Quantum Programming In Depth
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Quantum Programming in Depth
Author: Mariia Mykhailova
language: en
Publisher: Simon and Schuster
Release Date: 2025-07-29
Go beyond the basics with this in-depth guide to quantum programming. Here’s something you already know: quantum computing is a deep subject. Quantum Programming in Depth takes you beyond quantum basics and shows you how to take on practical quantum problem solving and programming using Q# and Qiskit. Author Mariia Mykhailova, a principal quantum applications software developer at PsiQuantum, guides you every step of the way. In Quantum Programming in Depth you’ll explore: • Algorithms to solve challenging quantum computing problems • Writing quantum programs with Q# and Qiskit • Testing quantum programs with simulators and specialized tools • Evaluating performance of quantum programs on future fault-tolerant quantum computers Quantum Programming in Depth shows you how to do quantum computing outside the lab or classroom, presenting problems of quantum programming and demonstrating how they’re solved. You’ll learn to write quantum programs using Qiskit and Q#—and even how to test your quantum code using common testing tools like pytest. You’ll learn to prepare quantum states and implement operations, extract information from quantum states and operations, evaluate classical functions on a quantum computer, solve search problems, and more. About the Technology Going from the basic quantum concepts to developing software for quantum computers can be difficult! Algorithms that leverage quantum phenomena require new ways of thinking about computation and new approaches to writing code, testing it, and evaluating its performance. This book bridges the gap between QC theory and quantum programming in practice. About the Book Quantum Programming in Depth shows you how to solve quantum computing problems in a programmer-friendly way. The book’s hands-on project-based approach will hone your quantum skills using realistic problems and progressively harder programming challenges. As you read, you’ll design quantum algorithms and explore their performance on future fault-tolerant quantum computers. What’s Inside • Solve challenging quantum computing problems • Write quantum programs with Q# and Qiskit • Test quantum programs • Evaluate performance of quantum programs About the Readers For students and software engineers who know Python and the basic concepts of quantum computing. About the Author Mariia Mykhailova is a principal quantum applications software developer at PsiQuantum. Table of Contents 1 Quantum computing: The hype and the promise Part 1 2 Preparing quantum states 3 Implementing quantum operations Part 2 4 Analyzing quantum states 5 Analyzing quantum operations Part 3 6 Evaluating classical functions on a quantum computer 7 Grover’s search algorithm 8 Solving N queens puzzle using Grover’s algorithm 9 Evaluating the performance of quantum algorithms A Setting up your environment Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
Applied Artificial Intelligence for Drug Discovery
The integration of artificial intelligence (AI) into pharmaceutical research has redefined the landscape of drug discovery, enabling unprecedented advances across data integration, molecular design, clinical translation, and therapeutic innovation. Applied Artificial Intelligence for Drug Discovery is a comprehensive and forward-looking volume that explores how AI, machine learning (ML), and deep learning (DL) are revolutionizing the discovery and development of new drugs. Spanning 27 chapters authored by leading international experts, this book presents state-of-the-art methods and practical applications covering the entire drug discovery pipeline. Topics include AI-based drug target identification, pathway analysis, structure- and ligand-based drug design, generative models for de novo design, peptide discovery, ADMET prediction, retrosynthesis, drug repurposing, and nanomedicine. Dedicated chapters focus on the implementation of large language models, contrastive and few-shot learning, quantum machine learning, federated and explainable AI, and clinical trial optimization. With its balance of foundational theory, applied case studies, and emerging perspectives, the book offers a unique resource for computational chemists, pharmaceutical scientists, bioinformaticians, data scientists, and R&D professionals. This volume serves not only as a scientific reference but also as a strategic guide for those looking to adopt AI in pharmaceutical pipelines and therapeutic development. It is equally suited for academic researchers and industrial innovators seeking to unlock the full potential of AI in healthcare.
Information Security Applications
This book constitutes the revised selected papers from the 23rd International Conference on Information Security Applications, WISA 2022, which took place on Jeju Island, South Korea, during August 2022. The 25 papers included in this book were carefully reviewed and selected from 76 submissions. They were organized in topical sections as follows: network security; cryptography; vulnerability analysis; privacy enhancing technique; security management; security engineering.