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arXiv:2512.11483 · IEEE Access

NetQMPI: An MPI-Inspired library for programming Distributed Quantum Applications over Quantum Networks using NetQASM SDK

F. Javier Cardama, Tomás F. Pena

quant-phSubmitted Dec 12, 2025• Announced Dec 15, 2025• 0 citations• Revised Dec 26, 2025 (v2)
v1 · Dec 12, 2025v2 · Dec 26, 2025
arXivHTMLPDF

Abstract

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 $\mathcal{O}(N^2)$ to constant complexity $\mathcal{O}(1)$. 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.

DOI
10.1109/ACCESS.2026.3723566

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Distributed quantum computing (DQC) is emerging as a practical solution to overcome the scalability limits of individual quantum processors by interconnecting them via quantum networks. However, programming such systems remains a significant challenge due to the need to coordinate quantum operations, manage entanglement, and synchronize classical communication. This paper proposes NetQMPI as a Python library that enables high-level programming of distributed quantum applications by building on top of two key foundations: NetQASM, which abstracts the physical network layer to interface with quantum nodes and simulators such as NetSquid and SimulaQron; and NetQIR, which proposes a layered abstraction model suitable for defining a quantum version of the classical Message Passing Interface (MPI). NetQMPI provides an MPI-style programming model tailored to quantum systems. It introduces primitives such as qsend and qrecv that abstract quantum communication details like entanglement generation, and protocols. Collective operations such as qscatter or qgather are also included. This allows developers to focus on distributed algorithm design while relying on NetQMPI to handle low-level operations efficiently.
The rapid advancement of quantum computing has highlighted the need for scalable and efficient software infrastructures to fully exploit its potential. Current quantum processors face significant scalability constraints due to the limited number of qubits per chip. In response, distributed quantum computing (DQC) —achieved by networking multiple quantum processor units (QPUs)— is emerging as a promising solution. To support this paradigm, robust intermediate representations (IRs) are needed to translate high-level quantum algorithms into executable instructions suitable for distributed systems. This paper presents NetQIR, an extension of Microsoft’s Quantum Intermediate Representation (QIR), specifically designed to facilitate DQC by incorporating new instruction specifications. NetQIR was developed in response to the lack of abstraction at the network and hardware layers identified in the existing literature as a significant obstacle to effectively implementing distributed quantum algorithms. Based on this analysis, NetQIR introduces new essential abstraction features to support compilers in DQC contexts. It defines network communication instructions independent of specific hardware, abstracting the complexities of inter-QPU communication. Although the proposed work allows abstraction of the underlying network, it is important to note that it is intended for the development of high-performance code on future modular quantum architectures. Leveraging the QIR framework, NetQIR aims to bridge the gap between high-level quantum algorithm design and low-level hardware execution, thus promoting modular and scalable approaches to quantum software infrastructures for distributed applications. Furthermore, its design may serve as a foundational component for future implementations of distributed quantum standards such as the Quantum Message Passing Interface (QMPI).
Abstract We introduce NetQASM, a low-level instruction set architecture for quantum internet applications. NetQASM is a universal, platform-independent and extendable instruction set with support for local quantum gates, powerful classical logic and quantum networking operations for remote entanglement generation. Furthermore, NetQASM allows for close integration of classical logic and communication at the application layer with quantum operations at the physical layer. This enables quantum network applications to be programmed in high-level platform-independent software, which is not possible using any other QASM variants. We implement NetQASM in a series of tools to write, parse, encode and run NetQASM code, which are available online. Our tools include a higher-level software development kit (SDK) in Python, which allows an easy way of programming applications for a quantum internet. Our SDK can be used at home by making use of our existing quantum simulators, NetSquid and SimulaQron, and will also provide a public interface to hardware released on a future iteration of Quantum Network Explorer.
Distributed quantum computing (DQC) seeks to scale beyond the limits of monolithic processors by interconnecting multiple quantum processing units (QPUs) through entanglement-based links. Realizing this vision requires the co-design of hardware and software across the domains of quantum networking, compilation, and scheduling, yet existing tools remain fragmented between monolithic circuit compilers and long-distance quantum network simulators. We present an open-source, topology-informed framework for the compilation and scheduling of distributed quantum programs. Given an input circuit and a description of the target network, the framework partitions and reconstructs the circuit into a distributed program that respects the specified inter- and intra-QPU topology, covers cross-QPU operations through gate and state teleportation, and schedules the result under either deterministic or stochastic entanglement-generation models. By accepting and emitting standard OpenQASM, the framework interoperates with existing monolithic toolchains, and its standardized module interfaces allow partitioning and scheduling strategies to be interchanged and benchmarked. Using this framework, we show that the best-performing compilation strategy varies across the tested circuits and network configurations, and that both network topology and intra-QPU connectivity substantially affect the entanglement cost of execution. These findings underscore the need for a co-design approach to distributed quantum computing, which our framework is designed to support.
Practical applications of quantum computing are currently limited by the number of qubits that can be set with reasonable fidelity for each system. Therefore, a distributed quantum computing system with multiple quantum computers coherently connected is highly demanding. To realize the inter-node communication of quantum information, the software interface, Quantum Message Passing Interface (QMPI), leveraging the framework built for classical MPI but taking advantage of quantum teleportation to communicate between different quantum nodes was proposed. In this work, we developed a QMPI implementation with a variety of point-to-point and collective operations in Qiskit and characterize its performance by demonstrating the reference implementations on a few benchmark quantum applications. Moreover, we developed a new approach for optimizing collective communications for the distributed quantum programs with multi-controlled Toffoli gates. This approach outperforms current state-of-the-art in terms of fidelity and the number of remote EPR pairs in both simulations and experiments over IBM’s quantum platforms.
Quantum computers today are noisy and limited in the number of qubits that can be set with reasonable fidelities and gate times for each system. Since the current limit on the number of qubits is difficult to surpass, it is expected that the future of quantum computing will lie in connecting different quantum computers together to form a quantum network, each with its own limitations. Herein lies the field of distributed quantum computing optimized for large-scale communication. One such system that has been designed is the Quantum Message Passing Interface (QMPI). This interface, unlike the classical MPI, takes advantage of quantum teleportation to communicate between different quantum nodes but leverages the framework built for classical MPI. This general interface is essential as we try to connect various quantum computers, as it can be used to develop distributed quantum algorithms across various nodes. In this work, we develop a reference implementation for a QMPI interface in Qiskit and characterize its performance. In our interface, we have implemented point-to-point and optimized collective operations for larger distributed quantum networks. To test our framework, we demonstrate our implementation with applications that can leverage the QMPI framework including Trotterization of the transverse field Ising model and distributive quantum phase estimation. Lastly, we have developed a new technique for decomposing quantum gates across many nodes which leverages multi-controlled Toffolli gates. This technique beats the state of the art for an adder circuit in terms of fidelity and the number of EPR pairs used.