Quantum computing (QC) holds promise for next-generation applications that requires exponential time to solve NP problems. However, even after 25+ years, researchers still struggle with stable error correction solutions for delivering a stable commercialised quantum universal quantum machine. Companies like IBM, Rigetti, and D-Wave have already started offering quantum annealers, intermediate quantum devices based on the qubit. Therefore, researchers believe that QC would be introduced as an extension of classical computers (CC), where CC would offload a specific computational intensive task. Cloud companies, including Amazon, Azure, and IBM, have already begun to provide cloud services where an organisation can use a QC to work on potential applications. This paper systematically analyses the need to provide QC as a service (QCaaS) for potential applications. Furthermore, we discuss the framework on which this service can be offered. Subsequently, we provide a detailed discussion of various toolkits, libraries, and simulators available for QC.
Quantum computing (QC) holds promise for next-generation applications that requires exponential time to solve NP problems. However, even after 25+ years, researchers still struggle with stable error correction solutions for delivering a stable commercialised quantum universal quantum machine. Companies like IBM, Rigetti, and D-Wave have already started offering quantum annealers, intermediate quantum devices based on the qubit. Therefore, researchers believe that QC would be introduced as an extension of classical computers (CC), where CC would offload a specific computational intensive task. Cloud companies, including Amazon, Azure, and IBM, have already begun to provide cloud services where an organisation can use a QC to work on potential applications. This paper systematically analyses the need to provide QC as a service (QCaaS) for potential applications. Furthermore, we discuss the framework on which this service can be offered. Subsequently, we provide a detailed discussion of various toolkits, libraries, and simulators available for QC.
Quantum systems have started to emerge as a disruptive technology and enabling platforms - exploiting the principles of quantum mechanics via programmable quantum bits (QuBits) - to achieve quantum supremacy in computing. Academic research, industrial projects (e.g., Amazon Braket, IBM Qiskit), and consortiums like 'Quantum Flagship' are striving to develop practically capable and commercially viable quantum computing (QC) systems and technologies. Quantum Computing as a Service (QCaaS) is viewed as a solution attuned to the philosophy of service-orientation that can offer QC resources and platforms, as utility computing, to individuals and organisations who do not own quantum computers. This research investigates a process-centric and architecture-driven approach to offer a software engineering perspective on enabling QCaaS - a.k.a quantum service-orientation. We employed a two-phase research method comprising (a) a systematic mapping study and (b) an architecture-based development, first to identify the phases of the quantum service development life cycle and subsequently to integrate these phases into a reference architecture that supports QCaaS. The SMS process retrieved a collection of potentially relevant research literature and based on a multi-step selection and qualitative assessment, we selected 41 peer-reviewed studies to answer three RQs. The RQs investigate (i) demographic details in terms of frequency, types, and trends of research, (ii) phases of quantum service development lifecycle to derive a reference architecture for conception, modeling, assembly, and deployment of services, and (iii) The results identify a 4-phased development lifecycle along with quantum significant requirements (QSRs), various modeling notations, catalogue of patterns, programming languages, and deployment platforms that can be integrated in a layered reference architecture to engineer QCaaS.
Quantum computing is a transformative paradigm based on the principles of quantum mechanics such as superposition and entanglement to outperform classical computers in solving complex problems. This paper presents a comprehensive overview of quantum computing, detailing its foundational concepts, advancements, applications, platforms, limitations, and future scope. Key research contributions from organizations such as IBM, AWS, and Microsoft, as well as government initiatives, are discussed. Applications are explored across cryptography, pharmaceuticals, healthcare, finance, manufacturing, simulation, and AI. Quantum platforms such as Qiskit, Azure Quantum, and D-Wave Ocean SDK are also reviewed. Although still in its development stages and facing challenges, quantum computing faces difficulties related to error correction and the environment may entirely change modern computing. The article concludes by stressing the need for continuous research, education, strategic planning, and development to utilize the disruptive abilities of quantum technologies.
The convergence of quantum computing and cloud platforms represents a significant paradigm shift in the landscape of digital services, creating unprecedented opportunities for technological advancement. This article provides an extensive review of this integration, examining its technological underpinnings, the current state of commercial and public-sector services, emerging applications, and the persistent challenges that define its developmental trajectory. By synthesizing recent academic literature, detailed industry reports, and policy analyses, we explore the transition from theoretical concepts to practical, accessible quantum systems. We detail the progress made in the Noisy Intermediate-Scale Quantum (NISQ) era, marked by significant hardware advancements from leaders like IBM and Google, and the development of crucial error mitigation techniques that extend the utility of current processors. Key findings indicate that cloud access is the primary mechanism for democratizing quantum resources, accelerating research, and enabling the exploration of high-value use cases in sectors such as finance, pharmaceuticals, and manufacturing. Furthermore, we investigate the growing adoption by non-profit organizations to tackle complex social and environmental challenges. However, substantial hurdles related to quantum decoherence, hardware scalability, software architecture, and the quantum-classical interface remain. The discussion contextualizes these findings, highlighting the strategic importance of national policies, the industry's push towards fault-tolerant systems, and the long-term vision of hybrid quantum-classical supercomputing. We conclude that while the path to achieving full-scale, fault-tolerant quantum computing is long and complex, its integration with cloud infrastructure is the critical catalyst, paving the way for a new frontier in computational capability and societal problem-solving.
Quantum Computing (QC) has emerged as a breakthrough technology with the potential to revolutionize Artificial Intelligence (AI) applications. By leveraging quantum mechanics principles, QC exponentially increases computational capacity, enabling accelerated data processing and optimization. The cloud availability of quantum computers facilitates their integration with existing cloud AI services, potentially offering the most promising route to exploit quantum algorithms within current cloud infrastructures. This chapter explores the interactions between quantum computing and cloud-based AI services, summarizing recent advances in implementation and the unique advantages of QC services compared to traditional cloud-based AI services. It also calls attention to open questions and potential areas of development. The authors give a comprehensive overview of quantum algorithms, hybrid quantum-classical models, and real-world implementations. The authors also explore the ways AI-cloud companies will be affected after major cloud providers enter the world of quantum computing-based business. This chapter also looks at security challenges, fundamental scalability limitations, and future research directions, with insights into how quantum computing will reshape the AI landscape over the next few decades.
Quantum computing was proposed to simulate processes that surpass the capabilities of its counterpart, classical computing. Utilizing the principles of quantum mechanics, it improves the computing power of quantum computing. Top developers namely IBM, Rigetti, D-Wave, Qutech and Google have invested greatly in the technology. Nowadays, users can access the quantum computing system publicly over the network in a cloud environment, this system architecture is known as cloud-based quantum computing. However, different developers deliver different architecture and functionality of the system on their platforms. This has indirectly spawned a question of which cloud-based quantum computing platform is a better option based on certain specific requirements by an individual or group. The main objective of this study is to provide a proposed framework using the existing cloud-based service of quantum computing based on previous studies for users with their specific demands.
The integration of quantum computing into cloud services represents a revolutionary advancement in processing capabilities.Quantum computers, utilizing principles of quantum mechanics, offer unparalleled computational speeds, allowing cloud providers to deliver quantum processing units alongside traditional CPUs and GPUs.Accessible through Quantum Computing as a Service (QCaaS), this facilitates businesses and researchers in harnessing quantum power without substantial upfront investments.Hybrid cloud solutions seamlessly blend classical and quantum processing, opening new frontiers in optimization and cryptography.The integration accelerates quantum machine learning and supports global quantum research.Concurrently, cloud computing's elasticity and pay-as-you-go model attract businesses.This paper explores the reciprocal impact of quantum technology on cloud computing and vice versa, recognizing the rapid development of quantum technology.The study evaluates cloud quantum computing services, revealing key factors influencing execution time.This research provides insights for informed decision-making based on service specifications.