HLS4ML Integration with QICK

The QICK (Quantum Instrumentation Control Kit) integration aims to enhance the readout of superconducting qubits by leveraging machine learning (ML) techniques. These techniques offer high accuracy, increased speed, and better state preservation for qubit readouts. The integration process employs neural network algorithms to optimize system performance and achieve high accuracy rates. The QICK board uses an FPGA, allowing for efficient real-time processing and high-performance execution of machine learning algorithms.

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Published
2024-08-15
DOI
https://doi.org/10.2172/2432410
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

HLS4ML Integration with QICK

Mohamud Ali
Parallel Computing and Optimization Techniques
article

HLS4ML Integration with QICK

Mohamud Ali
article en

Abstract

The QICK (Quantum Instrumentation Control Kit) integration aims to enhance the readout of superconducting qubits by leveraging machine learning (ML) techniques. These techniques offer high accuracy, increased speed, and better state preservation for qubit readouts. The integration process employs neural network algorithms to optimize system performance and achieve high accuracy rates. The QICK board uses an FPGA, allowing for efficient real-time processing and high-performance execution of machine learning algorithms.

Northwestern University (PH)
Openalex Percentile: Top 87%
Parallel Computing and Optimization Techniques
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HLS4ML Integration with QICK — Mohamud Ali · (2024) | TGRS Research Map | TGRS