Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 16 tok/s
GPT-5 High 18 tok/s Pro
GPT-4o 104 tok/s
GPT OSS 120B 459 tok/s Pro
Kimi K2 216 tok/s Pro
2000 character limit reached

Exploring operation parallelism vs. ion movement in ion-trapped QCCD architectures (2502.04181v1)

Published 6 Feb 2025 in quant-ph

Abstract: Ion-trapped Quantum Charge-Coupled Device (QCCD) architectures have emerged as a promising alternative to scale single-trap devices by interconnecting multiple traps through ion shuttling, enabling the execution of parallel operations across different traps. While this parallelism enhances computational throughput, it introduces additional operations, raising the following question: do the benefits of parallelism outweigh the potential loss of fidelity due to increased ion movements? This paper answers this question by exploring the trade-off between the parallelism of operations and fidelity loss due to movement overhead, comparing sequential execution in single-trap devices with parallel execution in QCCD architectures. We first analyze the fidelity impact of both methods, establishing the optimal number of ion movements for the worst-case scenario. Next, we evaluate several quantum algorithms on QCCD architectures by exploiting parallelism through ion distribution across multiple traps. This analysis identifies the algorithms that benefit the most from parallel executions, explores the underlying reasons, and determines the optimal balance between movement overhead and fidelity loss for each algorithm.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube