Quantum computing technologies are rapidly evolving into a highly heterogeneous ecosystem of quantum devices and their interconnection networks. Concurrently, searching for real-world applications that display quantum advantage demands capabilities beyond any current single technology. In this position paper, we highlight the importance and the timeliness of a unified, community-wide effort to conceptualize and implement abstract, standardized frameworks for distribution of quantum computing across hybrid networks as a fundamental step towards practical and advantageous quantum computing, maximizing return on investment in the NISQ-era and beyond. These frameworks will ultimately encapsulate many details of such heterogeneous systems, keeping them transparent to quantum application developers while exposing them to quantum architecture and network researchers.
Quantum computing technologies are rapidly evolving into a highly heterogeneous ecosystem of quantum devices and their interconnection networks. Concurrently, searching for real-world applications that display quantum advantage demands capabilities beyond any current single technology. In this position paper, we highlight the importance and the timeliness of a unified, community-wide effort to conceptualize and implement abstract, standardized frameworks for distribution of quantum computing across hybrid networks as a fundamental step towards practical and advantageous quantum computing, maximizing return on investment in the NISQ-era and beyond. These frameworks will ultimately encapsulate many details of such heterogeneous systems, keeping them transparent to quantum application developers while exposing them to quantum architecture and network researchers.
Quantum computing communication interfaces are emerging as a fundamental technology for enabling seamless interaction between quantum processors, classical computing systems, cloud infrastructures, and distributed quantum networks. The development of efficient communication interfaces is essential to address challenges such as quantum state transmission, synchronization, error correction, latency, scalability, and interoperability across heterogeneous computing environments. This paper presents a comprehensive study of quantum computing communication interfaces by examining their architecture, communication protocols, hardware components, and software integration mechanisms. The proposed framework incorporates quantum-classical hybrid communication, quantum networking principles, secure quantum key distribution, adaptive resource management, and intelligent error mitigation techniques to improve communication reliability and computational efficiency. Furthermore, the study investigates the role of emerging technologies such as quantum internet, photonic interconnects, edge-cloud integration, and artificial intelligence in enhancing interface performance. Performance evaluation demonstrates that the proposed communication interface architecture achieves reduced communication latency, improved transmission fidelity, enhanced scalability, optimized resource utilization, and stronger security compared with conventional quantum communication approaches. The findings indicate that intelligent quantum communication interfaces can significantly accelerate the practical deployment of distributed quantum computing systems and future large-scale quantum applications.
The realization of large-scale quantum networks requires more than advances in quantum repeaters, memories, and processors, it requires a framework explaining how heterogeneous quantum technologies evolve from isolated deployments into interconnected infrastructures. While the classical Internet evolved under strong utility incentives associated with resource sharing and communication demands, quantum networking currently lacks dominant applications capable of generating comparable incentives. As a consequence, contemporary quantum networks are largely formed through technology-driven decisions motivated by technical feasibility, experimental validation, and expected future value. This work argues that the absence of utility-driven network formation is not solely a consequence of immature applications, but also of insufficient abstraction. In particular, heterogeneous quantum platforms remain tightly coupled to the functionalities they provide, preventing the definition of technology-independent utility functions. A hierarchical architecture consisting of Physical Platforms (PP), Functionalities (F), Services (S), Applications (A), and Use-Cases (UC) is proposed, together with the argument that quantum interconnects constitute the enabling technology required to decouple physical implementations from network functionalities. Such decoupling permits the definition of utility functions at the functionality level and establishes the conditions under which strategic (agent-based) network formation becomes applicable. Quantum interconnects should therefore be viewed not only as interoperability devices, but also as fundamental enablers of strategic quantum network evolution.
Quantum computing has the potential to solve complex problems that are outside the scope of classical systems, making it a standard shifter. Current devices, which are considered as Noisy Intermediate-Scale Quantum (NISQ) systems, are insufficient in their practical utility due to hardware limitations, error rates, and qubit counts. The dynamic growths wanted to exceed the NISQ era and grow scalable quantum algorithms and architectures that can achieve useful quantum benefit in real-world applications are reviewed in this research. This research gives a comprehensive examination of the complications in scaling quantum systems, adjacent resource efficacy, qubit connectivity, and error correction. In addition to connecting architectural innovations like modular quantum computing, error-resilient circuit design, and distributed quantum systems, the paper provides new hybrid quantum-classical algorithms planned to exploit performance in noisy environments. Results from benchmarking in arenas like machine learning, optimization, and quantum chemistry show how these methods can provide short-term quantum benefit. Lastly, this paper proposes a research roadmap for quantum computing that highlights the requirement of co-designing algorithms, software, and hardware. The goal of this effort is to straighten the progress of quantum systems that can resolve problems in the real world at scale by addressing the inadequacies of NISQ devices and emphasizing scalable solutions.
Abstract Quantum computing leverages fundamental quantum-mechanical phenomena—most notably superposition, entanglement, and quantum tunneling—to perform computations in ways that differ fundamentally from classical digital processing. Compared to conventional computing architectures, quantum systems promise significant reductions in computational time and potentially lower energy consumption for specific classes of problems. These advantages, combined with advances in nanoscale engineering and the slowing of traditional hardware scaling trends such as Moore’s Law, have led to substantial commercial and national-security-driven investments in quantum technologies over the past decade. A major milestone was reached when Google announced the experimental demonstration of “quantum supremacy,” showing that a quantum processor could execute a specific computational task infeasible for a classical supercomputer within practical time constraints. Although the demonstrated problem had no immediate practical application, this achievement marked a crucial step toward the development of quantum systems capable of delivering real-world computational advantages and provided a more precise technical framing of the concept of quantum advantage. Despite the fact that the mathematical foundations, programming models, and principal quantum algorithms were established in the 1990s, quantum computing remained largely confined to a specialized research community for decades. Today, the increasing accessibility of cloud-based quantum hardware calls for a broader dissemination of implementation-oriented knowledge among researchers and practitioners in computer science, software engineering, and related fields. The quantum programming paradigm differs fundamentally from classical programming models and often relies on physical and algebraic notations that may pose barriers to traditionally trained computer scientists. This series of articles provides a self-contained and concise introduction to quantum computing and its core algorithms, with a strong emphasis on practical implementation. Given that real quantum processors—such as those accessible via the IBM quantum ecosystem—are now available as cloud services, experimental validation can be conducted both on simulators and on actual hardware for small-scale inputs. While other platforms such as Rigetti and IonQ also offer cloud-based quantum computing services, this review focuses exclusively on the IBM quantum computing ecosystem.
The rapid advancement of quantum computing has, without question, outpaced the rate of the subsequent setting up of an appropriate framework to categorize its various technologies. This has resulted in essentially fragmented terminologies with research efforts being considered in isolation, limiting collaboration or adaptation by industry. This chapter intends to fill the gap by introducing a multidimensional taxonomic approach to help develop a coherent and standardized framework for terminology in quantum computing. The proposed framework separates itself from existing frameworks by unifying four significant dimensions: computational models, hardware implementations, algorithmic strategies, and application domains. Its modular nature promotes relative ease of adaptation to emerging technologies, such as diamond-based qubits and cloud-based quantum platforms. The theoretical framework upon which this model has been developed is based on systematic literature review, domain analysis, and expert consultation. Using comparative benchmarking and real-world scenarios, the framework documents its flexibility in coordinating technical capabilities with market demands. For academia, it offers a structured curriculum tool and research roadmap, whereas, for industry, it clarifies investment priorities and benchmarks technological advancements. The identified challenges such as complexity and maintenance demands, are acknowledged with solutions proposed through dynamic updating mechanisms and collaborative governance. Providing a common terminology and adaptable structure not only organizes present knowledge but also makes possible a faster transfer of theoretical breakthroughs to social impact. It allows stakeholders to conduct complex tasks on quantum computing technology and ensure equitable and sustainable utilization of its future transformative potential.
Distributed Quantum Computing (DQC) is essential for scaling quantum algorithms beyond the limitations of monolithic NISQ devices. However, the current software ecosystem forces developers to manually orchestrate low-level network resources, such as entanglement generation (EPR pairs) and classical synchronization, leading to verbose, error-prone, and non-scalable code. This paper introduces \textbf{NetQMPI}, a high-level Python framework that adapts the Message Passing Interface (MPI) standard to the quantum domain using the Single Program Multiple Data (SPMD) paradigm. Built as a middleware over the NetQASM SDK, NetQMPI abstracts the underlying physical topology, automating network initialization and resource management through a unified Communicator interface. We propose semantic point-to-point primitives and novel collective operations--such as expose and unexpose--that address the constraints of the No-Cloning Theorem by leveraging multipartite entanglement for data distribution. Our comparative analysis demonstrates that NetQMPI decouples algorithmic logic from network size, reducing the code complexity for generating an N-node GHZ state from O(N2) to constant complexity O(1). Furthermore, the framework ensures backend agnosticism, enabling the seamless execution of high-level applications on rigorous physical simulators, such as NetSquid (via SquidASM), and future quantum hardware adhering to the NetQASM standard.