Distributed Quantum Error Mitigation: Global and Local ZNE encodings

TL;DR

This paper explores how Zero Noise Extrapolation (ZNE) can be adapted for distributed quantum computing, comparing global and local approaches, and demonstrating that global ZNE offers better scalability and error reduction.

Contribution

It introduces a comparative analysis of global versus local ZNE in distributed quantum architectures, revealing the advantages of global optimization for scalability and error mitigation.

Findings

Global ZNE achieves up to 48% error reduction across six QPUs.

Increasing QPU count can improve mitigation despite added communication noise.

Counterintuitively, more QPUs can enhance error mitigation effectiveness.

Abstract

Errors are the primary bottleneck preventing practical quantum computing. This challenge is exacerbated in the distributed quantum computing regime, where quantum networks introduce additional communication-induced noise. While error mitigation techniques such as Zero Noise Extrapolation (ZNE) have proven effective for standalone quantum processors, their behavior in distributed architectures is not yet well understood. We investigate ZNE in this setting by comparing Global optimization (ZNE is applied prior to circuit partitioning), against Local optimization (ZNE is applied independently to each sub-circuit). Partitioning is performed on a monolithic circuit, which is then transformed into a distributed implementation by inserting noisy teleportation-based communication primitives between sub-circuits. We evaluate both approaches across varying numbers of quantum processing units (QPUs) and under heterogeneous local and network noise conditions. Our results demonstrate that Global ZNE exhibits superior scalability, achieving error reductions of up to $48\%$ across six QPUs. Moreover, we observe counterintuitive noise behavior, where increasing the number of QPUs improves mitigation effectiveness despite higher communication overhead. These findings highlight fundamental trade-offs in distributed quantum error mitigation and raise new questions regarding the interplay between circuit structure, partitioning strategies, and network noise.