Quantum computing is on the verge of a transition from fundamental research to practical applications. Yet, to make the step to large-scale quantum computation, an extensible qubit system has to be developed. In classical semiconductor technology, this was made possible by the invention of the integrated circuit, which allowed to interconnect large numbers of components without having to solder to each and every one of them. Similarly, we expect that the scaling of interconnections and control lines with the number of qubits will be a central bottleneck in creating large-scale quantum technology. Here, we define the quantum Rent's exponent $p$ to quantify the progress in overcoming this challenge at different levels throughout the quantum computing stack. We further discuss the concept of quantum extensibility as an indicator of a platform's potential to reach the large quantum volume needed for universal quantum computing and review extensibility limits faced by different qubit implementations on the way towards truly large-scale qubit systems.
Quantum computing is on the verge of a transition from fundamental research to practical applications. Yet, to make the step to large-scale quantum computation, an extensible qubit system has to be developed. In classical semiconductor technology, this was made possible by the invention of the integrated circuit, which allowed to interconnect large numbers of components without having to solder to each and every one of them. Similarly, we expect that the scaling of interconnections and control lines with the number of qubits will be a central bottleneck in creating large-scale quantum technology. Here, we define the quantum Rent's exponent p to quantify the progress in overcoming this challenge at different levels throughout the quantum computing stack. We further discuss the concept of quantum extensibility as an indicator of a platform's potential to reach the large quantum volume needed for universal quantum computing and review extensibility limits faced by different qubit implementations on the way towards truly large-scale qubit systems.
The field of quantum computing has evolved into a large interdisciplinary community where significant resources are invested worldwide. As a result, accelerated progress is achieved and we are at the beginning of a new age of computation, developing programmable quantum systems towards universal quantum computers. Quantum computers promise to solve certain mathematical problems that are intractable to classical computers. Quantum computing systems are built from the bottom up reaching the limits of what can be classically simulated. The IBM Quantum Development Roadmap describes our vision of creating a quantum computing ecosystem delivering quantum applications through the cloud. This requires developing the entire quantum computing stack starting from the qubit and quantum processor technology, control electronics to software, algorithms and applications for quantum computing, implemented in the cloud and integrated with high performance computing. In this presentation the recent developments of our quantum computing systems and the scientific advances that enabled scaling superconducting quantum processors to 127 qubits are presented. Besides scale, also quality and speed will be discussed building the key metric for measuring the performance of quantum computation. Examples of applications where the computational power of quantum computing could make a difference are provided.
There are signs that we are approaching a technical revolution that might take humankind’s computational capabilities to a new level. Quantum Computing leverages the principles of quantum mechanics, enabling the computational power to solve specific problems currently intractable for classical computers (e.g., cracking cryptographic keys). Since we are getting to a point where we can no longer build smaller, more powerful, more efficient devices with conventional methodologies, we need to think of new ways for technological progress. The manufacturing of microchips is reaching its limits in the use of traditional architectures. Hence, new and more advanced technologies need to address the challenges of increasing energy consumption and data processing. Connectivity, scalable architectures and concepts like Cloud Computing and Software-as-a-Service have already helped to scale computational-intense applications in the last years and have attracted the interest of IS researchers (e.g., Benlian et al. 2009 ; Benlian et al. 2018 ; Messerschmidt and Hinz 2013 ). Looking ahead to the next generation, computing will comprise technologies that enable high-performance applications far beyond today’s possibilities. One prominent example with a disruptive potential is Quantum Computing. While there are abundant open questions and directions for further developments, researchers in this area have made substantial progress in the last decade, indicating that, after medical imaging, lasers, and superconductors, another quantum-technological innovation might be approaching. We, therefore, intend to provide an overview of the current state of Quantum Computing research and outline how this new technology might stimulate research in Information Systems.
Quantum computing based on superconducting integrated circuits is entering a pivotal phase, transitioning from fundamental research and development to early-stage technology scaling and industrial implementation. But still, scaling superconducting quantum computing beyond kilo-qubit levels represents a formidable challenge. Novel solutions are required such as overhead reduction and more integrated solutions in Semicon-inspired workflows. This, in turn, will lead to a renewed acceleration in superconducting quantum computing development. In this proceedings paper we address two major challenges on the path to quantum advantage: the wiring bottleneck and the test and characterization bottleneck. The wiring bottleneck arises because each qubit requires multiple dedicated control lines—up to three for current transmon-based processors—making large-scale integration difficult. Dense wiring increases thermal load and electromagnetic interference, which can degrade gate fidelities below the error-correction threshold. This creates a trade-off between scaling qubit numbers and maintaining qubit quality. The test and characterization bottleneck stems from the need to calibrate and benchmark every qubit individually, a process that scales poorly with qubit count. Unlike classical transistors, qubits require complex, quantum-level tuning, dramatically expanding the calibration parameter space. Without automation and accelerated testing, this will lead to a backlog of untested chips and limit throughput between fabrication and qualification.
For the realization of a quantum computer, a good qubit design as the basic building block is a nontrivial starting point. To fully leverage the potential of quantum computing, quantum processors will likely have to incorporate billions of high-quality qubits. Several approaches are being pursued and exhibit different strength and weaknesses. The device concepts and fabrication procedures for semiconductor based qubits are very similar to those used in the semiconductor industry. Using the spin-degree of freedom, their coherence properties and the quality of single-qubit operations have now reached the required level and are on par with competing approaches. Two-qubit operations will likely follow suit in the near future. With these basic requirements being met, it is now time to think if and how increasingly large multi-qubit systems and eventually functional quantum processor can be realized. This quest raises many pertinent questions, some of which equally apply to other qubit platforms. How reproducibly can the different types of semiconductor qubits be produced? How can their operating point be adjusted efficiently and in an automated way? How can they be connected to form meaningful multi-qubit circuits? How severe are multi-qubit control issues such as crosstalk and frequency crowding, and how can they be avoided? What control system architectures are most suitable for operating large numbers of qubits? What is the limit of cryogenic electronics regarding power consumption and integration density? This paper gives a (partial) overview of the state of the art in the field and discusses future challenges associated with the realization of large-scale quantum processors, many of which will greatly benefit from input from engineering science. The guiding vision is that of a highly integrated quantum processor with an ultra-low power cryogenic control system.
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.
Quantum computing, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.