ECDQC: Efficient Compilation for Distributed Quantum Computing with Linear Layout

TL;DR

This paper proposes an efficient compilation method for distributed quantum computing (DQC) using the Linear Nearest Neighbor (LNN) architecture that decreases compilation time, gate count, and circuit depth, improving scalability and robustness for large-scale quantum computations.

Abstract

In this paper, we propose an efficient compilation method for distributed quantum computing (DQC) using the Linear Nearest Neighbor (LNN) architecture. By exploiting the LNN topology's symmetry, we optimize quantum circuit compilation for High Local Connectivity, Sparse Full Connectivity (HLC-SFC) algorithms like Quantum Approximate Optimization Algorithm (QAOA) and Quantum Fourier Transform (QFT). We also utilize dangling qubits to minimize non-local interactions and reduce SWAP gates. Our approach significantly decreases compilation time, gate count, and circuit depth, improving scalability and robustness for large-scale quantum computations.

Figures (4)

• Figure 1: Proposed chip-to-chip distributed quantum system by modifying the Heavy-hex topology to LNN topology and taking the dangling qubits as teleportation pair.
• Figure 2: Overview of the Chip-to-Chip DQC Compilation Process. The process begins with a heavy-hex architecture and compiles HLC-SFC quantum algorithms, such as QAOA and QFT, using an LNN compiler. The compiler leverages symmetry to optimize the structure, managing dangling qubits and employing a qubit movement strategy. This leads to an efficient chip-to-chip DQC system with minimized non-local interactions and enhanced scalability.
• Figure 3: Gate Count Comparison between Random and Dangling Qubit Placement for QFT and QAOA Circuits.
• Figure 4: Total SWAP Gates and Cross-Group SWAP Gates Comparison between Random and Dangling Qubit Placement.