Fuzzy-Based Balanced Partitioning Under Capacity and Size-Tolerance Constraints in Distributed Quantum Circuits

It is important for the design of a distributed quantum circuit (DQC) to minimize communication cost in k -way balanced partitioning. In this article, given an original (QC), partitioning number , maximum capacity δ inside each partition, and size tolerance γ between two partitions, new (δ, γ)-balanced problem can be formulated as under constraint size-tolerance γ, fuzzy-based algorithm proposed DQC design. First, edge-weighted connection graph constructed from gates QC. Furthermore, based on estimation probabilistic strength vertices xmlns:xlink="http://www.w3.org/1999/xlink">initial k-way result graph, fuzzy memberships clusters generated -means clustering. Finally, all assigned onto partitions Compared with Daei's recursive Kernighan–Lin-based four-way partitioning, experimental results show that three constraints = 1, 2, 3 use 58.3%, 61.3%, 64.5% CPU time reduce 16.1%, 21.2%, 24.6% eight tested circuits average, respectively. modified Dadkhah's three-way, four-way, or five-way 35.0% 11.1%