Generalised Circuit Partitioning for Distributed Quantum Computing

Distributed quantum computing (DQC) is a new paradigm aimed at scaling up quantum computing via the interconnection of smaller quantum processing units (QPUs). Shared entanglement allows teleportation of both states and gates between QPUs. This leads to an attractive horizontal scaling of quantum processing power that comes at the expense of the additional time and noise introduced by entanglement sharing protocols. Consequently, protocols for partitioning quantum circuits should aim to minimise the amount of entanglement-based communication required between distributed QPUs. Existing protocols tend to focus primarily on optimising entanglement costs for gate teleportation or state teleportation to cover operations between QPUs, rather than both at the same time. The most general form of the problem should treat gate and state teleportation on the same footing, allowing minimal cost circuit partitions through a combination of the two. This work introduces a graph-based formulation that allows joint optimisation of gate and state teleportation cost. The formulation permits lowe-bit cost for a variety of circuit types. Using a genetic algorithm, improved performance over state-of-the-art methods is obtained in terms of both average e-bit cost and time scaling.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.10273
Citations
20
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
6.95

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article

Generalised Circuit Partitioning for Distributed Quantum Computing

Kin K. Leung, Kuan‐Cheng Chen, Felix Burt
20 citations
Quantum Computing Algorithms and Architecture
6.95
article

Generalised Circuit Partitioning for Distributed Quantum Computing

Kin K. Leung, Kuan‐Cheng Chen, Felix Burt
article en
20 citations

Abstract

Distributed quantum computing (DQC) is a new paradigm aimed at scaling up quantum computing via the interconnection of smaller quantum processing units (QPUs). Shared entanglement allows teleportation of both states and gates between QPUs. This leads to an attractive horizontal scaling of quantum processing power that comes at the expense of the additional time and noise introduced by entanglement sharing protocols. Consequently, protocols for partitioning quantum circuits should aim to minimise the amount of entanglement-based communication required between distributed QPUs. Existing protocols tend to focus primarily on optimising entanglement costs for gate teleportation or state teleportation to cover operations between QPUs, rather than both at the same time. The most general form of the problem should treat gate and state teleportation on the same footing, allowing minimal cost circuit partitions through a combination of the two. This work introduces a graph-based formulation that allows joint optimisation of gate and state teleportation cost. The formulation permits lowe-bit cost for a variety of circuit types. Using a genetic algorithm, improved performance over state-of-the-art methods is obtained in terms of both average e-bit cost and time scaling.

Imperial College London (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 3%
Quantum Computing Algorithms and Architecture
6.95
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