Qasmbench: a Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation
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Qiskit Backend Specifications for Openqasm and Openpulse
Qiskit Backend Specifications for OpenQASM and OpenPulse Experiments David C. McKay1,∗ Thomas Alexander1, Luciano Bello1, Michael J. Biercuk2, Lev Bishop1, Jiayin Chen2, Jerry M. Chow1, Antonio D. C´orcoles1, Daniel Egger1, Stefan Filipp1, Juan Gomez1, Michael Hush2, Ali Javadi-Abhari1, Diego Moreda1, Paul Nation1, Brent Paulovicks1, Erick Winston1, Christopher J. Wood1, James Wootton1 and Jay M. Gambetta1 1IBM Research 2Q-CTRL Pty Ltd, Sydney NSW Australia September 11, 2018 Abstract As interest in quantum computing grows, there is a pressing need for standardized API's so that algorithm designers, circuit designers, and physicists can be provided a common reference frame for designing, executing, and optimizing experiments. There is also a need for a language specification that goes beyond gates and allows users to specify the time dynamics of a quantum experiment and recover the time dynamics of the output. In this document we provide a specification for a common interface to backends (simulators and experiments) and a standarized data structure (Qobj | quantum object) for sending experiments to those backends via Qiskit. We also introduce OpenPulse, a language for specifying pulse level control (i.e. control of the continuous time dynamics) of a general quantum device independent of the specific arXiv:1809.03452v1 [quant-ph] 10 Sep 2018 hardware implementation. ∗[email protected] 1 Contents 1 Introduction3 1.1 Intended Audience . .4 1.2 Outline of Document . .4 1.3 Outside of the Scope . .5 1.4 Interface Language and Schemas . .5 2 Qiskit API5 2.1 General Overview of a Qiskit Experiment . .7 2.2 Provider . .8 2.3 Backend . -
Qubic: an Open Source FPGA-Based Control and Measurement System for Superconducting Quantum Information Processors
1 QubiC: An open source FPGA-based control and measurement system for superconducting quantum information processors Yilun Xu,1 Gang Huang,1 Jan Balewski,1 Ravi Naik,2 Alexis Morvan,1 Bradley Mitchell,2 Kasra Nowrouzi,1 David I. Santiago,1 and Irfan Siddiqi1;2 1Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA 2University of California at Berkeley, Berkeley, CA 94720, USA Corresponding author: Gang Huang (email: [email protected]) Abstract—As quantum information processors grow in quan- for general purpose test and measurement applications, and tum bit (qubit) count and functionality, the control and measure- typically cannot keep pace both in terms of footprint and cost ment system becomes a limiting factor to large scale extensibility. as quantum system complexity increases [6]. A customized To tackle this challenge and keep pace with rapidly evolving classical control requirements, full control stack access is essential quantum engineering solution rooted in extensible primitives to system level optimization. We design a modular FPGA (field- is needed for the quantum computing community. programmable gate array) based system called QubiC to control The field-programmable gate array (FPGA) architecture and measure a superconducting quantum processing unit. The allows for customized solutions capable of growing and evolv- system includes room temperature electronics hardware, FPGA ing with the field [7]. Several FPGA frameworks have been gateware, and engineering software. A prototype hardware mod- ule is assembled from several commercial off-the-shelf evaluation developed for quantum control and measurement [8]–[11]. boards and in-house developed circuit boards. Gateware and Nevertheless, current FPGA-based control systems are not software are designed to implement basic qubit control and fully open to the broader quantum community so it is hard measurement protocols. -
BCG) Is a Global Management Consulting Firm and the World’S Leading Advisor on Business Strategy
The Next Decade in Quantum Computing— and How to Play Boston Consulting Group (BCG) is a global management consulting firm and the world’s leading advisor on business strategy. We partner with clients from the private, public, and not-for-profit sectors in all regions to identify their highest-value opportunities, address their most critical challenges, and transform their enterprises. Our customized approach combines deep insight into the dynamics of companies and markets with close collaboration at all levels of the client organization. This ensures that our clients achieve sustainable competitive advantage, build more capable organizations, and secure lasting results. Founded in 1963, BCG is a private company with offices in more than 90 cities in 50 countries. For more information, please visit bcg.com. THE NEXT DECADE IN QUANTUM COMPUTING— AND HOW TO PLAY PHILIPP GERBERT FRANK RUESS November 2018 | Boston Consulting Group CONTENTS 3 INTRODUCTION 4 HOW QUANTUM COMPUTERS ARE DIFFERENT, AND WHY IT MATTERS 6 THE EMERGING QUANTUM COMPUTING ECOSYSTEM Tech Companies Applications and Users 10 INVESTMENTS, PUBLICATIONS, AND INTELLECTUAL PROPERTY 13 A BRIEF TOUR OF QUANTUM COMPUTING TECHNOLOGIES Criteria for Assessment Current Technologies Other Promising Technologies Odd Man Out 18 SIMPLIFYING THE QUANTUM ALGORITHM ZOO 21 HOW TO PLAY THE NEXT FIVE YEARS AND BEYOND Determining Timing and Engagement The Current State of Play 24 A POTENTIAL QUANTUM WINTER, AND THE OPPORTUNITY THEREIN 25 FOR FURTHER READING 26 NOTE TO THE READER 2 | The Next Decade in Quantum Computing—and How to Play INTRODUCTION he experts are convinced that in time they can build a Thigh-performance quantum computer. -
Mapping Quantum Algorithms in a Crossbar Architecture
Mapping QUANTUM ALGORITHMS IN A CROSSBAR ARCHITECTURE Alejandro MorAIS Mapping quantum algorithms in a crossbar architecture by Alejandro Morais to obtain the degree of Master of Science at the Delft University of Technology, to be defended publicly on the 25th of September 2019. Student number: 4747240 Project duration: November 1, 2018 – July 1, 2019 Thesis committee: Dr. ir. C.G. Almudever, QCA, TU Delft Dr. ir. Z. Al-Ars, CE, TU Delft Dr. ir. F. Sebastiano, AQUA, TU Delft Dr. ir. M. Veldhorst, QuTech, TU Delft Supervisor: Dr. ir. C.G. Almudever, QCA, TU Delft An electronic version of this thesis is available at https://repository.tudelft.nl/. Abstract In recent years, Quantum Computing has gone from theory to a promising reality, leading to quantum chips that in a near future might be able to exceed the computational power of any current supercomputer. For this to happen, there are some problems that must be overcome. For example, in a quantum processor, qubits are usually arranged in a 2D architecture with limited connectivity between them and in which only nearest-neighbour interactions are allowed. This restricts the execution of two-qubit gates and requires qubit to be moved to adjacent positions. Quantum algorithms, which are described as quantum circuits, neglect the quantum chip constraints and therefore cannot be directly executed. This is known as the mapping problem. This thesis focuses on the problem of mapping quantum algorithms into a quantum chip based on spin qubits, called the crossbar architecture. In this project we have developed the required compiler support (mapping) for making quantum circuits executable on the crossbar architecture based on the tools provided by OpenQL. -
Quantum Computing in the NISQ Era and Beyond
Quantum Computing in the NISQ era and beyond John Preskill Institute for Quantum Information and Matter and Walter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena CA 91125, USA 30 July 2018 Noisy Intermediate-Scale Quantum (NISQ) technology will be available in the near future. Quantum computers with 50-100 qubits may be able to perform tasks which surpass the capabilities of today’s classical digital computers, but noise in quantum gates will limit the size of quantum circuits that can be executed reliably. NISQ devices will be useful tools for exploring many-body quantum physics, and may have other useful applications, but the 100-qubit quantum computer will not change the world right away — we should regard it as a significant step toward the more powerful quantum technologies of the future. Quantum technologists should continue to strive for more accurate quantum gates and, eventually, fully fault-tolerant quantum computing. 1 Introduction Now is an opportune time for a fruitful discussion among researchers, entrepreneurs, man- agers, and investors who share an interest in quantum computing. There has been a recent surge of investment by both large public companies and startup companies, a trend that has surprised many quantumists working in academia. While we have long recognized the commercial potential of quantum technology, this ramping up of industrial activity has happened sooner and more suddenly than most of us expected. In this article I assess the current status and future potential of quantum computing. Because quantum computing technology is so different from the information technology we use now, we have only a very limited ability to glimpse its future applications, or to project when these applications will come to fruition. -
Hacking the Superdense Coding Protocol on IBM's Quantum Computers
Cyberattacks on Quantum Networked Computation and Communications – Hacking the Superdense Coding Protocol on IBM’s Quantum Computers Carlos Pedro Gonçalves May 18, 2021 Lusophone University of Humanities and Technologies, e-mail: [email protected] Abstract The development of automated gate specification for quantum com- munications and quantum networked computation opens up the way for malware designed at corrupting the automation software, changing the au- tomated quantum communications protocols and algorithms. We study two types of attacks on automated quantum communications protocols and simulate these attacks on the superdense coding protocol, using re- mote access to IBM’s Quantum Computers available through IBM Q Ex- perience to simulate these attacks on what would be a low noise quan- tum communications network. The first type of attack leads to a hacker- controlled bijective transformation of the final measured strings, the sec- ond type of attack is a unitary scrambling attack that modifies the au- tomated gate specification to effectively scramble the final measurement, disrupting quantum communications and taking advantage of quantum randomness upon measurement in a way that makes it difficult to distin- guish from hardware malfunction or from a sudden rise in environmental noise. We show that, due to quantum entanglement and symmetries, the second type of attack works as a way to strategically disrupt quantum arXiv:2105.07187v1 [quant-ph] 15 May 2021 communications networks and quantum networked computation in a way that makes it difficult to ascertain which node was attacked. The main findings are discussed in the wider setting of quantum cybersecurity and quantum networked computation, where ways of hacking including the role of insider threats are discussed. -
Ope|N〉Fermion: the Electronic Structure Package for Quantum Computers
Opejni Fermion: The Electronic Structure Package for Quantum Computers Jarrod R. McClean,1, ∗ Ian D. Kivlichan,1, 2 Kevin J. Sung,3 Damian S. Steiger,1, 4 Yudong Cao,5 Chengyu Dai,6 E. Schuyler Fried,5, 7 Craig Gidney,8 Brendan Gimby,3 Thomas H¨aner,4 Tarini Hardikar,9 Vojtˇech Havl´ıˇcek,10 Cupjin Huang,3 Zhang Jiang,11 Matthew Neeley,8 Thomas O'Brien,12 Isil Ozfidan,13 Jhonathan Romero,5 Nicholas Rubin,7 Nicolas P. D. Sawaya,5 Kanav Setia,9 Sukin Sim,5 Mark Steudtner,12, 14 Wei Sun,15 Fang Zhang,3 and Ryan Babbush1, y 1Google Inc., Venice, CA 90291 2Department of Physics, Harvard University, Cambridge, MA 02138 3Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 4Theoretische Physik, ETH Zurich, 8093 Zurich, Switzerland 5Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138 6Department of Physics, University of Michigan, Ann Arbor, MI 48109 7Rigetti Computing, Berkeley CA 94710 8Google Inc., Santa Barbara, CA 93117 9Department of Physics, Dartmouth College, Hanover, NH 03755 10Department of Computer Science, Oxford University, Oxford OX1 3QD, United Kingdom 11QuAIL, NASA Ames Research Center, Moffett Field, CA 94035 12Instituut-Lorentz, Universiteit Leiden, 2300 RA Leiden, The Netherlands 13D-Wave Systems Inc., Burnaby, BC 14QuTech, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands 15Google Inc., Cambridge, MA 02142 (Dated: February 27, 2018) Quantum simulation of chemistry and materials is predicted to be an important application for both near-term and fault-tolerant quantum devices. However, at present, developing and studying algorithms for these problems can be difficult due to the prohibitive amount of domain knowl- edge required in both the area of chemistry and quantum algorithms. -
Learning Nonlinear Input–Output Maps with Dissipative Quantum Systems
Quantum Information Processing (2019) 18:198 https://doi.org/10.1007/s11128-019-2311-9 Learning nonlinear input–output maps with dissipative quantum systems Jiayin Chen1 · Hendra I. Nurdin1 Received: 17 October 2018 / Accepted: 3 May 2019 / Published online: 15 May 2019 © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract In this paper, we develop a theory of learning nonlinear input–output maps with fading memory by dissipative quantum systems, as a quantum counterpart of the theory of approximating such maps using classical dynamical systems. The theory identifies the properties required for a class of dissipative quantum systems to be universal, in that any input–output map with fading memory can be approximated arbitrarily closely by an element of this class. We then introduce an example class of dissipative quantum systems that is provably universal. Numerical experiments illustrate that with a small number of qubits, this class can achieve comparable performance to classical learning schemes with a large number of tunable parameters. Further numerical analysis sug- gests that the exponentially increasing Hilbert space presents a potential resource for dissipative quantum systems to surpass classical learning schemes for input–output maps. Keywords Machine learning with quantum systems · Dissipative quantum systems · Universality property · Reservoir computing · Nonlinear input–output maps · Fading memory maps · Nonlinear time series · Stone–Weierstrass theorem 1 Introduction We are in the midst of the noisy intermediate-scale quantum (NISQ) technology era [1], marked by noisy quantum computers consisting of roughly tens to hundreds of qubits. Currently, there is a substantial interest in early applications of these machines that can accelerate the development of practical quantum computers, akin to how the humble hearing aid stimulated the development of integrated circuit (IC) technology [2]. -
Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices
Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices Gushu Li Yufei Ding Yuan Xie University of California University of California University of California Santa Barbara, CA Santa Barbara, CA Santa Barbara, CA [email protected] [email protected] [email protected] Abstract 1 Introduction Due to little consideration in the hardware constraints, e.g., Quantum Computing (QC) has been rapidly growing in the limited connections between physical qubits to enable two- last few decades because of its potential in various important qubit gates, most quantum algorithms cannot be directly applications, including integer factorization [47], database executed on the Noisy Intermediate-Scale Quantum (NISQ) search [15], quantum simulation [36], etc. Recently, IBM, devices. Dynamically remapping logical qubits to physical Intel, and Google released their QC devices with 50, 49, and qubits in the compiler is needed to enable the two-qubit 72 qubits respectively [22, 23, 56]. IBM and Rigetti also pro- gates in the algorithm, which introduces additional oper- vide cloud QC services [18, 40], allowing more people to ations and inevitably reduces the fidelity of the algorithm. study real quantum hardware. We are expected to enter the Previous solutions in finding such remapping suffer from Noisy Intermediate-Scale Quantum (NISQ) era in the next high complexity, poor initial mapping quality, and limited few years [39], when QC devices with dozens to hundreds of flexibility and controllability. qubits will be available. Though the number of qubits is insuf- To address these drawbacks mentioned above, this paper ficient for Quantum Error Correction (QEC), .it is expected proposes a SWAP-based BidiREctional heuristic search al- that these devices will be used to solve real-world problems gorithm (SABRE), which is applicable to NISQ devices with beyond the capability of available classical computers [5, 38]. -
Qclang: High-Level Quantum Computing Language
QClang: High-Level Quantum Computing Language Klint Qinami∗ Connor Abbott∗ *Columbia University in the City of New York [email protected], [email protected] ABSTRACT QClang [/klæN/] is a high-level, imperative programming language intended for the implementation and rapid prototyping of quantum algorithms. Its features include user-defined functions, unitary gates, quantum and classical data built-ins, and vectorized operators. The QClang compiler semantically enforces quantum restrictions, like the no-cloning theorem, through substructural typing. QClang code is compiled to the Open QASM intermediate representation and thus can be freely executed on various simulators and physical quantum machines, including the IBM Quantum Experience. Its syntax closely resembles that of the C pro- gramming language and other modern languages. These features, coupled with its higher-level control flow and abstraction, allow for a large reduction in the number of statements required to implement sophisticated quantum computing algorithms when compared to an equivalent implementation in Open QASM. The compiler, along with its regression test suite, is available on GitHub. KEYWORDS: compilers, quantum computing, Open QASM, imperative languages. 1 Background 1.1 Motivation Programming directly in a low-level language like Open QASM can be exceptionally difficult. While developing minimal programs is possible, generating hand-written Open QASM implementations of more sophisticated programs quickly becomes unwieldy. This challenge has already led to the development of SDKs like the Quantum Information Software Kit (QISKit), which allows for the generation of Open QASM IR through a higher-level language like Python. This additional abstraction naturally allows for quick prototyping, the generation of larger, more sophisticated programs, and greater ease-of-use. -
Dance with Noise in NISQ Era — a NASA Perspective on Quantum Computing
Dance with Noise in NISQ Era — A NASA Perspective on Quantum Computing Zhihui Wang1,2 Eleanor Rieffel1 [email protected] [email protected] 1. NASA Quantum Artificial Intelligence Lab (QuAIL) 2. Universities Space Research Association ICCAD 2019, West Minster, CO Quantum Computing: Explore “bizarre” features of quantum mechanics Superposition Entanglement Quantum Tunneling Article developed fast, high-fidelity gates that can be executed simultaneously a across a two-dimensional qubit array. We calibrated and benchmarked the processor at both the component and system level using a powerful new tool: cross-entropy benchmarking11. Finally, we used component- level fidelities to accurately predict the performance of the whole sys- tem, further showing that quantum information behaves as expected when scaling to large systems. A suitable computational task To demonstrate quantum supremacy, we compare our quantum proces- sor against state-of-the-art classical computers in the task of sampling the output of a pseudo-random quantum circuit11,13,14. Random circuits are a suitable choice for benchmarking because they do not possess The Noisy Intermediate-Scale Quantum (NISQ) Era structure and therefore allow for limited guarantees of computational hardness10–12. We design the circuits to entangle a set of quantum bits (qubits) by repeated application of single-qubit and two-qubit logi- cal operations. Sampling the quantum circuit’s output produces a set Qubit Adjustable coupler of bitstrings, for example {0000101, 1011100, …}. Owing to quantum interference, the probability distribution of the bitstrings resembles b a speckled intensity pattern produced by light interference in laser Google scatter, such that some bitstrings are much more likely to occur than others. -
Afonso Rodrigues Validation of Quantum Simulations
Universidade do Minho Escola de Engenharia Departamento de Informática Afonso Rodrigues Validation of quantum simulations Assessing efficiency and reliability in experimental implementations November 2018 Universidade do Minho Escola de Engenharia Departamento de Informática Afonso Rodrigues Validation of quantum simulations Assessing efficiency and reliability in experimental implementations Master dissertation Master Degree in Engineering Physics Dissertation supervised by Luís Barbosa Carlos Tavares November 2018 ACKNOWLEDGEMENTS This work was only possible thanks to the contribution of several people to which I want to express my gratitude. To my supervisor prof. Luís Barbosa, for giving me the opportunity to undertake this project, and for his constant support, availability and patience; also to my co-supervisor Carlos Tavares, for his early insight. In no particular order of importance, to Miguel Nogueira, Ricardo Alves, Rui Costa, João Fonseca, Miguel Sanches, Joaquim Santos, and José Bruno, my friends and colleagues who accompanied me in this course and provided invaluable help. To my parents and sister, and Maria Coelho, André Souto and Gil Pimentel for their unconditional encouragement on the difficult days. Finally, I wish to thank University of Minho for these five years of learning, INESC TEC and specifically the HASLab team for supporting me in my first steps as a researcher. I acknowledge use of the IBM Q for this work. i ABSTRACT Quantum simulation is one of the most relevant applications of quantum computation for the near future, due to its scientific impact and also because quantum simulation algorithms are typically less demanding than generalized quantum computations. Ultimately, the success of a quantum simulation depends on the amount and reliability of information one is able to extract from the results.