Quantum computing is an emerging field of high interest. Many companies have started to work on developing more powerful and stable quantum computers. However, developers still struggle to master the art of programming with a quantum computer. One of the major challenges faced is the integration of quantum parts of a system with the classical one. This paper proposes a novel development model called Quantum-Algorithms-as-a-Service (QAaaS). This new model aims to allow developers to abstract the quantum components away from the design of the software they are building. The model leverages Software-as-a-Service and Function-as-a-Service to support multiple quantum cloud providers and run their algorithms regardless of the underlying hardware.
Quantum computing is an emerging field of high interest. Many companies have started to work on developing more powerful and stable quantum computers. However, developers still struggle to master the art of programming with a quantum computer. One of the major challenges faced is the integration of quantum parts of a system with the classical one. This paper proposes a novel development model called Quantum-Algorithms-as-a-Service (QAaaS). This new model aims to allow developers to abstract the quantum components away from the design of the software they are building. The model leverages Software-as-a-Service and Function-as-a-Service to support multiple quantum cloud providers and run their algorithms regardless of the underlying hardware.
Quantum computing is rapidly reaching a point in which its application design and engineering aspects have to be seriously considered. However, quantum software engineering is still in its infancy with numerous challenges, especially in dealing with the diversity of quantum programming languages and noisy intermediate-scale quantum systems. To alleviate these challenges, we propose QFaaS, a novel Quantum Function-as-a-Service framework, which leverages the advantages of the serverless model and state-of-the-art techniques to advance practical quantum computing in the NISQ era. Our framework provides essential elements of a serverless quantum system to streamline service-oriented quantum application development in cloud environments, such as combining hybrid quantum-classical computation, automating the backend selection, and adapting quantum DevOps techniques. QFaaS offers the first full-stack and unified quantum serverless platform by integrating multiple well-known quantum software development kits (Qiskit, Q#, Cirq, and Braket), quantum simulators, and cloud providers (IBM Quantum and Amazon Braket). This paper proposes the concept of quantum functions, software life cycle, system design, operation workflows, and implementation of QFaaS. We also present two practical use cases and performance evaluations on today’s quantum computers and simulators to demonstrate our framework’s capability to ease the burden on traditional engineers to expedite the ongoing quantum software transition.
Quantum computers (QCs) aim to disrupt the status-quo of computing - replacing traditional systems and platforms that are driven by digital circuits and modular software - with hardware and software that operate on the principle of quantum mechanics. QCs that rely on quantum mechanics can exploit quantum circuits (i.e., quantum bits for manipulating quantum gates) to achieve ‘quantum computational supremacy’ over traditional, i.e., digital computing systems. Currently, the issues that impede mass-scale adoption of quantum systems are rooted in the fact that building, maintaining, and/or programming QCs is a complex and radically distinct engineering paradigm when compared to the challenges of classical computing and software engineering. Quantum service orientation is seen as a solution that synergises the research on service computing and quantum software engineering (QSE) to allow developers and users to build and utilise quantum software services based on pay-per-shot utility computing model. The pay-per-shot model represents a single execution of instruction on quantum processing unit and it allows vendors (e.g., Amazon Braket) to offer their QC platforms, simulators, and software services to end-users. This research contributes by (i) developing a reference architecture for enabling Quantum Computing as a Service (QCaaS), (ii) implementing microservices with the quantum-classic split pattern as an architectural use-case, and (iii) evaluating the architecture based on practitioners’ feedback. The proposed reference architecture follows a layered software pattern to support the three phases of service lifecycle namely development, deployment, and split of quantum software services. In the QSE context, the research focuses on unifying architectural methods and service-orientation patterns to promote reuse knowledge and best practices to tackle emerging and futuristic challenges of architecting QCaaS.
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 computers (QCs) aim to disrupt the status-quo of computing -- replacing traditional systems and platforms that are driven by digital circuits and modular software -- with hardware and software that operates on the principle of quantum mechanics. QCs that rely on quantum mechanics can exploit quantum circuits (i.e., quantum bits for manipulating quantum gates) to achieve "quantum computational supremacy" over traditional, i.e., digital computing systems. Currently, the issues that impede mass-scale adoption of quantum systems are rooted in the fact that building, maintaining, and/or programming QCs is a complex and radically distinct engineering paradigm when compared to challenges of classical computing and software engineering. Quantum service orientation is seen as a solution that synergises the research on service computing and quantum software engineering (QSE) to allow developers and users to build and utilise quantum software services based on pay-per-shot utility computing model. The pay-per-shot model represents a single execution of instruction on quantum processing unit and it allows vendors (e.g., Amazon Braket) to offer their QC platforms, simulators, software services etc. to enterprises and individuals who do not need to own or maintain quantum systems. This research contributes by 1) developing a reference architecture for enabling quantum computing as a service, 2) implementing microservices with the quantum-classic split pattern as an architectural use-case, and 3) evaluating the reference architecture based on feedback by 22 practitioners. In the QSE context, the research focuses on unifying architectural methods and service-orientation patterns to promote reuse knowledge and best practices to tackle emerging and futuristic challenges of architecting and implementing Quantum Computing as a Service (QCaaS).
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.
Starting from the idea of Quantum Computing which is a concept that dates back to 80s, we come to the present day where we can perform calculations on real quantum computers. This sudden development of technology opens up new scenarios that quickly lead to the desire and the real possibility of integrating this technology into current software architectures. The usage of frameworks that allow computation to be performed directly on quantum hardware poses a series of challenges. This document describes a an architectural framework that addresses the problems of integrating an API exposed Quantum provider in an existing Enterprise architecture and it provides a minimum viable product (MVP) solution that really merges classical quantum computers on a basic scenario with reusable code on GitHub repository. The solution leverages a web-based frontend where user can build and select applications/use cases and simply execute it without any further complication. Every triggered run leverages on multiple backend options, that include a scheduler managing the queuing mechanism to correctly schedule jobs and final results retrieval. The proposed solution uses the up-to-date cloud native technologies (e.g. Cloud Functions, Containers, Microservices) and serves as a general framework to develop multiple applications on the same infrastructure.