A Modular, Topology-Aware Software Stack for Entanglement-Based Distributed Quantum Computing
Abstract
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.
Related
- Distributed variational quantum computing with deterministic entanglement tuning
- Entanglement-Capability-Aware Finite-Bond Circuit Cutting for Distributed Quantum Computing
- SeQUeNCe.DQC: Full-stack Simulation of Distributed Quantum Computing
- Entanglement as Topology: Hopf Linking as the Geometric Origin of Quantum Correlation
- Transversal Fanout for Fault Tolerant Distributed Quantum Computing: Analysis and Application
BibTeX
@misc{andreesen2026modular,
title = {{A Modular, Topology-Aware Software Stack for Entanglement-Based Distributed Quantum Computing}},
author = {Luke Andreesen and Shobhit Gupta and Sean Sullivan and Manish Kumar Singh},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.15728},
eprint = {2609.15728},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.15728},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Modular, Topology-Aware Software Stack for Entanglement-Based Distributed Quantum Computing
AU - Luke Andreesen
AU - Shobhit Gupta
AU - Sean Sullivan
AU - Manish Kumar Singh
PY - 2026
DA - 2026/09/14
PB - arXiv
DO - 10.48550/arxiv.2609.15728
UR - https://arxiv.org/abs/2609.15728
AB - 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.
ER -