Quick Navigation

Topics

Trapped Ion Quantum Computing

Efficient Circuit Cutting and Scheduling in a Multi-Node Quantum System with Dynamic EPR Pairs

arXiv
Authors: Zefan Du, Wenrui Zhang, Wenqi Wei, Juntao Chen, Tao Han, Zhiding Liang, Ying Mao

Year

2024

Paper ID

56982

Status

Preprint

Abstract Read

~2 min

Abstract Words

172

Citations

N/A

Abstract

Despite advancements, current quantum hardware faces significant challenges, including limited qubit counts and high susceptibility to noise, which hinder the execution of large, complex algorithms. To address these limitations, multi-node quantum systems and quantum circuit cutting techniques partition large circuits into smaller subcircuits that can be executed on individual quantum machines and then reconstructed using classical resources. However, these methods introduce new challenges, such as the large overhead from subcircuit reconstruction and additional noise from entangled EPR pairs, especially in multi-node quantum systems. In this paper, we propose the Efficient Circuit Cutting and Scheduling (EC2S) system, which integrates EPR pairs with circuit cutting to address these issues. EC2S improves system performance by transitioning from logical to physical EPR pairs and further reduces computational overhead by minimizing the number of subcircuits during the reconstruction phase. \sol is implemented using Qiskit and evaluated on both real quantum hardware and various emulators. Compared to the state-of-the-art Qiskit-Addon-Cut, EC2S achieves significant improvements in fidelity, up to 16.7%, and reduces system-wide expenditure by up to 99.5%.

Why This Paper Matters

  • This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
  • It adds a 2024 reference point for readers tracking recent quantum research.
  • Despite advancements, current quantum hardware faces significant challenges, including limited qubit counts and high susceptibility to noise, which hinder the execution of...

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #56982

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.