Distributed Quantum Computing with QMPI

Häner, Thomas; Steiger, Damian S.; Hoefler, Torsten; Troyer, Matthias

doi:10.48550/arxiv.2105.01109

Cited by 2 publications

(2 citation statements)

References 48 publications

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“…Finally, to actually deploy such a distributed QAOA system, networked control system for distributed quantum devices are necessary. Proposals addressing such control systems can be found in [44], [45].…”

Section: Discussionmentioning

confidence: 99%

A Hybrid Grasshopper Optimization Algorithm With Invasive Weed for Global Optimization

Yue

2020

IEEE Access

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The grasshopper optimization algorithm (GOA) is a promising metaheuristic algorithm for optimization. In the current study, a hybrid grasshopper optimization algorithm with invasive weed optimization (IWGOA) is proposed. The invasive weed optimization (IWO) and random walk strategy are helpful for improving the search precision and accelerating the convergence rate. In addition, the exploration and exploitation capability of the IWGOA algorithm are further enhanced by the grouping strategy. The IWGOA algorithm is compared with some typical and latest optimization algorithms including genetic algorithm (GA), moth-flame optimization algorithm (MFO), particle swarm optimization and gravitational search algorithm (PSOGSA), ant lion optimizer (ALO), conventional GOA algorithm, chaotic GOA algorithm (CGOA) and opposition-based learning GOA algorithm (OBLGOA) on 23 benchmark functions and 30 CEC 2014 benchmark functions. The results show that the IWGOA algorithm is able to provide better outcomes than the other algorithms on the majority of the benchmark functions. Additionally, the IWGOA algorithm is applied to multi-level image segmentation, and obtains promising results. All of these findings demonstrate the superiority of the IWGOA algorithm. INDEX TERMS Grasshopper optimization algorithm, invasive weed optimization, grouping strategy, random walk strategy, global optimization.

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Section: Discussionmentioning

confidence: 99%

A Hybrid Grasshopper Optimization Algorithm With Invasive Weed for Global Optimization

Yue

2020

IEEE Access

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“…This research will eventually enable application-level compilers that optimize use distributed quantum software according to cost functions based on link use [56]. For example, in the area of protocols that route network traffic, the work in [57] presents Quantum MPI, inspired by classical messaging passing interface (MPI), to standardize qubit messaging and entanglement distribution between nodes for distributed and parallel quantum computing. Much has yet to be defined in the space of quantum network protocols due to ambiguity in how quantum networks will be physically realized.…”

Section: Algorithms and Applicationsmentioning

confidence: 99%

Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation

LaRacuente¹,

Smith²,

Imany³

et al. 2022

Preprint

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A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributing a quantum computer across nearby small qubit arrays, known as chiplets, could solve many problems associated with size. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. We model and evaluate the chiplet architecture in a way that bridges the physical and network layers. We find concrete evidence that distributed quantum computing may accelerate the path toward useful and ultimately scalable quantum computers. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.

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Distributed Quantum Computing with QMPI

Cited by 2 publications

References 48 publications

A Hybrid Grasshopper Optimization Algorithm With Invasive Weed for Global Optimization

A Hybrid Grasshopper Optimization Algorithm With Invasive Weed for Global Optimization

Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation

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