<!--HTML-->The control of superconducting qubits, central to quantum computing, demands precise manipulation of fast microwave pulses. FPGAs offer ideal versatility for this task. However, due to FPGA complexity, institutions often opt for costly, pre-made solutions, limiting customization. We therefore presented Qibosoq, an open-source software package designed for radio frequency system on chip (RFSoC) platforms. Qibosoq bridges the RFSoC firmware provided by QICK, a Quantum Instrumentation Control Kit, with Qibo, an open-source quantum computing framework. By using RFSoC boards, it is possible to significantly lower the cost of a qubit-control hardware, while also maintaining high development flexibility. We present the Qibosoq software package, as well as the result of testing it with multiple qubits both as a characterization platform and as an algorithm executor, where we demonstrated the capability of the RFSoC board to accurately perform Quantum Machine Learning applications.
<!--HTML-->The control of superconducting qubits, central to quantum computing, demands precise manipulation of fast microwave pulses. FPGAs offer ideal versatility for this task. However, due to FPGA complexity, institutions often opt for costly, pre-made solutions, limiting customization. We therefore presented Qibosoq, an open-source software package designed for radio frequency system on chip (RFSoC) platforms. Qibosoq bridges the RFSoC firmware provided by QICK, a Quantum Instrumentation Control Kit, with Qibo, an open-source quantum computing framework. By using RFSoC boards, it is possible to significantly lower the cost of a qubit-control hardware, while also maintaining high development flexibility. We present the Qibosoq software package, as well as the result of testing it with multiple qubits both as a characterization platform and as an algorithm executor, where we demonstrated the capability of the RFSoC board to accurately perform Quantum Machine Learning applications.
Abstract We present Qibosoq , an open-source server-side software package designed for radio frequency system on chip (RFSoC) for executing arbitrary pulse sequences and algorithms on self-hosted quantum processing units using only open-source software. Qibosoq connects the RFSoC firmware provided by Qick , a Quantum Instrumentation Control Kit, with Qibo , a quantum computing middleware framework that enables both experimental and gate-based applications. It simplifies the work of experimentalists and developers by managing client-server communication protocols, implementing tests, and validation procedures, thereby reducing the complexity of experimental setups. The client-side integration is achieved with dedicated drivers implemented in Qibolab , the specialized software module of Qibo for quantum hardware control. Therefore, this setup provides a seamless mechanism to deploy circuit-based algorithms on custom self-hosted quantum hardware platforms controlled by RFSoC electronics.
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.
We present FIREQ (FPGA Instrumentation for Readout and Qubit control), an open-source RFSoC-based framework for the control and readout of superconducting qubits. FIREQ combines a modular AXI-compliant firmware architecture with a PYNQ-based software stack designed to support extensible hardware integration, deterministic experiment timing, and low-overhead execution of repeated calibration and characterization workflows. The firmware implements direct RF synthesis and acquisition, trigger-based sequencing, programmable pulse generation, frequency-multiplexed readout, and memory-efficient acquisition and waveform buffering. The software adopts a client-server architecture with streamed data transfer and dependency-aware configuration updates to reduce host-device and reconfiguration overhead during parameter sweeps. On an AMD Zynq UltraScale+ RFSoC ZCU216, FIREQ generates RF pulses up to 9.3 GHz with a pulse-duration resolution of 107 ps and an event-timing resolution of 1.7 ns. FPGA resource utilization is compared with representative open-source RFSoC control frameworks, showing a low BRAM footprint while retaining full-rate I/Q generation and acquisition. The RF output is characterized in terms of phase noise, noise spectral density, and inter-channel timing skew. End-to-end operation is validated on a superconducting qubit through resonator spectroscopy, Rabi, Ramsey, and relaxation measurements, yielding T1 = 6.94 us and T2* = 13.50 us. FIREQ can therefore be used both as a qubit-control platform and as an experimental environment for evaluating alternative control and readout IP architectures.
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.
Semiconductor triple-quantum dots (TQDs) are a promising platform for scalable quantum information processing, but the community has so far lacked access to affordable and flexible high-speed control electronics. SpinQICK, an open-source spin qubit-control package built on the Xilinx Radio Frequency System-on-Chip (RFSoC), directly addresses this gap by leveraging the high sampling-rate signal generation and advanced digital signal processing (DSP) capabilities of the Quantum Instrumentation Control Kit (QICK) to enable precise time-domain voltage control and readout of semiconductor spin qubits. In this paper, we use spinQICK to demonstrate coherent control, state preparation, and readout of a fully connected triangular exchange-only device. We also introduce and experimentally verify a novel dynamical decoupling (DD) sequence enabled by the triangular TQD and leverage its unique decoupling properties to characterize electrical noise. These results establish spinQICK as a low-cost, flexible platform for semiconductor spin qubit control and provide a pathway for hardware optimization through qubit-level noise diagnostics.
Researchers manipulate and measure quantum processing units via the classical electronics control system. We developed an open-source FPGA-based quantum bit control system called QubiC for superconducting qubits. After years of qubit calibration and testing experience on QubiC 1.0, we recognized the need for mid-circuit measurement and feed-forward capabilities to implement advanced quantum algorithms, and upgraded the system to QubiC 2.0 on an AMD ZCU216 RFSoC evaluation board with all these enriched features. The system uses portable FPGA gateware with a simplified processor to handle commands on-the-fly. For design simplicity and straightforward scaling, we adopted a multi-core distributed architecture, assigning one processor core per qubit. The pulses combine the unique pulse envelope and carrier information specified in a command. Each pulse envelope is pre-stored in the FPGA's block RAMs, ensuring speed and reusability throughout the quantum circuit, while pulse parameters including amplitude, phase, and frequency can be updated from pulse to pulse. The software stack is developed in Python, running on both the FPGA's ARM core and a host computer via XML-RPC. Quantum circuits can be described in a high-level language supporting both pulse-level and native-gate-level programming with high-level control flow constructs, and are compiled into binary commands loaded into the FPGA. With QubiC 2.0, we achieved multi-FPGA synchronization and low-latency data communication, and demonstrated feed-forward experiments on conditional circuits. The system also serves as a platform for artificial intelligence and machine learning driven quantum control, such as FPGA-based real-time quantum state discrimination. The enhanced QubiC system provides researchers with powerful tools to explore and implement advanced quantum algorithms and applications.