Quantum computing is poised to transform fields such as cryptography, materials science, pharmaceutical research, and large-scale optimization. Unlike classical computers that process information using bits, quantum computers operate using qubits, which can represent multiple states simultaneously. However, controlling and measuring qubits requires extremely precise electronic systems capable of generating, processing, and analyzing high-frequency signals with deterministic timing and minimal latency.
At the core of this infrastructure lies the Quantum Control Unit (QCU), a specialized hardware platform responsible for generating microwave pulses used to manipulate qubits and capturing the resulting cubit readout signals. As quantum systems grow in complexity and qubit counts increase, traditional control architectures built using multiple discrete instruments are becoming increasingly difficult to scale. This is where RFSoC-based System on Modules (SoMs) offer a compelling alternative by integrating high-speed data converters, programmable logic, and embedded processing capabilities into a single compact platform.
The Role of Classical Control Electronics in Quantum Systems
Although quantum processors perform the actual quantum computations, they rely heavily on classical electronics to generate control signals and interpret measurement results. In superconducting quantum computing architectures, qubits are manipulated using microwave-frequency pulses that must be precisely generated and timed.
Traditionally, these control functions are implemented using multiple laboratory instruments connected to form the control chain. A typical setup may include:
- Arbitrary waveform generators (AWGs) for pulse generation
- Microwave signal generators
- Mixers and up/down converters
- High-speed digitizers for measurement
- Synchronization modules and timing systems
While this approach works for early-stage research experiments, it becomes difficult to scale. The resulting systems often consist of large racks of equipment with complex cabling, higher latency, and significant cost. Integrated RFSoC platforms provide a more compact and scalable alternative.
RFSoC Technology for Quantum Control
RFSoC devices integrate high-speed RF data converters, programmable FPGA fabric, and embedded processors into a single chip. This architecture enables direct generation and acquisition of RF signals without relying on multiple external instruments.
In a quantum control system, the RFSoC acts as a flexible control and readout engine. It generates microwave pulses required for qubit manipulation while simultaneously digitizing measurement signals from the quantum processor.
Typical RFSoC capabilities that make them suitable for quantum control include:
- Multi-gigahertz RF DACs for microwave pulse generation
- High-speed RF ADCs for qubit readout
- Integrated FPGA fabric for real-time signal processing
- Embedded processors for system control and experiment management
- Deterministic timing and synchronization
Because the ADCs, DACs, and FPGA processing engines reside within the same device, RFSoC platforms enable deterministic, FPGA-level signal processing with ultra-low latency and real-time closed-loop feedback, which are essential for precise qubit control and measurement in quantum systems.
It is important to note that RFSoC devices do not perform quantum computation themselves. Instead, they serve as the classical control interface between the quantum processor and external computing systems.
Typical RFSoC-Based Quantum Control Architecture
A typical RFSoC-based quantum control system architecture consists of a host control platform, an RFSoC-based Quantum Control Unit, and the quantum processor located inside a cryogenic environment.
Host Control System:
Researchers use a quantum software framework or quantum kit on a host PC to define quantum algorithms and pulse sequences using high-level languages such as Python.
RFSoC-Based Quantum Control Unit:
The generated control data is transferred to the RFSoC platform, where real-time waveform generation, sequencing, synchronization, and readout processing are executed.
Cryostat & Qubits:
The RF signals generated by the RFSoC drive the qubits inside the cryostat, while the reflected or emitted signals are captured and analyzed to determine qubit states.
Key Functional Blocks
The RF signals generated by the RFSoC drive the qubits inside the cryostat, while the reflected or emitted signals are captured and analyzed to determine qubit states.
Master Sequencer
The master sequencer executes time-critical control logic derived from host-side Python code. It ensures deterministic timing across multiple channels, enabling synchronized pulse generation, qubit addressing, and experiment repeatability.
Pulse Generation & Control
Using the integrated RF DACs, the RFSoC generates precisely shaped microwave pulses required for qubit manipulation. Pulse parameters such as amplitude, phase, frequency, and duration are controlled in real time, enabling single-qubit and multi-qubit gate operations.
Readout Signal Processing
Signals returned from the qubits are digitized using the RF ADCs and processed through FPGA-based DSP pipelines. This includes filtering, demodulation, and integration to extract qubit state information with minimal latency.
ARM-Based Control & Validation
The embedded ARM processors handle experiment coordination, parameter updates, and validation of qubit states. This allows tight coupling between real-time hardware control and higher-level software orchestration.
Key Advantages of RFSoC-Based Quantum Control Systems
RFSoC-based architectures provide several advantages compared to traditional instrument-based quantum control setups.
- System Integration: RFSoC devices consolidate several discrete instruments into a single platform, reducing hardware complexity and system size.
- Low Latency Processing: Because signal generation, acquisition, and processing occur within the same device, RFSoC systems can achieve extremely low processing latency.
- Closed-Loop Feedback: RFSoC platforms allow measurement results to influence control pulses in real time. This enables conditional operations and adaptive experiments that are essential for advanced quantum algorithms.
- Improved Synchronization: With tightly integrated clocking and processing resources, RFSoC-based systems offer improved synchronization across multiple channels.
- Scalability: As quantum processors scale to larger numbers of qubits, RFSoC platforms provide a flexible and scalable control architecture.
Zynq UltraScale+ RFSoC System on Modules for Quantum Control Platforms
While RFSoC FPGA devices provide powerful capabilities, integrating them into a complete hardware system requires significant engineering effort. Designers must address several challenges, including:
- High-speed memory integration
- Power management design
- Clocking architecture
- High-speed I/O connectivity
- Thermal management
Zynq UltraScale+ RFSoC System on Modules (SoMs) simplify this process by integrating the RFSoC FPGA device together with essential supporting components into a compact and ready-to-use module. An RFSoC SoM typically includes RFSoC FPGA, high-speed DDR memory, power management circuitry, clocking and timing infrastructure, high-speed interfaces such as PCIe and Ethernet. By using a pre-validated module platform, developers can significantly reduce hardware design complexity and accelerate system development.
Software Ecosystem for RFSoC-Based Quantum Control
Beyond hardware capabilities, the software ecosystem also plays an important role in enabling RFSoC-based quantum control systems.
Several frameworks have emerged that allow researchers to build quantum control experiments on top of RFSoC platforms. These frameworks typically provide:
- Pulse sequence programming environments
- Experiment orchestration tools
- Calibration and measurement routines
- Integration with high-level programming languages such as Python
Examples of such ecosystems include open quantum control frameworks that allow researchers to define microwave pulse sequences and measurement workflows while the RFSoC hardware executes time-critical operations in FPGA logic.
This combination of flexible software tools and high-performance hardware makes RFSoC platforms particularly attractive for research and experimental quantum computing systems.
Frameworks such as Quantum Instrumentation Control Kit (QICK) further extend the capabilities of RFSoC-based platforms by enabling real-time pulse sequencing, qubit control, and low-latency feedback directly within the FPGA fabric. This allows researchers to implement advanced quantum experiments with deterministic timing and reduced system complexity.
Learn more about real-time quantum control using QICK on iWave RFSoC platforms in our detailed article.
In addition, Python-based frameworks such as PYNQ simplify RF system design by allowing developers to build and control signal processing pipelines using high-level programming. This significantly reduces development effort and accelerates experimentation on RFSoC platforms.
Explore how PYNQ enables Python-based RF system design on iWave RFSoC System on Modules.
iWave Global’s Zynq UltraScale+ RFSoC System on Modules provide a powerful and flexible foundation for next-generation Quantum Control Units. By combining high-speed RF converters, FPGA-based real-time processing, and embedded software control in a single platform, RFSoC enables researchers and system designers to accelerate quantum experimentation while maintaining precision, scalability, and deterministic performance.
For detailed information, please reach us at mktg@iwave-global.com
