Download or read book Hands On Quantum Information Processing with Python written by Makhamisa Senekane and published by . This book was released on 2021-01-29 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the potential of quantum information processing and understand the state of a quantum system with this practical guide Key Features: Get well-versed with quantum information processing using Python Understand the basics of quantum cryptography by implementing quantum key distribution protocols in Python Implement well-known games such as the CHSH and GHZ games using quantum strategies and techniques Book Description: Quantum computation is the study of a subclass of computers that exploits the laws of quantum mechanics to perform certain operations that are thought to be difficult to perform on a non-quantum computer. Hands-On Quantum Information Processing with Python begins by taking you through the essentials of quantum information processing to help you explore its potential. Next, you'll become well-versed with the fundamental property of quantum entanglement and find out how to illustrate this using the teleportation protocol. As you advance, you'll discover how quantum circuits and algorithms such as Simon's algorithm, Grover's algorithm, and Shor's algorithm work, and get to grips with quantum cryptography by implementing important quantum key distribution (QKD) protocols in Python. You will also learn how to implement non-local games such as the CHSH game and the GHZ game by using Python. Finally, you'll cover key quantum machine learning algorithms, and these implementations will give you full rein to really play with and fully understand more complicated ideas. By the end of this quantum computing book, you will have gained a deeper understanding and appreciation of quantum information. What You Will Learn: Discover how quantum circuits and quantum algorithms work Familiarize yourself with non-local games and learn how to implement them Get to grips with various quantum computing models Implement quantum cryptographic protocols such as BB84 and B92 in Python Explore entanglement and teleportation in quantum systems Find out how to measure and apply operations to qubits Delve into quantum computing with the continuous-variable quantum state Get acquainted with essential quantum machine learning algorithms Who this book is for: This book is for developers, programmers, or undergraduates in computer science who want to learn about the fundamentals of quantum information processing. A basic understanding of the Python programming language is required, and a good grasp of math and statistics will be useful to get the best out of this book.

Download or read book A Practical Guide to Quantum Machine Learning and Quantum Optimization written by Elias F. Combarro and published by Packt Publishing Ltd. This book was released on 2023-03-31 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with fully explained algorithms and ready-to-use examples that can be run on quantum simulators and actual quantum computers with this comprehensive guide Key FeaturesGet a solid grasp of the principles behind quantum algorithms and optimization with minimal mathematical prerequisitesLearn the process of implementing the algorithms on simulators and actual quantum computersSolve real-world problems using practical examples of methodsBook Description This book provides deep coverage of modern quantum algorithms that can be used to solve real-world problems. You'll be introduced to quantum computing using a hands-on approach with minimal prerequisites. You'll discover many algorithms, tools, and methods to model optimization problems with the QUBO and Ising formalisms, and you will find out how to solve optimization problems with quantum annealing, QAOA, Grover Adaptive Search (GAS), and VQE. This book also shows you how to train quantum machine learning models, such as quantum support vector machines, quantum neural networks, and quantum generative adversarial networks. The book takes a straightforward path to help you learn about quantum algorithms, illustrating them with code that's ready to be run on quantum simulators and actual quantum computers. You'll also learn how to utilize programming frameworks such as IBM's Qiskit, Xanadu's PennyLane, and D-Wave's Leap. Through reading this book, you will not only build a solid foundation of the fundamentals of quantum computing, but you will also become familiar with a wide variety of modern quantum algorithms. Moreover, this book will give you the programming skills that will enable you to start applying quantum methods to solve practical problems right away. What you will learnReview the basics of quantum computingGain a solid understanding of modern quantum algorithmsUnderstand how to formulate optimization problems with QUBOSolve optimization problems with quantum annealing, QAOA, GAS, and VQEFind out how to create quantum machine learning modelsExplore how quantum support vector machines and quantum neural networks work using Qiskit and PennyLaneDiscover how to implement hybrid architectures using Qiskit and PennyLane and its PyTorch interfaceWho this book is for This book is for professionals from a wide variety of backgrounds, including computer scientists and programmers, engineers, physicists, chemists, and mathematicians. Basic knowledge of linear algebra and some programming skills (for instance, in Python) are assumed, although all mathematical prerequisites will be covered in the appendices.

Download or read book Learn Quantum Computing with Python and Q written by Sarah C. Kaiser and published by Simon and Schuster. This book was released on 2021-06-22 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: "For software developers. No prior experience with quantum computing required"--Back cover.

Download or read book Learn Quantum Computing with Python and IBM Quantum Experience written by Robert Loredo and published by Packt Publishing Ltd. This book was released on 2020-09-28 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step guide to learning the implementation and associated methodologies in quantum computing with the help of the IBM Quantum Experience, Qiskit, and Python that will have you up and running and productive in no time Key FeaturesDetermine the difference between classical computers and quantum computersUnderstand the quantum computational principles such as superposition and entanglement and how they are leveraged on IBM Quantum Experience systemsRun your own quantum experiments and applications by integrating with QiskitBook Description IBM Quantum Experience is a platform that enables developers to learn the basics of quantum computing by allowing them to run experiments on a quantum computing simulator and a real quantum computer. This book will explain the basic principles of quantum mechanics, the principles involved in quantum computing, and the implementation of quantum algorithms and experiments on IBM's quantum processors. You will start working with simple programs that illustrate quantum computing principles and slowly work your way up to more complex programs and algorithms that leverage quantum computing. As you build on your knowledge, you'll understand the functionality of IBM Quantum Experience and the various resources it offers. Furthermore, you'll not only learn the differences between the various quantum computers but also the various simulators available. Later, you'll explore the basics of quantum computing, quantum volume, and a few basic algorithms, all while optimally using the resources available on IBM Quantum Experience. By the end of this book, you'll learn how to build quantum programs on your own and have gained practical quantum computing skills that you can apply to your business. What you will learnExplore quantum computational principles such as superposition and quantum entanglementBecome familiar with the contents and layout of the IBM Quantum ExperienceUnderstand quantum gates and how they operate on qubitsDiscover the quantum information science kit and its elements such as Terra and AerGet to grips with quantum algorithms such as Bell State, Deutsch-Jozsa, Grover's algorithm, and Shor's algorithmHow to create and visualize a quantum circuitWho this book is for This book is for Python developers who are looking to learn quantum computing and put their knowledge to use in practical situations with the help of IBM Quantum Experience. Some background in computer science and high-school-level physics and math is required.

Download or read book Hands On Quantum Machine Learning With Python written by Frank Zickert and published by Independently Published. This book was released on 2023-01-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to become a quantum machine learning practitioner? ... But you don't want to study theoretical physics first Then, "Hands-On Quantum Machine Learning With Python" is for you. This book has one goal - to help developers, practitioners, and students like yourself become quantum machine learning experts. It doesn't matter if it is the first time you have worked with machine learning and quantum computing. Hands-On Quantum Machine Learning With Python is engineered from the ground up to help you reach expert status. Inside this book, you'll find: Super practical walkthroughs present solutions to real-world combinatorial optimization problems and challenges. Hands-on tutorials (with lots of code) show you the Variational Quantum Eigensolver and its implementation and usage. An accessible teaching style guaranteed to get you through the underlying maths and physics and master machine quantum learning. In this volume, you will learn how to solve current optimization problems on real quantum computers. We will dive deep into the Variational Quantum Eigensolver (VQE) and use it to solve combinatorial optimization problems. Combinatorial optimization is of paramount importance in many industries. For example, the famous Traveling Salesman Problem (TSP) asks for the shortest route between different cities. It is crucial for parcel delivery, aviation, and almost all mobility-related fields. The ability to solve these problems will enable you to be well prepared to find or keep a job in any of these fields being disrupted by the advent of quantum computing. -- Is this book right for me? -- You don't need to be a mathematician. You don't need to be a physicist, either. This book is for students, developers, data scientists, and practitioners interested in applying quantum machine learning to actual problems - today. "I am new to quantum computing and machine learning altogether." - No problem! Hands-On Quantum Machine Learning With Python is precisely what you need. We start with the absolute basics. We assume no prior knowledge of machine learning or quantum computing. You will not be left behind. (Please claim a bundle including "Volume 1: Getting Started"). "I have a computer science or programming background. Will I understand quantum machine learning?" - Absolutely! This book explains quantum machine learning in an accessible way, even if you are not a mathematician or a physicist. You'll find many code examples and explanations in no other book! "I'm an experienced data scientist or machine learning engineer." - The problems we solve will be familiar to you, but how we solve them will be new. The quantum algorithms we use will become an entirely new tool in your toolbox that you may not have even known existed. And yet, it's the tool you need to master if you want to keep your job in the future. "I am an expert in my field. But I don't have a Ph.D. What are my chances of becoming an expert in quantum computing?" Employers are looking for a rare mix of skills. On the one hand, they look for candidates who are experts in their field. On the other hand, they are looking for candidates with a well-equipped toolbox for machine learning with quantum computing. You are in pole position! -- What's inside this book? -- Hands-On Quantum Machine Learning With Python will make you an expert in solving combinatorial optimization problems with a quantum computer. Inside the book, we will focus on the following: Combinatorial optimization The Variational Quantum Eigensolver (VQE) Problem formulation Various solution ansatzes Running algorithms on real quantum computers Quantum error mitigation The Quantum Approximate Optimization Algorithm

Download or read book Hands On Quantum Machine Learning With Python written by Frank Zickert and published by Independently Published. This book was released on 2021-06-19 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: You're interested in quantum computing and machine learning. But you don't know how to get started? Let me help! Whether you just get started with quantum computing and machine learning or you're already a senior machine learning engineer, Hands-On Quantum Machine Learning With Python is your comprehensive guide to get started with Quantum Machine Learning - the use of quantum computing for the computation of machine learning algorithms. Quantum computing promises to solve problems intractable with current computing technologies. But is it fundamentally different and asks us to change the way we think. Hands-On Quantum Machine Learning With Python strives to be the perfect balance between theory taught in a textbook and the actual hands-on knowledge you'll need to implement real-world solutions. Inside this book, you will learn the basics of quantum computing and machine learning in a practical and applied manner.

Download or read book Quantum Computing with Silq Programming written by Srinjoy Ganguly and published by Packt Publishing Ltd. This book was released on 2021-04-30 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the mathematics behind quantum computing and explore the high-level quantum language Silq to take your quantum programming skills to the next level Key FeaturesHarness the potential of quantum computers more effectively using SilqLearn how to solve core problems that you may face while writing quantum programsExplore useful quantum applications such as cryptography and quantum machine learningBook Description Quantum computing is a growing field, with many research projects focusing on programming quantum computers in the most efficient way possible. One of the biggest challenges faced with existing languages is that they work on low-level circuit model details and are not able to represent quantum programs accurately. Developed by researchers at ETH Zurich after analyzing languages including Q# and Qiskit, Silq is a high-level programming language that can be viewed as the C++ of quantum computers! Quantum Computing with Silq Programming helps you explore Silq and its intuitive and simple syntax to enable you to describe complex tasks with less code. This book will help you get to grips with the constructs of the Silq and show you how to write quantum programs with it. You’ll learn how to use Silq to program quantum algorithms to solve existing and complex tasks. Using quantum algorithms, you’ll also gain practical experience in useful applications such as quantum error correction, cryptography, and quantum machine learning. Finally, you’ll discover how to optimize the programming of quantum computers with the simple Silq. By the end of this Silq book, you’ll have mastered the features of Silq and be able to build efficient quantum applications independently. What you will learnIdentify the challenges that researchers face in quantum programmingUnderstand quantum computing concepts and learn how to make quantum circuitsExplore Silq programming constructs and use them to create quantum programsUse Silq to code quantum algorithms such as Grover's and Simon’sDiscover the practicalities of quantum error correction with SilqExplore useful applications such as quantum machine learning in a practical wayWho this book is for This Silq quantum computing book is for students, researchers, and scientists looking to learn quantum computing techniques and software development. Quantum computing enthusiasts who want to explore this futuristic technology will also find this book useful. Beginner-level knowledge of any programming language as well as mathematical topics such as linear algebra, probability, complex numbers, and statistics is required.

Download or read book Learn Quantum Computing with Python and IBM Q Experience written by ROBERT. LOREDO and published by . This book was released on 2020-08 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Practical Guide to Quantum Machine Learning and Quantum Optimisation written by Elias F. Combarro and published by Packt Publishing. This book was released on 2023-03-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with fully explained algorithms and ready-to-use examples that can be run on quantum simulators and actual quantum computers with this comprehensive guide Key Features: Get a solid grasp of the principles behind quantum algorithms and optimization with minimal mathematical prerequisites Learn the process of implementing the algorithms on simulators and actual quantum computers Solve real-world problems using practical examples of methods Book Description: This book provides deep coverage of modern quantum algorithms that can be used to solve real-world problems. You'll be introduced to quantum computing using a hands-on approach with minimal prerequisites. You'll discover many algorithms, tools, and methods to model optimization problems with the QUBO and Ising formalisms, and you will find out how to solve optimization problems with quantum annealing, QAOA, Grover Adaptive Search (GAS), and VQE. This book also shows you how to train quantum machine learning models, such as quantum support vector machines, quantum neural networks, and quantum generative adversarial networks. The book takes a straightforward path to help you learn about quantum algorithms, illustrating them with code that's ready to be run on quantum simulators and actual quantum computers. You'll also learn how to utilize programming frameworks such as IBM's Qiskit, Xanadu's PennyLane, and D-Wave's Leap. Through reading this book, you will not only build a solid foundation of the fundamentals of quantum computing, but you will also become familiar with a wide variety of modern quantum algorithms. Moreover, this book will give you the programming skills that will enable you to start applying quantum methods to solve practical problems right away. What You Will Learn: Review the basics of quantum computing Gain a solid understanding of modern quantum algorithms Understand how to formulate optimization problems with QUBO Solve optimization problems with quantum annealing, QAOA, GAS, and VQE Find out how to create quantum machine learning models Explore how quantum support vector machines and quantum neural networks work using Qiskit and PennyLane Discover how to implement hybrid architectures using Qiskit and PennyLane and its PyTorch interface Who this book is for: This book is for professionals from a wide variety of backgrounds, including computer scientists and programmers, engineers, physicists, chemists, and mathematicians. Basic knowledge of linear algebra and some programming skills (for instance, in Python) are assumed, although all mathematical prerequisites will be covered in the appendices.

Download or read book Programming Quantum Computers written by Eric R. Johnston and published by "O'Reilly Media, Inc.". This book was released on 2019-07-03 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum computers are poised to kick-start a new computing revolution—and you can join in right away. If you’re in software engineering, computer graphics, data science, or just an intrigued computerphile, this book provides a hands-on programmer’s guide to understanding quantum computing. Rather than labor through math and theory, you’ll work directly with examples that demonstrate this technology’s unique capabilities. Quantum computing specialists Eric Johnston, Nic Harrigan, and Mercedes Gimeno-Segovia show you how to build the skills, tools, and intuition required to write quantum programs at the center of applications. You’ll understand what quantum computers can do and learn how to identify the types of problems they can solve. This book includes three multichapter sections: Programming for a QPU—Explore core concepts for programming quantum processing units, including how to describe and manipulate qubits and how to perform quantum teleportation. QPU Primitives—Learn algorithmic primitives and techniques, including amplitude amplification, the Quantum Fourier Transform, and phase estimation. QPU Applications—Investigate how QPU primitives are used to build existing applications, including quantum search techniques and Shor’s factoring algorithm.

Download or read book Quantum Computing An Applied Approach written by Jack D. Hidary and published by Springer Nature. This book was released on 2021-09-29 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates the foundations of quantum computing with a hands-on coding approach to this emerging field; it is the first to bring these elements together in an updated manner. This work is suitable for both academic coursework and corporate technical training. The second edition includes extensive updates and revisions, both to textual content and to the code. Sections have been added on quantum machine learning, quantum error correction, Dirac notation and more. This new edition benefits from the input of the many faculty, students, corporate engineering teams, and independent readers who have used the first edition. This volume comprises three books under one cover: Part I outlines the necessary foundations of quantum computing and quantum circuits. Part II walks through the canon of quantum computing algorithms and provides code on a range of quantum computing methods in current use. Part III covers the mathematical toolkit required to master quantum computing. Additional resources include a table of operators and circuit elements and a companion GitHub site providing code and updates. Jack D. Hidary is a research scientist in quantum computing and in AI at Alphabet X, formerly Google X.

Download or read book Quantum Computing written by Eleanor G. Rieffel and published by MIT Press. This book was released on 2014-08-29 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough exposition of quantum computing and the underlying concepts of quantum physics, with explanations of the relevant mathematics and numerous examples. The combination of two of the twentieth century's most influential and revolutionary scientific theories, information theory and quantum mechanics, gave rise to a radically new view of computing and information. Quantum information processing explores the implications of using quantum mechanics instead of classical mechanics to model information and its processing. Quantum computing is not about changing the physical substrate on which computation is done from classical to quantum but about changing the notion of computation itself, at the most basic level. The fundamental unit of computation is no longer the bit but the quantum bit or qubit. This comprehensive introduction to the field offers a thorough exposition of quantum computing and the underlying concepts of quantum physics, explaining all the relevant mathematics and offering numerous examples. With its careful development of concepts and thorough explanations, the book makes quantum computing accessible to students and professionals in mathematics, computer science, and engineering. A reader with no prior knowledge of quantum physics (but with sufficient knowledge of linear algebra) will be able to gain a fluent understanding by working through the book.

Download or read book Quantum Machine Learning An Applied Approach written by Santanu Ganguly and published by Apress. This book was released on 2021-08-11 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Know how to adapt quantum computing and machine learning algorithms. This book takes you on a journey into hands-on quantum machine learning (QML) through various options available in industry and research. The first three chapters offer insights into the combination of the science of quantum mechanics and the techniques of machine learning, where concepts of classical information technology meet the power of physics. Subsequent chapters follow a systematic deep dive into various quantum machine learning algorithms, quantum optimization, applications of advanced QML algorithms (quantum k-means, quantum k-medians, quantum neural networks, etc.), qubit state preparation for specific QML algorithms, inference, polynomial Hamiltonian simulation, and more, finishing with advanced and up-to-date research areas such as quantum walks, QML via Tensor Networks, and QBoost. Hands-on exercises from open source libraries regularly used today in industry and research are included, such as Qiskit, Rigetti's Forest, D-Wave's dOcean, Google's Cirq and brand new TensorFlow Quantum, and Xanadu's PennyLane, accompanied by guided implementation instructions. Wherever applicable, the book also shares various options of accessing quantum computing and machine learning ecosystems as may be relevant to specific algorithms. The book offers a hands-on approach to the field of QML using updated libraries and algorithms in this emerging field. You will benefit from the concrete examples and understanding of tools and concepts for building intelligent systems boosted by the quantum computing ecosystem. This work leverages the author’s active research in the field and is accompanied by a constantly updated website for the book which provides all of the code examples. What You will Learn Understand and explore quantum computing and quantum machine learning, and their application in science and industry Explore various data training models utilizing quantum machine learning algorithms and Python libraries Get hands-on and familiar with applied quantum computing, including freely available cloud-based access Be familiar with techniques for training and scaling quantum neural networks Gain insight into the application of practical code examples without needing to acquire excessive machine learning theory or take a quantum mechanics deep dive Who This Book Is For Data scientists, machine learning professionals, and researchers

Download or read book Advances in Computational Intelligence written by Ignacio Rojas and published by Springer Nature. This book was released on 2023-11-03 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 14134 and LNCS 14135 constitutes the refereed proceedings of the 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, held in Ponta Delgada, Portugal, during June 19–21, 2023. The 108 full papers presented in this two-volume set were carefully reviewed and selected from 149 submissions. The papers in Part I are organized in topical sections on advanced topics in computational intelligence; advances in artificial neural networks; ANN HW-accelerators; applications of machine learning in biomedicine and healthcare; and applications of machine learning in time series analysis. The papers in Part II are organized in topical sections on deep learning and applications; deep learning applied to computer vision and robotics; general applications of artificial intelligence; interaction with neural systems in both health and disease; machine learning for 4.0 industry solutions; neural networks in chemistry and material characterization; ordinal classification; real world applications of BCI systems; and spiking neural networks: applications and algorithms.

Download or read book Quantum Information Processing and Quantum Error Correction written by Ivan Djordjevic and published by Academic Press. This book was released on 2012-04-16 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum Information Processing and Quantum Error Correction is a self-contained, tutorial-based introduction to quantum information, quantum computation, and quantum error-correction. Assuming no knowledge of quantum mechanics and written at an intuitive level suitable for the engineer, the book gives all the essential principles needed to design and implement quantum electronic and photonic circuits. Numerous examples from a wide area of application are given to show how the principles can be implemented in practice. This book is ideal for the electronics, photonics and computer engineer who requires an easy- to-understand foundation on the principles of quantum information processing and quantum error correction, together with insight into how to develop quantum electronic and photonic circuits. Readers of this book will be ready for further study in this area, and will be prepared to perform independent research. The reader completed the book will be able design the information processing circuits, stabilizer codes, Calderbank-Shor-Steane (CSS) codes, subsystem codes, topological codes and entanglement-assisted quantum error correction codes; and propose corresponding physical implementation. The reader completed the book will be proficient in quantum fault-tolerant design as well. Unique Features Unique in covering both quantum information processing and quantum error correction - everything in one book that an engineer needs to understand and implement quantum-level circuits. Gives an intuitive understanding by not assuming knowledge of quantum mechanics, thereby avoiding heavy mathematics. In-depth coverage of the design and implementation of quantum information processing and quantum error correction circuits. Provides the right balance among the quantum mechanics, quantum error correction, quantum computing and quantum communication. Dr. Djordjevic is an Assistant Professor in the Department of Electrical and Computer Engineering of College of Engineering, University of Arizona, with a joint appointment in the College of Optical Sciences. Prior to this appointment in August 2006, he was with University of Arizona, Tucson, USA (as a Research Assistant Professor); University of the West of England, Bristol, UK; University of Bristol, Bristol, UK; Tyco Telecommunications, Eatontown, USA; and National Technical University of Athens, Athens, Greece. His current research interests include optical networks, error control coding, constrained coding, coded modulation, turbo equalization, OFDM applications, and quantum error correction. He presently directs the Optical Communications Systems Laboratory (OCSL) within the ECE Department at the University of Arizona. Provides everything an engineer needs in one tutorial-based introduction to understand and implement quantum-level circuits Avoids the heavy use of mathematics by not assuming the previous knowledge of quantum mechanics Provides in-depth coverage of the design and implementation of quantum information processing and quantum error correction circuits

Download or read book Quantum Information Processing with Diamond written by Steven Prawer and published by Elsevier. This book was released on 2014-05-12 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diamond nitrogen vacancy (NV) color centers can transform quantum information science into practical quantum information technology, including fast, safe computing. Quantum Information Processing with Diamond looks at the principles of quantum information science, diamond materials, and their applications. Part one provides an introduction to quantum information processing using diamond, as well as its principles and fabrication techniques. Part two outlines experimental demonstrations of quantum information processing using diamond, and the emerging applications of diamond for quantum information science. It contains chapters on quantum key distribution, quantum microscopy, the hybridization of quantum systems, and building quantum optical devices. Part three outlines promising directions and future trends in diamond technologies for quantum information processing and sensing. Quantum Information Processing with Diamond is a key reference for R&D managers in industrial sectors such as conventional electronics, communication engineering, computer science, biotechnology, quantum optics, quantum mechanics, quantum computing, quantum cryptology, and nanotechnology, as well as academics in physics, chemistry, biology, and engineering. Brings together the topics of diamond and quantum information processing Looks at applications such as quantum computing, neural circuits, and in vivo monitoring of processes at the molecular scale

Download or read book Quantum Computing in Practice with Qiskit and IBM Quantum Experience written by Hassi Norlén and published by Packt Publishing Ltd. This book was released on 2020-11-23 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the nuances of programming traditional quantum computers and solve the challenges of the future while building and executing quantum programs on IBM Quantum hardware and simulators Key FeaturesWork your way up from writing a simple quantum program to programming complex quantum algorithmsExplore the probabilistic nature of qubits by performing quantum coin tosses and using random number generatorsDelve into quantum algorithms and their practical applications in various domainsBook Description IBM Quantum Experience® is a leading platform for programming quantum computers and implementing quantum solutions directly on the cloud. This book will help you get up to speed with programming quantum computers and provide solutions to the most common problems and challenges. You’ll start with a high-level overview of IBM Quantum Experience® and Qiskit®, where you will perform the installation while writing some basic quantum programs. This introduction puts less emphasis on the theoretical framework and more emphasis on recent developments such as Shor’s algorithm and Grover’s algorithm. Next, you’ll delve into Qiskit®, a quantum information science toolkit, and its constituent packages such as Terra, Aer, Ignis, and Aqua. You’ll cover these packages in detail, exploring their benefits and use cases. Later, you’ll discover various quantum gates that Qiskit® offers and even deconstruct a quantum program with their help, before going on to compare Noisy Intermediate-Scale Quantum (NISQ) and Universal Fault-Tolerant quantum computing using simulators and actual hardware. Finally, you’ll explore quantum algorithms and understand how they differ from classical algorithms, along with learning how to use pre-packaged algorithms in Qiskit® Aqua. By the end of this quantum computing book, you’ll be able to build and execute your own quantum programs using IBM Quantum Experience® and Qiskit® with Python. What you will learnVisualize a qubit in Python and understand the concept of superpositionInstall a local Qiskit® simulator and connect to actual quantum hardwareCompose quantum programs at the level of circuits using Qiskit® TerraCompare and contrast Noisy Intermediate-Scale Quantum computing (NISQ) and Universal Fault-Tolerant quantum computing using simulators and IBM Quantum® hardwareMitigate noise in quantum circuits and systems using Qiskit® IgnisUnderstand the difference between classical and quantum algorithms by implementing Grover’s algorithm in Qiskit®Who this book is for This book is for developers, data scientists, machine learning researchers, or quantum computing enthusiasts who want to understand how to use IBM Quantum Experience® and Qiskit® to implement quantum solutions and gain practical quantum computing experience. Python programming experience is a must to grasp the concepts covered in the book more effectively. Basic knowledge of quantum computing will also be beneficial.