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Register a new userFull-Stack, Real-System Quantum Computer Studies: Architectural Comparisons and Design Insights
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In recent years, Quantum Computing (QC) has progressed to the point where small working prototypes are available for use. Termed Noisy Intermediate-Scale Quantum (NISQ) computers, these prototypes are too small for large benchmarks or even for Quantum Error Correction, but they do have sufficient resources to run small benchmarks, particularly if compiled with optimizations to make use of scarce qubits and limited operation counts and coherence times. QC has not yet, however, settled on a particular preferred device implementation technology, and indeed different NISQ prototypes implement qubits with very different physical approaches and therefore widely-varying device and machine characteristics. Our work performs a full-stack, benchmark-driven hardware-software analysis of QC systems. We evaluate QC architectural possibilities, software-visible gates, and software optimizations to tackle fundamental design questions about gate set choices, communication topology, the factors affecting benchmark performance and compiler optimizations. In order to answer key cross-technology and cross-platform design questions, our work has built the first top-to-bottom toolflow to target different qubit device technologies, including superconducting and trapped ion qubits which are the current QC front-runners. We use our toolflow, TriQ, to conduct {em real-system} measurements on 7 running QC prototypes from 3 different groups, IBM, Rigetti, and University of Maryland. From these real-system experiences at QCs hardware-software interface, we make observations about native and software-visible gates for different QC technologies, communication topologies, and the value of noise-aware compilation even on lower-noise platforms. This is the largest cross-platform real-system QC study performed thus far; its results have the potential to inform both QC device and compiler design going forward.
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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. 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. 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 towards 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 while the second case offers perfect qubits to the quantum application developer, where there is no decoherence nor error-rates. We conclude the paper 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 optimisation problems based on quantum heuristic approaches.
The development of a large scale quantum computer is a highly sought after goal of fundamental research and consequently a highly non-trivial problem. Scalability in quantum information processing is not just a problem of qubit manufacturing and control but it crucially depends on the ability to adapt advanced techniques in quantum information theory, such as error correction, to the experimental restrictions of assembling qubit arrays into the millions. In this paper we introduce a feasible architectural design for large scale quantum computation in optical systems. We combine the recent developments in topological cluster state computation with the photonic module, a simple chip based device which can be used as a fundamental building block for a large scale computer. The integration of the topological cluster model with this comparatively simple operational element addresses many significant issues in scalable computing and leads to a promising modular architecture with complete integration of active error correction exhibiting high fault-tolerant thresholds.
We describe staq, a full-stack quantum processing toolkit written in standard C++. staq is a quantum compiler toolkit, comprising of tools that range from quantum optimizers and translators to physical mappers for quantum devices with restricted connectives. The design of staq is inspired from the UNIX philosophy of less is more, i.e. staq achieves complex functionality via combining (piping) small tools, each of which performs a single task using the most advanced current state-of-the-art methods. We also provide a set of illustrative benchmarks.
We study the correlation clustering problem using the quantum approximate optimization algorithm (QAOA) and qudits, which constitute a natural platform for such non-binary problems. Specifically, we consider a neutral atom quantum computer and propose a full stack approach for correlation clustering, including Hamiltonian formulation of the algorithm, analysis of its performance, identification of a suitable level structure for ${}^{87}{rm Sr}$ and specific gate design. We show the qudit implementation is superior to the qubit encoding as quantified by the gate count. For single layer QAOA, we also prove (conjecture) a lower bound of $0.6367$ ($0.6699$) for the approximation ratio on 3-regular graphs. Our numerical studies evaluate the algorithms performance by considering complete and ErdH{o}s-Renyi graphs of up to 7 vertices and clusters. We find that in all cases the QAOA surpasses the Swamy bound $0.7666$ for the approximation ratio for QAOA depths $p geq 2$. Finally, by analysing the effect of errors when solving complete graphs we find that their inclusion severely limits the algorithms performance.
Quantum computers, if fully realized, promise to be a revolutionary technology. As a result, quantum computing has become one of the hottest areas of research in the last few years. Much effort is being applied at all levels of the system stack, from the creation of quantum algorithms to the development of hardware devices. The quantum age appears to be arriving sooner rather than later as commercially useful small-to-medium sized machines have already been built. However, full-scale quantum computers, and the full-scale algorithms they would perform, remain out of reach for now. It is currently uncertain how the first such computer will be built. Many different technologies are competing to be the first scalable quantum computer.
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