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HLS4ML Integration with QICK

Mohamud Ali

Published Aug 15, 2024• 0 citations
Publisher

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.

DOI
10.2172/2432410

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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.
We present an end-to-end workflow for superconducting qubit readout that embeds co-designed Neural Networks (NNs) into the Quantum Instrumentation Control Kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx RFSoC FPGAs, we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes thehls4mlpackage and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python APIs. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA look-up table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.
This thesis presents the development of a superconducting qubit control and readout system based on FPGA technology, with a focus on the design of a pulse sequencer and the integration of frequency-multiplexed control. The system leverages the Quantum Instrumentation Control Kit (QICK), an open-source Xilinx RFSoC-based platform capable of direct digital synthesis and acquisition of microwave signals up to 10 GHz. The QICK firmware was extended to support the simultaneous generation and readout of multiple frequency-multiplexed tones, enabling the control and measurement of several qubits coupled to a shared feedline. This approach optimizes the number of controllable qubits relative to the available ADC and DAC resources on the RFSoC 4x2 board. Furthermore, this work includes the development of Qubase, a Python-based pulse sequencer that allows users to easily define and execute complex sequences of control and measurement pulses through the QICK Python interface. The resulting architecture is both flexible and scalable, providing a foundation for efficient multi-qubit experiments and enabling advanced techniques such as quantum error correction and real-time feedback.
The QICK (Quantum Instrumentation Control Kit), first introduced in 2022, is a standalone open source control system for quantum information science. Since then, QICK has been migrated to new hardware platforms, expanded its functionality for applications with different types of qubits (superconducting, atomic, ion-trapped, and spin defects), as well as quantum sensors, and quantum networks. QICK is a highly optimized control kit, with a library of functions that can be used for more than one application. In particular, the software and firmware are customized to minimize latency and maximize control performance and throughput. In this white paper, we describe hardware details and performance of the QICK Box. The QICK Box features up to 16 outputs, up to 8 inputs, and 8 20-bit DC biases. Modular output and input daughtercards give the choice of signal chains optimized for fast DC-coupled signals or RF signals up to 10 GHz. Power levels, step attenuation, and bandpass filtering are controlled by software. We demonstrate the system's performance through single-shot readout measurements of a six-transmon device at the Quantum Underground Instrumentation Experimental Testbed (QUIET) at Fermilab, achieving (91.7 +/- 0.4)% readout fidelity limited by T1 decay during the readout. The single shot readout signal-to-noise ratio (SNR) is 4.4 +/- 0.1 without a quantum amplifier, confirming that the QICK Box is suitable for high-fidelity quantum control and measurement applications. Advances in firmware and software will be described in a separate paper.
We introduce a Xilinx RF System-on-Chip (RFSoC)-based qubit controller (called the Quantum Instrumentation Control Kit, or QICK for short), which supports the direct synthesis of control pulses with carrier frequencies of up to 6 GHz. The QICK can control multiple qubits or other quantum devices. The QICK consists of a digital board hosting an RFSoC field-programmable gate array, custom firmware, and software and an optional companion custom-designed analog front-end board. We characterize the analog performance of the system as well as its digital latency, important for quantum error correction and feedback protocols. We benchmark the controller by performing standard characterizations of a transmon qubit. We achieve an average gate fidelity of Favg=99.93%. All of the schematics, firmware, and software are open-source.
The Quantum Instrumentation Control Kit (QICK) is a standalone open-source qubit controller that was first introduced in 2022. In this follow-up work, we present recent upgrades to the QICK and the experimental use cases they uniquely enabled for superconducting qubit systems. These include multiplexed signal generation and readout, mixer-free readout, predistorted fast flux pulses, and phase-coherent pulses for parametric operations, including high-fidelity parametric entangling gates. We explain in detail how the QICK was used to enable these experiments. Published by the American Physical Society 2024