175 research outputs found

    On Testing Quantum Programs

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    A quantum computer (QC) can solve many computational problems more efficiently than a classic one. The field of QCs is growing: companies (such as DWave, IBM, Google, and Microsoft) are building QC offerings. We position that software engineers should look into defining a set of software engineering practices that apply to QC's software. To start this process, we give examples of challenges associated with testing such software and sketch potential solutions to some of these challenges.Comment: A condensed version to appear in Proceedings of the 41st International Conference on Software Engineering (ICSE 2019

    Cross-level Validation of Topological Quantum Circuits

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    Quantum computing promises a new approach to solving difficult computational problems, and the quest of building a quantum computer has started. While the first attempts on construction were succesful, scalability has never been achieved, due to the inherent fragile nature of the quantum bits (qubits). From the multitude of approaches to achieve scalability topological quantum computing (TQC) is the most promising one, by being based on an flexible approach to error-correction and making use of the straightforward measurement-based computing technique. TQC circuits are defined within a large, uniform, 3-dimensional lattice of physical qubits produced by the hardware and the physical volume of this lattice directly relates to the resources required for computation. Circuit optimization may result in non-intuitive mismatches between circuit specification and implementation. In this paper we introduce the first method for cross-level validation of TQC circuits. The specification of the circuit is expressed based on the stabilizer formalism, and the stabilizer table is checked by mapping the topology on the physical qubit level, followed by quantum circuit simulation. Simulation results show that cross-level validation of error-corrected circuits is feasible.Comment: 12 Pages, 5 Figures. Comments Welcome. RC2014, Springer Lecture Notes on Computer Science (LNCS) 8507, pp. 189-200. Springer International Publishing, Switzerland (2014), Y. Shigeru and M.Shin-ichi (Eds.

    A comprehensive survey on quantum computer usage: How many qubits are employed for what purposes?

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    Quantum computers (QCs), which work based on the law of quantum mechanics, are expected to be faster than classical computers in several computational tasks such as prime factoring and simulation of quantum many-body systems. In the last decade, research and development of QCs have rapidly advanced. Now hundreds of physical qubits are at our disposal, and one can find several remarkable experiments actually outperforming the classical computer in a specific computational task. On the other hand, it is unclear what the typical usages of the QCs are. Here we conduct an extensive survey on the papers that are posted in the quant-ph section in arXiv and claim to have used QCs in their abstracts. To understand the current situation of the research and development of the QCs, we evaluated the descriptive statistics about the papers, including the number of qubits employed, QPU vendors, application domains and so on. Our survey shows that the annual number of publications is increasing, and the typical number of qubits employed is about six to ten, growing along with the increase in the quantum volume (QV). Most of the preprints are devoted to applications such as quantum machine learning, condensed matter physics, and quantum chemistry, while quantum error correction and quantum noise mitigation use more qubits than the other topics. These imply that the increase in QV is fundamentally relevant, and more experiments for quantum error correction, and noise mitigation using shallow circuits with more qubits will take place.Comment: 14 pages, 5 figures, figures regenerate

    Trustworthy Quantum Computation through Quantum Physical Unclonable Functions

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    Quantum computing is under rapid development, and today there are several cloud-based, quantum computers (QCs) of modest size (>100s of physical qubits). Although these QCs, along with their highly-specialized classical support infrastructure, are in limited supply, they are readily available for remote access and programming. This work shows the viability of using intrinsic quantum hardware properties for fingerprinting cloud-based QCs that exist today. We demonstrate the reliability of intrinsic fingerprinting with real QC characterization data, as well as simulated QC data, and we detail a quantum physically unclonable function (Q-PUF) scheme for secure key generation using unique fingerprint data combined with fuzzy extraction. We use fixed-frequency transmon qubits for prototyping our methods

    Subspace Variational Quantum Simulator

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    Quantum simulation is one of the key applications of quantum computing, which can accelerate research and development in chemistry, material science, etc. Here, we propose an efficient method to simulate the time evolution driven by a static Hamiltonian, named subspace variational quantum simulator (SVQS). SVQS employs the subspace-search variational eigensolver (SSVQE) to find a low-energy subspace and further extends it to simulate dynamics within the low-energy subspace. More precisely, using a parameterized quantum circuit, the low-energy subspace of interest is encoded into a computational subspace spanned by a set of computational basis, where information processing can be easily done. After the information processing, the computational subspace is decoded to the original low-energy subspace. This allows us to simulate the dynamics of low-energy subspace with lower overhead compared to existing schemes. While the dimension is restricted for feasibility on near-term quantum devices, the idea is similar to quantum phase estimation and its applications such as quantum linear system solver and quantum metropolis sampling. Because of this simplicity, we can successfully demonstrate the proposed method on the actual quantum device using Regetti Quantum Cloud Service. Furthermore, we propose a variational initial state preparation for SVQS, where the initial states are searched from the simulatable eigensubspace. Finally, we demonstrate SVQS on Rigetti Quantum Cloud Service
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