2023/01/13 by Waldemir Cambiucci, Cambiucci, Waldemir, Regina Melo Silveira +3 · 1 citation
Computer Science · #FOS: Physical sciences #Parallel Computing and Optimization Techniques #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph) #Stochastic Gradient Optimization Techniques
paper · pdf · doi:10.48550/arxiv.2301.05759
openalex publication_date 2023/01/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In the context of NISQ computers - Noise Intermediate Scale Quantum, it is a consensus that the distribution of circuits among processing agents is a viable approach to get greater scalability with small machines. This approach can increase the combined computational power at the cost of dedicating qubits to get the communication between partitions. Then comes the challenge of reducing this cost of communication-based on efficient circuit partitioning strategies. In this context, this work aims to reduce the consumption of communication qubits generated during the physical partitioning of quantum circuits in the distributed quantum computing scenario. We present a new method for partitioning quantum circuits in a hypergraphic representation, using a heuristic partitioning algorithm for this, reducing the number of communication qubits between the partitions. With this approach, we obtained partial results with a more than 50% reduction in the communication cost generated for the bipartite partitioning against a process done randomly on benchmark circuits. The expectation is that future experiments with multiple partitions will continue with equal or better results than previous works, supporting distributed quantum computing with machines in heterogeneous processing and communication scenarios.