Superconducting qubits represent a highly promising and scalable quantum hardware technology. The design of these qubits follows a typical microwave circuit design process, where the circuit encompasses multiple resonance frequencies associated with both the resonators and the qubits. Chip design involves the meticulous engineering of resonators and qubits to align the circuit’s various frequencies with predefined values. Additionally, adjusting the coupling between resonators and qubits is essential to meet specific quantum parameters. As the demand for scaling to thousands of qubits grows, it becomes imperative to incorporate systematic engineering and design automation. In this article, we will explore the present requirements for electronic design automation (EDA) that shall enable the design of future superconducting quantum computers.
Superconducting qubits represent a highly promising and scalable quantum hardware technology. The design of these qubits follows a typical microwave circuit design process, where the circuit encompasses multiple resonance frequencies associated with both the resonators and the qubits. Chip design involves the meticulous engineering of resonators and qubits to align the circuit’s various frequencies with predefined values. Additionally, adjusting the coupling between resonators and qubits is essential to meet specific quantum parameters. As the demand for scaling to thousands of qubits grows, it becomes imperative to incorporate systematic engineering and design automation. In this article, we will explore the present requirements for electronic design automation (EDA) that shall enable the design of future superconducting quantum computers.
Electronic Design Automation (EDA) plays a crucial role in classical chip design and significantly influences the development of quantum chip design. However, traditional EDA tools cannot be directly applied to quantum chip design due to vast differences compared to the classical realm. Several EDA products tailored for quantum chip design currently exist, yet they only cover partial stages of the quantum chip design process instead of offering a fully comprehensive solution. Additionally, they often encounter issues such as limited automation, steep learning curves, challenges in integrating with actual fabrication processes, and difficulties in expanding functionality. To address these issues, we developed a full-stack EDA tool specifically for quantum chip design, called EDA-Q. The design workflow incorporates functionalities present in existing quantum EDA tools while supplementing critical design stages such as device mapping and fabrication process mapping, which users expect. EDA-Q utilizes a unique architecture to achieve exceptional scalability and flexibility. The integrated design mode guarantees algorithm compatibility with different chip components, while employing a specialized interactive processing mode to offer users a straightforward and adaptable command interface. Application examples demonstrate that EDA-Q significantly reduces chip design cycles, enhances automation levels, and decreases the time required for manual intervention. Multiple rounds of testing on the designed chip have validated the effectiveness of EDA-Q in practical applications.
The superconducting qubit quantum computer is one of the most promising quantum computing architectures for large-scale integration due to its maturity and close proximity to the well-established semiconductor manufacturing infrastructure. From an education perspective, it also bridges classical microwave electronics and quantum electrodynamics. In this paper, we will review the basics of quantum computers, superconductivity, and Josephson junctions. We then introduce important technologies and concepts related to DiVincenzo's criteria, which are the necessary conditions for the superconducting qubits to work as a useful quantum computer. Firstly, we will discuss various types of superconducting qubits formed with Josephson junctions, from which we will understand the trade-off across multiple design parameters, including their noise immunity. Secondly, we will discuss different schemes to achieve entanglement gate operations, which are a major bottleneck in achieving more efficient fault-tolerant quantum computing. Thirdly, we will review readout engineering, including the implementations of the Purcell filters and quantum-limited amplifiers. Finally, we will discuss the nature and review the studies of two-level system defects, which are currently the limiting factor of qubit coherence time. DiVincenzo's criteria are only the necessary conditions for a technology to be eligible for quantum computing. To have a useful quantum computer, large-scale integration is required. We will review proposals and developments for the large-scale integration of superconducting qubit devices. By comparing with the application of electronic design automation (EDA) in semiconductors, we will also review the use of EDA in superconducting qubit quantum computer design, which is necessary for its large-scale integration.
Quantum Electronic Design Automation (Q-EDA) is emerging as quantum chips move from laboratory prototypes to scalable engineering systems. This paper argues that superconducting quantum chip design is approaching a "SPICE moment" similar to early classical EDA, where growing qubit scale, control complexity, frequency planning, packaging, process variation, and cryogenic measurement feedback require a shift from experience-based design to model-driven engineering. We propose a Quantum Chip Paradigm Framework that treats Q-EDA not only as software, but as part of the quantum chip development paradigm. Unlike classical HDL-first design, quantum chip design must begin with physical structures such as Josephson junctions, resonators, couplers, readout elements, control lines, and packaging environments. The framework emphasizes PCell-based modeling, SPICE-Q simulation, Quantum PDKs, and design-technology-measurement co-optimization. We further outline a hierarchical Q-EDA system spanning physical structures, qubit PCells, logical qubits, quantum arithmetic, functional quantum IP, and Quantum SoC systems. The key goal is to turn physical models, layout rules, simulation results, fabrication data, and measurement feedback into reusable and auditable engineering objects for large-scale quantum processors and fault-tolerant quantum computing.
Superconducting qubits are pivotal in advancing quantum computing, poised for scale but limited by the complexity and fidelity of their control and readout systems, relying on RF and signal processing infrastructure. This survey serves as a comprehensive and technically grounded review of control and readout architectures tailored for superconducting qubits. Synthesizing insights from device physics, circuit design, microwave engineering, signal processing, and cryogenic integration, this work details the practicalities of RF pulse generation, signal synthesis, and readout signal analysis for quantum systems. it covers key requirements, parameters, and pulse engineering techniques, including commonly used envelopes like Gaussian and DRAG designs. Moving to the system level, this survey systematically classifies and critically analyses current architectural strategies (covering key areas like frequency conversion, waveform management, and system infrastructure) and technology platforms (including adaptive classical control stacks, cryogenic CMOS circuits, and novel interconnects and interfaces), evaluating their trade-offs in performance. Extensive literature analysis identifies prevailing limitations such as wiring complexity, thermal budget constraints, latency, and power consumption, while highlighting underexplored opportunities for on-chip signal processing and novel interconnects, drawing analogies to advanced communication systems design. By consolidating diverse control paradigms and critically evaluating their trade-offs, this survey provides a unified foundation for designing next-generation quantum control stacks. Finally, a forward-looking roadmap outlines key trends in monolithic integration, cryo-compatible digital architectures, and physics-informed hardware co-design, offering both a retrospective synthesis and a prospective vision for quantum hardware engineering beyond the NISQ era.
Design, simulation, analysis and verification methodologies are crucial for developing electronic circuits and systems at large. Whereas long-standing EDA software is used in the semiconductor technology, there is no counterpart for quantum computing systems yet. Although the quantum computing community started utilizing and adapting some of the already existing EDA tools, for instance, to design quantum processors and control electronics for driving the qubits, or even to solve some quantum computing design tasks, they do not fully use the expertise gained over the last decades in the field of design automation. Current intermediate-scale quantum computers have been designed in an ‘adhoc’ manner with heterogeneous methods and tools. As we are entering the large-scale era, it is timely and key to further adopt EDA methodologies and software for quantum computing. In this paper, we provide an overview on how full-stack quantum computing systems are being implemented nowadays and discuss which the main challenges are for transitioning from this current scenario to a comprehensive framework encompassing full automated system-wide architecting, design, simulation, verification, and test.
Superconductive silicon is one of the most promising technologies for implementing practical quantum computers. EDA vendors can assist in the quantum hardware designers’ endeavors by providing solutions that can lead to designs of increased qubit quality. This technical report presents a new modeling engine that is able to model tens to hundreds of physical qubits capturing all coupling and crosstalk between them, thus providing the quantum hardware designers with vital information on the quality of their designs.