As more and more small-scale quantum-coherent devices are realized, we next must learn to organize them efficiently into large-scale computers. The authors use the physics of quantum control to engineer efficient, scalable physical-layer controllers at the interface between conventional and quantum systems. They demonstrate an ``assembly language'' based on Walsh functions that unifies classical hardware constraints and capabilities, the underlying needs of the quantum-coherent devices, and the mathematics of quantum algorithms and control.
As more and more small-scale quantum-coherent devices are realized, we next must learn to organize them efficiently into large-scale computers. The authors use the physics of quantum control to engineer efficient, scalable physical-layer controllers at the interface between conventional and quantum systems. They demonstrate an ``assembly language'' based on Walsh functions that unifies classical hardware constraints and capabilities, the underlying needs of the quantum-coherent devices, and the mathematics of quantum algorithms and control.
Tomorrow's much anticipated quantum computers, exotic as they may be, will require complex classical hardware for their control and operation. For solid-state quantum processors, the authors propose an efficient scheme for executing a quantum algorithm via a multicomponent classical interface. These components, which include cryogenic classical logic, are assembled to demonstrate control of a quantum-dot qubit. Thus, when the new wave of hardware finally arrives, we will be ready--and able--to use it.
Abstract Spanning a range of hardware platforms, the building-blocks of quantum processors are today sufficiently advanced to begin work on scaling-up these systems into complex quantum machines. A key subsystem of all quantum machinery is the interface between the isolated qubits that encode quantum information and the classical control and readout technology needed to operate them. As few-qubit devices are combined to construct larger, fault-tolerant quantum systems in the near future, the quantum-classical interface will pose new challenges that increasingly require approaches from the engineering disciplines in combination with continued fundamental advances in physics, materials and mathematics. This review describes the subsystems comprising the quantum-classical interface from the viewpoint of an engineer, experimental physicist or student wanting to enter the field of solid-state quantum information technology. The fundamental signalling operations of readout and control are reviewed for a variety of qubit platforms, including spin systems, superconducting implementations and future devices based on topological degrees-of-freedom. New engineering opportunities for technology development at the boundary between qubits and their control hardware are identified, transversing electronics to cryogenics.
Quantum computing comes with the potential to push computational boundaries in various domains including, e.g., cryptography, simulation, optimization, and machine learning. Exploiting the principles of quantum mechanics, new algorithms can be developed with capabilities that are unprecedented by classical computers. However, the experimental realization of quantum devices is an active field of research with enormous open challenges, including robustness against noise and scalabilty. While systems and control theory plays a crucial role in tackling these challenges, the principles of quantum physics lead to a (perceived) high entry barrier for entering the field of quantum computing. This tutorial paper aims at lowering the barrier by introducing basic concepts required to understand and solve research problems in quantum systems. First, we introduce fundamentals of quantum algorithms, ranging from basic ingredients such as qubits and quantum logic gates to prominent examples and more advanced concepts, e.g., variational quantum algorithms. Next, we formalize some engineering questions for building quantum devices in the real world, which requires the careful manipulation of microscopic quantities obeying quantum effects. To this end for N-level systems, we introduce basic concepts of (bilinear) quantum systems and control theory including controllability, observability, and optimal control in a unified frame. Finally, we address the problem of noise in real-world quantum systems via robust quantum control, which relies on a set-membership uncertainty description frequently employed in control. A key goal of this tutorial paper is to demystify engineering aspects of quantum computing by emphasizing that its mathematical description mainly involves linear algebra (for quantum algorithms) and the handling of bilinear control systems (for quantum systems and control theory) but does not require too much detailed knowledge of quantum physics.
Quantum computing has made significant strides, with hardware platforms now advanced enough to tackle the challenges of scaling up to larger and more robust systems. Central to this progression is the interface between quantum processors, comprising isolated qubits, and the classical systems required for their control and readout. As these systems transition from few-qubit devices to fault-tolerant architectures, the complexity of this quantum-classical interaction poses significant engineering challenges. Field-Programmable Gate Arrays (FPGAs) have emerged as an adaptable and efficient solution, offering realtime control, low-latency operations, and seamless integration. This review delves into current FPGA-based platforms, including commercial systems, as well as open-source solutions developed by academic research groups. The architecture, features, and contributions of these platforms to addressing scalability and integration issues are thoroughly examined. Additionally, the review highlights innovations in cryogeniccompatible controllers and explores the potential of Cryo-FPGAs to reduce noise and improve fidelity in quantum systems. By providing a comprehensive analysis of current technologies and identifying opportunities for advancement, this review offers valuable insights for researchers and engineers working to develop scalable quantum computing solutions.
This paper presents a comprehensive review of quantum computing and the technological foundations of quantum processors. Quantum computing represents a transformative computational paradigm that leverages the fundamental principles of quantum mechanics—such as superposition, entanglement, and quantum interference—to solve complex problems that are intractable for classical computers. At the core of this paradigm lies the quantum processor, a specialized hardware system designed to initialize, control, and measure quantum bits (qubits) through precise gate operations and coherent interactions. The survey examines the essential theoretical concepts underlying quantum computation and provides a structured comparison of leading quantum processor platforms. Prominent architectures, including superconducting circuits, trapped-ion systems, and photonic implementations, are analyzed in terms of their physical mechanisms, scalability, coherence properties, and engineering challenges. Each platform offers distinct advantages and faces specific technical limitations related to noise, error correction, and fabrication complexity. In addition to reviewing hardware developments, this study highlights key obstacles in advancing quantum processors toward large-scale, fault-tolerant systems. Issues such as qubit stability, error mitigation, thermal management, and system integration are discussed to present a realistic perspective on current progress. Performance indicators including gate fidelity, coherence time, connectivity, and scalability are used to compare architectural approaches. The objective of this paper is to provide a clear and organized synthesis of recent advancements in quantum computing hardware, thereby offering researchers and practitioners a foundational reference to support continued innovation and development in this rapidly evolving field.
This paper describes the verification of the classical software and hardware stack that is used to control cold atom- and superconducting-based quantum computing hardware. The paper serves both as an introduction to quantum computing and to how classical device verification techniques can be employed there. Two main challenges in building a quantum control stack are generating precise deterministic-timing operations at the edge and scaled-out processing in the middle layer. Both challenges are to do with a certain kind of functional performance correctness. And, as usual, the design lives under tight power, memory and latency constraints. The quantum control stack is a complex interaction of algorithms, software runtimes and digital hardware. We take inspiration from modern software approaches to engineering, such as continuous integration and hardware automation, to quickly ship experimental features to customers in the field.