Quantum network simulation is an essential step towards developing applications for quantum networks and determining minimal requirements for the network hardware. As it is with classical networking, a simulation ecosystem allows for application development, standardization, and overall community building. Currently, there is limited traction towards building a quantum networking community—there are limited open-source platforms, challenging frameworks with steep learning curves, and strong requirements of software engineering skills. Our Quantum Network Development Kit (QNDK) project aims to solve these issues. It includes a graphical user interface to easily develop and run quantum network simulations with very little code. It integrates various quantum network simulation engines and provides a single interface to them, allowing users to use the features from any of them. Further, it deploys simulation execution in a cloud environment, offloading strong computing requirements to a high-performance computing system. In this paper, we detail the core features of the QNDK and outline the development roadmap to enabling virtual quantum testbeds.
Quantum network simulation is an essential step towards developing applications for quantum networks and determining minimal requirements for the network hardware. As it is with classical networking, a simulation ecosystem allows for application development, standardization, and overall community building. Currently, there is limited traction towards building a quantum networking community—there are limited open-source platforms, challenging frameworks with steep learning curves, and strong requirements of software engineering skills. Our Quantum Network Development Kit (QNDK) project aims to solve these issues. It includes a graphical user interface to easily develop and run quantum network simulations with very little code. It integrates various quantum network simulation engines and provides a single interface to them, allowing users to use the features from any of them. Further, it deploys simulation execution in a cloud environment, offloading strong computing requirements to a high-performance computing system. In this paper, we detail the core features of the QNDK and outline the development roadmap to enabling virtual quantum testbeds.
As quantum network technologies develop, the need for teaching and engineering tools such as simulators and emulators rises. QuNetSim addresses this need. QuNetSim is a Python software framework that delivers an easy-to-use interface for simulating quantum networks at the network layer, which can be extended at little effort of the user to implement the corresponding link layer protocols. The goal of QuNetSim is to make it easier to investigate and test quantum networking protocols over various quantum network configurations and parameters. The framework incorporates many known quantum network protocols so that users can quickly build simulations using a quantum-networking toolbox in a few lines of code and so that beginners can easily learn to implement their own quantum networking protocols. Unlike most current tools, QuNetSim simulates with real time and is, therefore, well suited to control laboratory hardware. Here, we present a software design overview of QuNetSim and demonstrate examples of protocols implemented with it. We describe ongoing work, which uses QuNetSim as a library, and describe possible future directions for the development of QuNetSim.
The rise of quantum networks has revolutionized domains such as communication, sensing, and cybersecurity. Despite this progress, current quantum network systems remain limited in scale, are highly application-specific (e.g., for quantum key distribution), and lack a clear road map for global expansion. These limitations are largely driven by a shortage of skilled professionals, limited accessibility to quantum infrastructure, and the high complexity and cost associated with building and operating quantum hardware. To address these challenges, this paper proposes an open-access software-based quantum network virtualization platform designed to facilitate scalable and remote interaction with quantum hardware. The system is built around a cloud application that virtualizes the core hardware components of a lab-scale quantum network testbed, including the time tagger and optical switch, enabling users to perform coincidence counts of the photon entanglements while ensuring fair resource allocation. The fairness is ensured by employing the Hungarian Algorithm to allocate nearly equal effective entanglement rates among users. We provide implementation details and performance analysis from the perspectives of hardware, software, and cloud platform, which demonstrates the functionality and efficiency of the developed prototype.
In a world of various competing quantum computing architectures, hardware-agnostic, full-stack platforms are necessary to bring the full power of quantum computing hardware to domain experts via the cloud. QCI Connect and its Software Development Kit provide a reference architecture for a full-stack platform with a modular design and open-source interface definitions, built to facilitate a community-driven application ecosystem. Here, we present its overall design and features, central interfaces, and lessons learned, both for users of the platform and as a reference guide for future developments.
As quantum computing continues to progress, there is an increasing need for standardized quantum network technology [1], [2] to connect quantum computers together. Experimental testbeds are necessary in order to develop quantum network software and hardware. Building a scalable testbed for data center-level quantum networks requires overcoming numerous engineering and technical challenges in quantum communications, quantum processing and quantum storage. In this work, we describe a software framework for use with an all-photonic quantum networking testbed. This framework is designed for rapid development and capable of automated execution of quantum experiments. We introduce PnPQ, an open-source, unified driver library for hardware commonly used in quantum optical experiments. On top of this low-level hardware control library, we present software modules for controlling and coordinating quantum network nodes using remote procedure calls (RPC). Finally, we describe high-level software for performing and analyzing quantum photonic experiments using these software modules. As a whole, these software components comprise the first version of a framework that will enable us to implement and test quantum network architectures. This framework is intended to help us move forward from building simple experiments to complex Quantum systems.
The Intel(R) Quantum Software Development Kit (SDK) offers a comprehensive platform for developers to create quantum applications using an LLVM-based compiler with user-friendly C++ language extensions. This full-stack solution facilitates the expression and optimization of quantum circuits and includes a quantum runtime library for seamless hybrid execution between classical and quantum kernels. The runtime enables dynamic parameter determination for quantum circuits, allowing both quantum and classical components of variational algorithms to be defined within a single program, compiled once, and significantly reducing execution latency. The SDK features a suite of quantum simulators, including simulations of Intel's quantum hardware components such as qubit control processors, control electronics, and quantum dot qubits. With a unified interface, the Intel Quantum SDK allows users to target ideal qubit simulators, realistic Intel quantum hardware simulators, and future Intel quantum hardware, enabling efficient optimization, compilation, and execution of scalable hybrid quantum-classical variational algorithms.
Quantum simulation is a leading candidate for demonstrating practical quantum advantage over classical computation, as it is believed to provide exponentially more compute power than any classical system. It offers new means of studying the behaviour of complex physical systems, for which conventionally software-intensive simulation codes based on numerical high-performance computing are used. Instead, quantum simulations map properties and characteristics of subject systems, for instance chemical molecules, onto quantum devices that then mimic the system under study.
Currently, the use of these techniques is largely limited to fundamental science, as the overall approach remains tailored for specific problems: We lack infrastructure and modelling abstractions that are provided by the software engineering community for other computational domains.
In this paper, we identify critical gaps in the quantum simulation software stack-particularly the absence of general-purpose frameworks for model specification, Hamiltonian construction, and hardware-aware mappings. We advocate for a modular model-driven engineering (MDE) approach that supports different types of quantum simulation (digital and analogue), and facilitates automation, performance evaluation, and reusability. Through an example from high-energy physics, we outline a vision for a quantum simulation framework capable of supporting scalable, cross-platform simulation workflows.