Modular Software for Real-Time Quantum Control Systems
Leon Riesebos, Brad Bondurant, Jacob Whitlow, Junki Kim, Mark Kuzyk,, Tianyi Chen, Samuel Phiri, Ye Wang, Chao Fang, Andrew Van Horn, Jungsang Kim,, Kenneth R. Brown

TL;DR
This paper presents a modular design for real-time quantum control software that enhances flexibility and portability, significantly reducing execution overhead and enabling shared code across different quantum systems.
Contribution
The paper introduces a systematic modular architecture for quantum control software, improving performance and portability compared to existing system-specific solutions.
Findings
Reduced kernel execution time overhead by 63.3% on average
Shared between 49.8% and 91.0% of code statements across systems
Successfully demonstrated portability with randomized benchmarking on two ion-trap systems
Abstract
Real-time control software and hardware is essential for operating quantum computers. In particular, the software plays a crucial role in bridging the gap between quantum programs and the quantum system. Unfortunately, current control software is often optimized for a specific system at the cost of flexibility and portability. We propose a systematic design strategy for modular real-time quantum control software and demonstrate that modular control software can reduce the execution time overhead of kernels by 63.3% on average while not increasing the binary size. Our analysis shows that modular control software for two distinctly different systems can share between 49.8% and 91.0% of covered code statements. To demonstrate the modularity and portability of our software architecture, we run a portable randomized benchmarking experiment on two different ion-trap quantum systems.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Parallel Computing and Optimization Techniques
