Augment your quantum computing journey using Amazon Braket with in-depth details of how to use Braket devices, build quantum circuits, leverage quantum annealing and solve optimization problems Key Features Learn about various quantum devices and their use in solving combinatorial optimization problems Prepare your business to leverage the benefits of the future quantum speedup Implement quantum computing concepts through real-world optimization use cases Book DescriptionAmazon Braket is a cloud-based pay-per-use platform for executing quantum algorithms on cutting-edge quantum computers and simulators. It is ideal for developing robust apps with the latest quantum devices. With this book, you'll take a hands-on approach to learning how to take real-world problems and run them on quantum devices. You'll begin with an introduction to the Amazon Braket platform and learn about the devices currently available on the platform, their benefits, and their purpose. Then, you'll review key quantum concepts and algorithms critical to converting real-world problems into a quantum circuit or binary quadratic model based on the appropriate device and its capability. The book also covers various optimization use cases, along with an explanation of the code. Finally, you'll work with a framework using code examples that will help to solve your use cases with quantum and quantum-inspired technologies. Later chapters cover custom-built functions and include almost 200 figures and diagrams to visualize key concepts. You’ll be able to scan the capabilities provided by Amazon Braket and explore the functions to adapt them for specific use cases. By the end of this book, you’ll have the tools to integrate your current business apps and AWS data with Amazon Braket to solve constrained and multi-objective optimization problems.What you will learn Explore the features and uses of the Amazon Braket console and components Discover the benefits of quantum computing devices available on Amazon Braket, including gate quantum computers, the annealer, and simulators Recognize which type of quantum device is the best fit for specific use cases and scaling Develop your own code from a basic set of use cases dealing with real-world optimization problems Understand the capabilities and limitations of current quantum computing technologies Explore the advanced features and API functions in Amazon Braket Who this book is for This book is for IT practitioners, architects, and developers looking to bring the power of quantum computing to their organizations. If you are a VP of IT, CIO, VP of architecture, chief architect, solution architect, actuarial fellow, or a developer already working on other AWS services such as AWS Lambda and EC2, you'll find this book useful in exploring how to leverage Amazon Braket for real-world use cases and to move your organization towards this emerging technology. Familiarity with the basics of quantum computing and Python is required.

Augment your quantum computing journey using Amazon Braket with in-depth details of how to use Braket devices, build quantum circuits, leverage quantum annealing and solve optimization problems Key Features Learn about various quantum devices and their use in solving combinatorial optimization problems Prepare your business to leverage the benefits of the future quantum speedup Implement quantum computing concepts through real-world optimization use cases Book DescriptionAmazon Braket is a cloud-based pay-per-use platform for executing quantum algorithms on cutting-edge quantum computers and simulators. It is ideal for developing robust apps with the latest quantum devices. With this book, you'll take a hands-on approach to learning how to take real-world problems and run them on quantum devices. You'll begin with an introduction to the Amazon Braket platform and learn about the devices currently available on the platform, their benefits, and their purpose. Then, you'll review key quantum concepts and algorithms critical to converting real-world problems into a quantum circuit or binary quadratic model based on the appropriate device and its capability. The book also covers various optimization use cases, along with an explanation of the code. Finally, you'll work with a framework using code examples that will help to solve your use cases with quantum and quantum-inspired technologies. Later chapters cover custom-built functions and include almost 200 figures and diagrams to visualize key concepts. You’ll be able to scan the capabilities provided by Amazon Braket and explore the functions to adapt them for specific use cases. By the end of this book, you’ll have the tools to integrate your current business apps and AWS data with Amazon Braket to solve constrained and multi-objective optimization problems.What you will learn Explore the features and uses of the Amazon Braket console and components Discover the benefits of quantum computing devices available on Amazon Braket, including gate quantum computers, the annealer, and simulators Recognize which type of quantum device is the best fit for specific use cases and scaling Develop your own code from a basic set of use cases dealing with real-world optimization problems Understand the capabilities and limitations of current quantum computing technologies Explore the advanced features and API functions in Amazon Braket Who this book is for This book is for IT practitioners, architects, and developers looking to bring the power of quantum computing to their organizations. If you are a VP of IT, CIO, VP of architecture, chief architect, solution architect, actuarial fellow, or a developer already working on other AWS services such as AWS Lambda and EC2, you'll find this book useful in exploring how to leverage Amazon Braket for real-world use cases and to move your organization towards this emerging technology. Familiarity with the basics of quantum computing and Python is required.

Achieve optimized solutions for real-world financial problems using quantum machine learning algorithms Key Features Learn to solve financial analysis problems by harnessing quantum power Unlock the benefits of quantum machine learning and its potential to solve problems Train QML to solve portfolio optimization and risk analytics problems Book DescriptionQuantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems. This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you’ll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing. By the end of this book, you’ll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.What you will learn Explore framework, model and technique deployed for Quantum Computing Understand the role of QC in financial modeling and simulations Apply Qiskit and Pennylane framework for financial modeling Build and train models using the most well-known NISQ algorithms Explore best practices for writing QML algorithms Use QML algorithms to understand and solve data mining problems Who this book is for This book is for financial practitioners, quantitative analysts, or developers; looking to bring the power of quantum computing to their organizations. This is an essential resource written for finance professionals, who want to harness the power of quantum computers for solving real-world financial problems. A basic understanding of Python, calculus, linear algebra, and quantum computing is a prerequisite.

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.

This book is an analysis of quantum computing, covering everything from its foundational principles to practical applications in the development of quantum services. It offers a technical and complex overview to provide the necessary knowledge to any researcher, scientist or developer who wants to get into service-oriented quantum computing. The field of quantum computing has evolved rapidly in recent years, with the potential to revolutionize the way we approach complex problems in various fields. This comprehensive guide covers the fundamental principles of quantum computing and its practical applications in the development of quantum services. Beyond theoretical knowledge, the book goes on to explore some of the challenges that quantum software developers face in today’s landscape. It addresses issues related to low-level abstractions and the absence of integration, deployment and quality assurance mechanisms in quantum software engineering. Also, it explores the principles of service-oriented computing applied to quantum computing, revealing architectural patterns adapted to quantum computing and discussing standardization and accessibility in this field. It also provides insight into streamlining the deployment process through a DevOps approach for continuous deployment of quantum services. This book will serve as a guide for all researchers, scientists and developers by providing them with an understanding of the current limitations and problems in quantum computing-oriented software development, and how to address them with software engineering techniques and tools applied to quantum computing.

This open access book explains the state of the art in quantum software engineering and design, independent from a specific hardware. It deals with quantum software theoretical aspects and with classical software engineering concepts like agile development approaches, validation, measurement, and deployment applied in a quantum or hybrid environment, and is complemented by a number of various industry applications. After an introductory chapter overviewing the contents of the subsequent chapters, the book is composed of three parts. It starts with a theoretical part on quantum software, as a bold declaration that quantum software theory is deep and valuable independent from the existence of specific quantum hardware. It is based upon the claim that quantum software is the more general theory subsuming classical and hybrid software system theories. The second, more extensive part deals with quantum software system and engineering design. Its quality follows from the comparison of the broad diversity of sometimes conflicting views. Moreover, the variety of approaches to design, enable the reader to make a well-pondered rational choice of preference. The book concludes with a third part, referring to multiple software applications and corresponding laboratory experiences, in order to understand their implications in practice and avoid repeating past mistakes. This book is of interest to industry professionals and researchers in academia, which are either producing or applying quantum software systems in their work or are considering their potential utility in the future. Furthermore, it also could be beneficial for practitioners already experienced with classical software engineering who desire to understand the fundamentals or possible applications of quantum software.

This book presents a set of software engineering techniques and tools to improve the productivity and assure the quality in quantum software development. Through the collaboration of the software engineering community with the quantum computing community new architectural paradigms for quantum-enabled computing systems will be anticipated and developed. The book starts with a chapter that introduces the main concepts and general foundations related to quantum computing. This is followed by a number of chapters dealing with the quantum software engineering methods and techniques. Topics like the Talavera Manifesto for quantum software engineering, frameworks for hybrid systems, formal methods for quantum software engineering, quantum software modelling languages, and reengineering for quantum software are covered in this part. A second set of chapters then deals with quantum software environments and tools, detailing platforms like QuantumPath®, Classiq as well as quantum software frameworks for deep learning. Overall, the book aims at academic researchers and practitioners involved in the creation of quantum information systems and software platforms. It is assumed that readers have a background in traditional software engineering and information systems.