.g., Python or C++, into a low-level language, e.g., Quantum Assembly. Our idea paper serves as a blueprint for ongoing efforts in quantum software engineering, offering a roadmap for further Classi|Q⟩ development to meet the diverse needs of researchers and practitioners. Classi|Q⟩ is designed to empower researchers and practitioners with no prior quantum experience to harness the potential of hybrid quantum computation. We also discuss future enhancements to Classi|Q⟩, including support for additional quantum languages, improved optimization strategies, and integration with emerging quantum computing platforms.
Since the invention of Quantum Computing (QC) in the 1980s, substantial claims about QC’s ability to solve computational problems of unparalleled complexity have emerged. However, forty years later, no significant real-world QC applications exist. Indeed, the availability of small-scale noisy quantum computers is to blame. Still, simultaneously, the programming of quantum computers is too close to quantum hardware, requiring software engineers with specialized backgrounds to build QC applications and limiting the maximum exploitation of QC’s potential. Thus, there is a need for an abstract yet intuitive quantum-oriented paradigm (QOP) for building QC applications, similar to the object-oriented paradigm established in the 1960s for classical computers that laid the foundations of modern programming and modeling languages for classical computers. Unfortunately, such a QC paradigm doesn’t exist. Thus, we foresee the need to build a novel QOP based on which future quantum programming and modeling languages shall be developed. Such QOP shall enable users with diverse backgrounds (e.g., computer scientists, software engineers, and physicists) to build QC applications cost-effectively, intuitively, and independently of low-level quantum mechanics characteristics (e.g., superposition and entanglement). This paper discusses the emerging work of QOP and presents research directions that the software engineering and programming communities can follow to build a successful QOP.
This paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum Computing (QC) such as the need for integrating diverse programming languages and managing the complexities of quantum-classical systems, this model is rooted in the principles of DevOps and continuous software engineering. It presents a comprehensive lifecycle for quantum software development, encompassing quantum-agnostic coding, testing, deployment, cloud computing services, orchestration, translation, execution, and interpretation phases. Each phase is designed to accommodate the unique demands of QC, enabling traditional software developers to engage with QC environments without needing in-depth QC expertise. The paper presents a detailed implementation roadmap, utilizing a range of existing tools and frameworks, thereby making quantum software development more accessible and efficient. The proposed model not only addresses current challenges in quantum software development but also makes a substantial contribution to the field of Quantum Software Engineering (QSE). By proposing a structured and accessible model, it sets the stage for further advancements and research in QSE, enhancing its practicality and relevance in a wide range of applications.
Quantum Computing (QC) is transitioning from theoretical frameworks to an indispensable powerhouse of computational capability, resulting in extensive adoption across both industrial and academic domains. QC presents exceptional advantages, including unparalleled processing speed and the potential to solve complex problems beyond the capabilities of classical computers. Nevertheless, academic researchers and industry practitioners encounter various challenges in harnessing the benefits of this technology. The limited accessibility of QC resources for classical developers, and a general lack of domain knowledge and expertise, represent insurmountable barrier, hence to address these challenges, we introduce a framework- Quantum Computing as a Service for Hybrid Classical-Quantum Software Development (QCSHQD), which leverages service-oriented strategies. Our framework comprises three principal components: an Integrated Development Environment (IDE) for user interaction, an abstraction layer dedicated to orchestrating quantum services, and a service provider responsible for executing services on quantum computer. This study presents a blueprint for QCSHQD, designed to democratize access to QC resources for classical developers who want to seamless harness QC power. The vision of QCSHQD paves the way for groundbreaking innovations by addressing key challenges of hybridization between classical and quantum computers.
Quantum computing leverages the principles of quantum mechanics to perform computations far beyond the capabilities of classical systems, particularly in fields such as cryptography and optimization. However, current quantum programming languages often require low-level implementation, posing significant barriers for many developers due to their steep learning curve and limited abstraction. In response, we introduce Qutes, a high-level quantum programming language designed to simplify quantum algorithm development while maintaining the flexibility required for advanced applications. By abstracting complex quantum operations and allowing intuitive expressions through high-level constructs, Qutes enables users to write efficient quantum programs without extensive knowledge of quantum mechanics or circuit design. Built upon Qiskit, Qutes translates its syntax directly into executable quantum code, facilitating seamless integration with quantum hardware. This paper provides an overview of the language's architecture, core functionalities, and its ability to unify classical and quantum operations within a single framework. Additionally, we demonstrate Qutes' application in key quantum algorithms, showcasing its potential to make quantum programming more accessible and practical for a wider range of developers and researchers.
Traditional compiler optimization focuses on maximizing performance within the constraints of classical architectures. However, quantum computing presents a fundamentally different paradigm, demanding a new approach to software optimization. This paper proposes a hardware-aware compiler optimization technique, inspired by quantum computing principles, to bridge the gap between high-level programming languages and the specific characteristics of quantum hardware. The core idea is to translate high-level code into quantum circuits while explicitly considering factors like qubit connectivity, gate fidelity, and decoherence. This approach allows for optimization strategies tailored to the unique limitations and opportunities of quantum devices, potentially leading to significant performance improvements compared to generic quantum compilation methods. The compiler operates by analyzing the algorithmic complexity, identifying quantum-native operations, and strategically mapping them onto the available quantum hardware, thereby minimizing the impact of hardware constraints. This paper outlines the framework, key components, and potential optimizations within this hardware-aware compiler.
There are no doubts that quantum programming and, in general, quantum computing, is one of the most promising areas within computer science and one of the areas where most expectations are being placed in recent years. Although the days when reliable and affordable quantum computers will be available is still a long way off, the explosion of programming languages for quantum programming has grown exponentially in recent years. The software engineering community has been quick to react to the need to adopt and adapt well-known tools and methods for software development, and for the design of new ones tailored to this new programming paradigm. However, many key aspects for its success depend on the establishment of an appropriate conceptual framework for the conception and design of quantum programs. This article discusses the concept of module, key in the software engineering discipline, and establishes initial criteria for determining the cohesion and coupling levels of a module in the field of quantum programming as a first step towards a sound quantum software engineering. As detailed in the article, the conceptual differences between classical and quantum computing are so pronounced that the translation of classical concepts to the new programming approach is not straightforward.