Updated QubiC: Improved Scalability, Performance, and QPU Support

Quantum computers rely on classical computers for control and readout. In the NISQ era, quantum computers are increasing in scale and spanning a broader range of QPU architectures and experiment/algorithm design, requiring cost-effective and flexible control systems. QubiC, the open-source control system developed at Lawrence Berkeley National Laboratory, was designed to support quantum computers in this evolution. After a few developmental years, QubiC 1.0 demonstrated its control and measurement capabilities on a superconducting quantum processing unit (QPU). With growing requirements from the QPU, QubiC 2.0 was developed on the latest RFSoC platform with mid-circuit measurement and feed-forward features, along with a new AC analog front-end. The latest updates focus on performance — with hardware-efficient randomized compiling (RC) and hardware-assisted parameterized circuit execution —, scalability — with software capable of synchronizing multiple boards —, and supporting a broader range of superconducting QPUs with an AC and DC-coupled analog front-end.

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Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.10430
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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article en

Abstract

Quantum computers rely on classical computers for control and readout. In the NISQ era, quantum computers are increasing in scale and spanning a broader range of QPU architectures and experiment/algorithm design, requiring cost-effective and flexible control systems. QubiC, the open-source control system developed at Lawrence Berkeley National Laboratory, was designed to support quantum computers in this evolution. After a few developmental years, QubiC 1.0 demonstrated its control and measurement capabilities on a superconducting quantum processing unit (QPU). With growing requirements from the QPU, QubiC 2.0 was developed on the latest RFSoC platform with mid-circuit measurement and feed-forward features, along with a new AC analog front-end. The latest updates focus on performance — with hardware-efficient randomized compiling (RC) and hardware-assisted parameterized circuit execution —, scalability — with software capable of synchronizing multiple boards —, and supporting a broader range of superconducting QPUs with an AC and DC-coupled analog front-end.

Lawrence Berkeley National Laboratory (US)
Laboratory Directed Research and Development, Lawrence Berkeley National Laboratory
Affordable and clean energy
Openalex Percentile: Top 77%
Quantum Computing Algorithms and Architecture
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