QuPort: Topology-, Port-, and Congestion-Aware Compilation for Modular Multi-QPU Quantum Systems

TL;DR

QuPort is a novel compilation framework for modular quantum systems that optimizes resource usage by considering device connectivity, communication, and congestion at multiple levels.

Contribution

It introduces a three-level model and a partitioning method, TPCCAP, to improve quantum circuit compilation for modular multi-QPU systems.

Findings

Optimizes quantum circuit mapping considering cross-QPU traffic and congestion.

Includes advanced partitioning, clustering, and routing techniques.

Enhances compilation efficiency for modular quantum architectures.

Abstract

Modular quantum processors require a compiler to reason about two resources at the same time: local device connectivity and communication across QPUs. A mapping that is acceptable on a single coupling graph may be unsuitable for a modular machine if it creates excessive cross-QPU traffic, concentrates that traffic on a small number of interconnect links, or assigns many boundary qubits to a QPU with few communication ports. This paper presents QuPort, a Python and Qiskit-based compilation framework that studies this setting through an explicit three-level model: a weighted logical interaction graph, a directed physical coupling map, and an undirected QPU-level interconnect graph. The main partitioning method, TPCCAP, optimizes the implemented objective formed by weighted cut distance, communication-port overflow, and routed link-load congestion. The framework also includes heavy-edge clustering, balanced greedy partitioning, simulated-annealing refinement, communication-port-aware layout, extraction of remote two-qubit operations, local-only routing of per-QPU circuits, and topology-aware schedule estimation. The model is a compiler-level abstraction. It does not claim a calibrated hardware runtime or an implementation of a physical remote-gate protocol.