Quantum Inspire: QuTech’s platform for co-development and collaboration in quantum computing
Thorsten Last, Nodar Samkharadze, Pieter T. Eendebak, R. Versluis, Xiao Xue, Amir Sammak, Delphine Brousse, Kelvin Loh, Henk Polinder, Giordano Scappucci, Menno Veldhorst, Lieven M. K. Vandersypen, Klará Maturová, Jérémy Veltin, Garrelt Alberts
The mission of QuTech is to bring quantum technology to industry and society by translating fundamental scientific research into applied research. To this end we are developing Quantum Inspire (QI), a full-stack quantum computer prototype for future co-development and collaborative R&D in quantum computing. A prerelease of this prototype system is already offering the public cloud-based access to QuTech technologies such as a programmable quantum computer simulator (with up to 31 qubits) and tutorials and user background knowledge on quantum information science (www.quantum-inspire.com). Access to a programmable CMOS-compatible Silicon spin qubit-based quantum processor will be provided in the next deployment phase. The first generation of QI’s quantum processors consists of a double quantum dot hosted in an in-house grown SiGe/28Si/SiGe heterostructure, and defined with a single layer of Al gates. Here we give an overview of important aspects of the QI full-stack. We illustrate QI’s modular system architecture and we will touch on parts of the manufacturing and electrical characterization of its first generation two spin qubit quantum processor unit. We close with a section on QI’s qubit calibration framework. The definition of a single qubit Pauli X gate is chosen as concrete example of the matching of an experiment to a component of the circuit model for quantum computation.
The mission of QuTech is to bring quantum technology to industry and society by translating fundamental scientific research into applied research. To this end we are developing Quantum Inspire (QI), a full-stack quantum computer prototype for future co-development and collaborative R&D in quantum computing. A prerelease of this prototype system is already offering the public cloud-based access to QuTech technologies such as a programmable quantum computer simulator (with up to 31 qubits) and tutorials and user background knowledge on quantum information science (www.quantum-inspire.com). Access to a programmable CMOS-compatible Silicon spin qubit-based quantum processor will be provided in the next deployment phase. The first generation of QI’s quantum processors consists of a double quantum dot hosted in an in-house grown SiGe/28Si/SiGe heterostructure, and defined with a single layer of Al gates. Here we give an overview of important aspects of the QI full-stack. We illustrate QI’s modular system architecture and we will touch on parts of the manufacturing and electrical characterization of its first generation two spin qubit quantum processor unit. We close with a section on QI’s qubit calibration framework. The definition of a single qubit Pauli X gate is chosen as concrete example of the matching of an experiment to a component of the circuit model for quantum computation.
The understanding of quantum mechanics enabled the development of technology such as transistors and has been the foundation of today’s information age. Actively using quantum mechanics to build quantum technology may cause a second revolution in handling information. However, to execute meaningful algorithms, largescale quantum computers have to be built. Such systems are constructed from many qubits, the quantum version of the classical bit. While exciting progress is being made across a range of different qubit platforms, achieving the radical scalability that is necessary to build a largescale processor could be a roadblock. Huge challenges are put on reproducibility, inand output connectivity and material quality. Qubits based on the spins of electrons and holes confined in semiconductor quantum dots may have an important advantage in constructing quantum processors. This platform can profit from the advanced semiconductor industry that was responsible for the first computing revolution. Group IV semiconductors such as silicon and germanium have a high compatibility with industrial semiconductor manufacturing and contain stable isotopes with zero nuclear spin. The materials can be isotopically purified and serve as excellent hosts for spins with long quantum coherence. In Chapter 3 we present quantum dot arrays in silicon metaloxidesemiconductor (SiMOS), strained silicon (Si/SiGe) and strained germanium (Ge/SiGe). A nearly identical integration scheme based on an overlapping gate structure can be used to define quantum dots in each platform. Each platform has its own opportunities, which are carefully assessed. By employing charge sensing we confirm that all quantum dots can be depleted to the singleelectron regime. We compare capacitive crosstalk and find it to be the smallest in SiMOS, relevant for the tuning of quantum dot arrays. Using this crossplatform integration, we can study qubits in each platform with minimal overhead. Long coherence times, excellent singlequbit gate fidelities and twoqubit logic have been demonstrated with SiMOS spin qubits, making it one of the leading platforms for quantum information processing. However, due to the high disorder at the Si/SiO2 interface compared to Ge/SiGe and Si/SiGe interface, quantum dots defined in SiMOS are small and achieving sufficient control over single electrons has been a long standing challenge. In Chapter 5 we show experiments on a double quantum dot that can be isolated from its reservoir. We demonstrate a tunable tunnel coupling between single electrons up to 13 GHz and tunable tunnel rates down to below 1 Hz. These results mark an important step towards the required degree of control over the location of and coupling between quantum dots, necessary for the operation of a large array.
This article presents the definition and implementation of a quantum computer architecture to enable creating a new computational device-a quantum computer as an accelerator. A key question addressed is what such a quantum computer is and how it relates to the classical processor that controls the entire execution process. In this article, we present explicitly the idea of a quantum accelerator that contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL, which visualized the quantum processor as a computational accelerator. The OpenQL compiler translates the program to a common assembly language, called cQASM, which can be executed on a quantum simulator. The cQASM represents the instruction set that can be executed by the microarchitecture implemented in the quantum accelerator. In a subsequent step, the compiler can convert the cQASM to generate the eQASM, which is executable on a particular experimental device incorporating the platform-specific parameters. This way, we are able to distinguish clearly the experimental research toward better qubits, and the industrial and societal applications that need to be developed and executed on a quantum device. The first case offers experimental physicists with a full-stack experimental platform using realistic qubits with decoherence and error-rates, whereas the second case offers perfect qubits to the quantum application developer, where there is neither decoherence nor error-rates. We conclude the article by explicitly presenting three examples of full-stack quantum accelerators, for an experimental superconducting processor, for quantum accelerated genome sequencing and for near-term generic optimization problems based on quantum heuristic approaches. The two later full-stack models are currently being actively researched in our group.
In a world of various competing quantum computing architectures, hardware-agnostic, full-stack platforms are necessary to bring the full power of quantum computing hardware to domain experts via the cloud. QCI Connect and its Software Development Kit provide a reference architecture for a full-stack platform with a modular design and open-source interface definitions, built to facilitate a community-driven application ecosystem. Here, we present its overall design and features, central interfaces, and lessons learned, both for users of the platform and as a reference guide for future developments.
Over the last 20 years there has been a steady increase in fundamental physics research and the hardware development needed to realize a quantum computer. However, in the last 5 years we have seen a dramatic increase in the interest from industry, including a variety of major semiconductor and technology leaders such as IBM, Google and Intel. This is the result of both a better understanding of the variety of problems that can be addressed and the impact that will come with quantum computing along with the emergence of a couple of potentially scalable hardware solutions. In a recent interview with a leading manufacturer, an aggressive strategy was laid out to achieve an operational 1000-qubit quantum computer within 5 years that can solve a variety of problems not addressable by conventional computing and the 10-year prospect to achieve a 1 million qubit machine that would “profoundly change society”. The major technology leaders view quantum information (QI) as a technology that they must begin to develop and understand today. Augmenting existing technology with QI is desirable, but , there are a variety of technical challenges to making silicon-based QI systems with the needed quantum properties and coherence times. New challenges in atomic precision and individual atom or electron effects that fundamentally affect device performance bring on a variety of new manufacturing and metrology challenges. Measuring electron spin coherence, exchange energies, and qubit fidelity are entirely new measurements for the semiconductor industry. Even the resolution of TEM may be inadequate, as TEM of a nominally 80 nm thick slice of silicon which averages many atoms together in a measurement where only one or two atoms can deeply change device performance, coherence times, or introduce charge offsets. After developing some of the first cold atom and ion trap quantum information demonstrations at NIST, we are now investing significantly in developing the supporting metrology and modeling methods needed to help industry develop and commercialize this new technology. In this presentation we will provide an overview of hardware solutions for quantum computing, future metrology needs and challenges to enable manufacturable quantum computers. Although industry leaders are now investing in superconducting qubits and silicon-based qubits, the two leading technologies, this talk will primarily focus on the principles of solid state silicon QI operation, manufacturing metrology solutions, and measurements needed to develop and evaluate viable technological solutions.
This paper presents the definition and implementation of a quantum computer architecture to enable creating a new computational device - a quantum computer as an accelerator In this paper, we present explicitly the idea of a quantum accelerator which contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. Important to realise is that qubits are defined as perfect qubits, implying they do not decohere and perform good quantum gate operations. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL. We also have to start thinking about how to verify, validate and test the quantum software such that the compiler generates a correct version of the quantum circuit. The OpenQL compiler translates the program to a common assembly language, called cQASM. We need to develop a quantum operating system that manages all the hardware of the micro-architecture. The layer below the micro-architecture is responsible of the mapping and routing of the qubits on the topology such that the nearest-neighbour-constraint can be be respected. At any moment in the future when we are capable of generating multiple good qubits, the compiler can convert the cQASM to generate the eQASM, which is executable on a particular experimental device incorporating the platform-specific parameters. This way, we are able to distinguish clearly the experimental research towards better qubits, and the industrial and societal applications that need to be developed and executed on a quantum device.
This paper presents the definition and implementation of a quantum computer architecture to enable creating a new computational device - a quantum computer as an accelerator. A key question addressed is what such a quantum computer is and how it relates to the classical processor that controls the entire execution process. In this paper, we present explicitly the idea of a quantum accelerator which contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL, which visualised the quantum processor as a computational accelerator. The OpenQL compiler translates the program to a common assembly language, called cQASM, which can be executed on a quantum simulator. The cQASM represents the instruction set that can be executed by the micro-architecture implemented in the quantum accelerator. We propose that the industrial and societal application developers use perfect qubits that have no decoherence or error-rates. The perfect qubits offers facilities to the quantum application developer and they are not blocked by issues such as decoherence.