Benchmarking Distributed Quantum Computing Emulators Enables Scalable Phase Recovery Via Fourier Transform

The pursuit of scalable quantum computing increasingly focuses on distributed architectures, where interconnected nodes collaborate to solve complex problems, and researchers Guillermo Díaz-Camacho, Iago F. Llovo, and F. Javier Cardama, from the Galicia Supercomputing Center and the Centro Singular de Investigaciación en Tecnoloxías Intelixentes, have developed a new benchmarking framework to evaluate the performance of emulators designed for these systems. Recognising the crucial role of emulation in exploring distributed quantum computing (DQC) feasibility, the team, alongside collaborators Irais Bautista, Daniel Faílde, and Mariamo Mussa Juane, assessed several platforms using a distributed implementation of the inverse Fourier Transform as a representative test case. Their work reveals significant variations in emulator capabilities, particularly in supporting essential protocols like teleportation and modelling realistic network conditions, and highlights the trade-offs between architectural fidelity and simulation scalability. This comprehensive analysis provides valuable insights for future emulator development and the validation of distributed quantum algorithms, offering a foundation for advancing the field of scalable quantum computation.

Scalable quantum computing demands architectural solutions beyond monolithic processors. Distributed quantum computing (DQC) addresses this challenge by interconnecting smaller quantum processors through quantum communication protocols, enabling collaborative computation. While several experimental and theoretical proposals for DQC exist, emulator platforms are essential tools for exploring their feasibility under realistic conditions.

Distributed Quantum Computing Emulator Benchmarking

Scientists are systematically evaluating software tools that simulate distributed quantum computing systems, a crucial step towards building practical quantum computers. As constructing actual distributed quantum hardware presents significant challenges, simulation is essential for developing algorithms, designing systems, and analysing performance. This research focuses specifically on emulators capable of modelling distributed quantum computers, systems where quantum processing units (QPUs) are physically separated and communicate over a network, introducing complexities not present in single-QPU simulations. The experiments utilize an all-to-all connectivity pattern, simplifying analysis while providing a baseline for more complex network topologies. The authors plan to release the benchmarking suite publicly on GitHub, promoting reproducibility and community contribution.

Distributed Quantum Computing Emulator Benchmarking Achieved

Scientists are addressing the challenge of scaling quantum computers by investigating distributed quantum computing (DQC), an approach that connects smaller quantum processors to function as a unified system. This work presents a benchmarking framework to evaluate DQC emulators, essential tools for exploring the feasibility of DQC protocols before scalable hardware is available. This implementation allows for rigorous testing of protocols requiring teleportation, entanglement management, and inter-node gate execution.

The research categorized existing emulators based on their architecture and target functionality, identifying a gap in tools that simultaneously offer faithful emulation of distributed quantum computing and a distributed-memory classical simulation backend. Four representative emulators, Qiskit Aer, SquidASM, Interlin-q, and SQUANCH, were selected for benchmarking, differing significantly in their support for discrete-event simulation, quantum networking, noise modelling, and parallel execution. The team’s analysis highlights the trade-offs between architectural fidelity and simulation scalability, providing a foundation for future emulator development and validation of distributed protocols.

Emulator Benchmarking For Distributed Quantum Computing

This work presents a benchmarking framework for evaluating emulators designed for distributed quantum computing, a promising approach to overcome the limitations of scaling single quantum processors. By partitioning this calculation across multiple simulated nodes, the team analysed execution time, memory usage, and computational fidelity, comparing results against a monolithic, non-distributed baseline. The investigation revealed significant differences between available emulators in their support for essential features like teleportation protocols, discrete-event simulation, and realistic noise modelling.

Through rigorous testing of Qiskit Aer, SquidASM, Interlin-q, and SQUANCH, the team highlighted the trade-offs between architectural fidelity, how accurately an emulator replicates physical quantum behaviour, and simulation scalability, the ability to model increasingly complex systems. This comparative analysis provides valuable insight for future emulator development and validation of distributed quantum protocols. Future work could extend the framework to incorporate additional algorithms and a wider range of emulators, further refining the understanding of distributed quantum computing capabilities. The team also notes that accurately modelling all physical effects remains a significant challenge for all emulators, and ongoing improvements in this area are crucial for reliable simulations.