Quantum Computing For Computer Scientists Pdf Github
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Quantum Computing: An Applied Approach
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.
Quantum Computing in Practice with Qiskit® and IBM Quantum Experience®
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 Features Work your way up from writing a simple quantum program to programming complex quantum algorithms Explore the probabilistic nature of qubits by performing quantum coin tosses and using random number generators Delve into quantum algorithms and their practical applications in various domains Long Description IBM Quantum Experience(R) 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(R) and Qiskit(R), 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(R), 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(R) 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(R) 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(R) and Qiskit(R) with Python. What You Will Learn Visualize a qubit in Python and understand the concept of superposition Install a local Qiskit(R) simulator and connect to actual quantum hardware Compose quantum programs at the level of circuits using Qiskit(R) Terra Compare and contrast Noisy Intermediate-Scale Quantum computing (NISQ) and Universal Fault-Tolerant quantum computing using simulators and IBM Quantum(R) hardware Mitigate noise in quantum circuits and systems using Qiskit(R) Ignis Understand the difference between classical and quantum algorithms by implementing Grover's algorithm in Qiskit(R) 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(R) and Qiskit(R) 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.
Learn Quantum Computing with Python and Q#
Author: Sarah C. Kaiser
language: en
Publisher: Simon and Schuster
Release Date: 2021-07-27
Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Summary Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you’ll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft’s Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics. About the book Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft’s open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You’ll learn to apply quantum to real-world applications, such as sending secret messages and solving chemistry problems. What's inside The underlying mechanics of quantum computers Simulating qubits in Python Exploring quantum algorithms with Q# Applying quantum computing to chemistry, arithmetic, and data About the reader For software developers. No prior experience with quantum computing required. About the author Dr. Sarah Kaiser works at the Unitary Fund, a non-profit organization supporting the quantum open-source ecosystem, and is an expert in building quantum tech in the lab. Dr. Christopher Granade works in the Quantum Systems group at Microsoft, and is an expert in characterizing quantum devices. Table of Contents PART 1 GETTING STARTED WITH QUANTUM 1 Introducing quantum computing 2 Qubits: The building blocks 3 Sharing secrets with quantum key distribution 4 Nonlocal games: Working with multiple qubits 5 Nonlocal games: Implementing a multi-qubit simulator 6 Teleportation and entanglement: Moving quantum data around PART 2 PROGRAMMING QUANTUM ALGORITHMS IN Q# 7 Changing the odds: An introduction to Q# 8 What is a quantum algorithm? 9 Quantum sensing: It’s not just a phase PART 3 APPLIED QUANTUM COMPUTING 10 Solving chemistry problems with quantum computers 11 Searching with quantum computers 12 Arithmetic with quantum computers