Building Quantum Software in Python: A developer's guide 310263

Код товару: 310263Паперова книга
A developer-centric look at quantum computing.

The demand for developers who can implement solutions with quantum resources is growing larger every day. Building Quantum Software with Python gives you the foundation you need to build the software for the quantum age, and apply quantum computing to real-world business and research problems.

In Building Quantum Software with Python you will learn about:
  • Quantum states, gates, and circuits
  • A practical introduction to quantum algorithms
  • Running quantum software on classical simulators and quantum hardware
  • Quantum search, phase estimation, and quantum counting
  • Quantum solutions to optimization problems
Building Quantum Software with Python lays out the math and programming techniques you’ll need to apply quantum solutions to real challenges like sampling from classically intractable probability distributions and large-scale optimization problems. You will learn which quantum algorithms and patterns apply to different types of problems and how to build your first quantum applications. All the simulator code you write can be easily converted to run on real quantum hardware.

Foreword by Heather Higgins.

About the technology
Large-scale optimization problems, complex financial and scientific simulations, cryptographic calculations, and certain types of machine learning require unreasonably long times to run on classical computers. Quantum computers can perform some operations like these almost instantaneously! Don’t wait to get started. This book will prime you on quantum applications, implementations, and hybrid quantum-classic designs so you’ll be ready to join the quantum revolution.

About the book
Building Quantum Software with Python teaches you how to build working applications that run on a simulator or real quantum hardware. By relating QC to classical computing concepts you already know, this book’s intuitive visualizations and code implementations make quantum computing easy to grasp even if you don’t have a background in advanced math. As you go, you’ll discover and implement quantum techniques for truly random sampling, optimization solutions, unstructured search, and more—all using easy-to-follow Python code.

What's inside
  • Hype-free discussions of when, where, and why QC makes sense
  • Solving complex optimization problems
  • Quantum search using Grover’s Algorithm
  • Fourier transform, phase estimation, and probability distribution sampling
About the reader
For developers who know Python. No advanced math knowledge required.

About the Author
Constantin Gonciulea leads the Advanced Technology group at Wells Fargo. He holds advanced degrees in mathematics and computer science. Over the last 25 years, he has delivered major server-side, web, and mobile online banking platforms and products, and has worked in quantum computing since 2018.

Charlee Stefanski is a senior software engineer in the Advanced Technology group at Wells Fargo, where she leads the development of the internal quantum computing platform. She holds a BS from the University of Michigan and a Masters from UC Berkeley.
1'600 ₴
Купити
Monobank
до 10 платежей
от 180 ₴ / міс.
  • Нова Пошта
    Безкоштовно від 3'000,00 ₴
  • Укрпошта
    Безкоштовно від 1'000,00 ₴
  • Meest Пошта
    Безкоштовно від 3'000,00 ₴
Building Quantum Software in Python: A developers guide - фото 1
Інші книги Manning
Quantum Programming in Depth: Solving problems with Q# and Qiskit
308324
Mariia Mykhailova
2'100 ₴
Managing Machine Learning Projects: From design to deployment
276500
Simon Thompson
990 ₴
Machine Learning Algorithms in Depth
286417
Vadim Smolyakov
2'100 ₴
Evolutionary Deep Learning: Genetic algorithms and neural networks
261456
Micheal Lanham
1'400 ₴
Build a Robo-Advisor with Python (From Scratch): Automate your financial and investment decisions
310247
Rob ReiderAlex Michalka
1'400 ₴
The Well-Grounded Python Developer: How the pros use Python and Flask
246936
Doug Farrell
1'450 ₴
Math and Architectures of Deep Learning
282315
Krishnendu Chaudhury
1'400 ₴
Advanced Algorithms and Data Structures
160093
Marcello La Rocca
2'400 ₴
Rust in Action 1st Edition
276057
Tim McNamara
780 ₴
Grokking Continuous Delivery
253619
Christie Wilson
650 ₴

Характеристики

  • Бренд
  • Автор
  • Категорія
    Програмування
  • Рік
    2025
  • Сторінок
    376
  • Формат
    165х235 мм
  • Обкладинка
    М'яка
  • Тип паперу
    Офсетний
  • Мова
    Англійська
  • Ілюстрації
    Чорно-білі

Від видавця

A developer-centric look at quantum computing.

The demand for developers who can implement solutions with quantum resources is growing larger every day. Building Quantum Software with Python gives you the foundation you need to build the software for the quantum age, and apply quantum computing to real-world business and research problems.

In Building Quantum Software with Python you will learn about:
  • Quantum states, gates, and circuits
  • A practical introduction to quantum algorithms
  • Running quantum software on classical simulators and quantum hardware
  • Quantum search, phase estimation, and quantum counting
  • Quantum solutions to optimization problems
Building Quantum Software with Python lays out the math and programming techniques you’ll need to apply quantum solutions to real challenges like sampling from classically intractable probability distributions and large-scale optimization problems. You will learn which quantum algorithms and patterns apply to different types of problems and how to build your first quantum applications. All the simulator code you write can be easily converted to run on real quantum hardware.

Foreword by Heather Higgins.

About the technology
Large-scale optimization problems, complex financial and scientific simulations, cryptographic calculations, and certain types of machine learning require unreasonably long times to run on classical computers. Quantum computers can perform some operations like these almost instantaneously! Don’t wait to get started. This book will prime you on quantum applications, implementations, and hybrid quantum-classic designs so you’ll be ready to join the quantum revolution.

About the book
Building Quantum Software with Python teaches you how to build working applications that run on a simulator or real quantum hardware. By relating QC to classical computing concepts you already know, this book’s intuitive visualizations and code implementations make quantum computing easy to grasp even if you don’t have a background in advanced math. As you go, you’ll discover and implement quantum techniques for truly random sampling, optimization solutions, unstructured search, and more—all using easy-to-follow Python code.

What's inside
  • Hype-free discussions of when, where, and why QC makes sense
  • Solving complex optimization problems
  • Quantum search using Grover’s Algorithm
  • Fourier transform, phase estimation, and probability distribution sampling
About the reader
For developers who know Python. No advanced math knowledge required.

About the Author
Constantin Gonciulea leads the Advanced Technology group at Wells Fargo. He holds advanced degrees in mathematics and computer science. Over the last 25 years, he has delivered major server-side, web, and mobile online banking platforms and products, and has worked in quantum computing since 2018.

Charlee Stefanski is a senior software engineer in the Advanced Technology group at Wells Fargo, where she leads the development of the internal quantum computing platform. She holds a BS from the University of Michigan and a Masters from UC Berkeley.

Зміст

Table of Contents
Part 1
1 Advantages and challenges of programming quantum computers
2 A first look at quantum computations: The knapsack problem
3 Single-qubit states and gates
4 Quantum state and circuits: Beyond one qubit
Part 2
5 Selecting outcomes with quantum oracles
6 Quantum search and probability estimation
7 The quantum Fourier transform
8 Using the quantum Fourier transform
9 Quantum phase estimation
Part 3
10 Encoding functions in quantum states
11 Search-based quantum optimization
12 Conclusions and outlook
Appendixes
A Math refresher
B More about quantum states and gates
C Outcome pairing strategies

Відгуки про Building Quantum Software in Python: A developer's guide

Building Quantum Software in Python: A developer's guide
Building Quantum Software in Python: A developer's guide
1'600 ₴
Купити
Персонально для вас
Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition
270201
Stefan Jansen
1'450 ₴
The hitchhiker's Guide to Python: Best Practices for Development 1st Edition
67107
Kenneth Reitz
1'500 ₴
Hands-On Application Development with PyCharm - Second Edition: Build applications like a pro with the ultimate python development tool 2nd ed. Edition
282448
Bruce M. Van Horn IIQuan Nguyen
1'500 ₴
Think Bayes. Bayesian Statistics in Python 2nd Edition
154853
Allen Downey
1'600 ₴
Hands-On Microservices with Django: Build cloud-native and reactive applications with Python using Django 5
277867
Tieme Woldman
1'600 ₴
Django 5 By Example - Fifth Edition: Build powerful and reliable Python web applications from scratch 5th ed. Edition
280327
Antonio Mele
1'600 ₴
Web Development with Django - Second Edition: A definitive guide to building modern Python web applications using Django 4 2nd ed. Edition
281127
Ben ShawSaurabh BadhwarChris Guest
1'600 ₴
Python Playground, 2nd Edition: Geeky Projects for the Curious Programmer
303268
Mahesh Venkitachalam
1'600 ₴
Modern Django Web Development: With Channels, DRF, GraphQL, and React First Edition
310260
Malhar Lathkar
1'600 ₴
Using Asyncio in Python: Understanding Python's Asynchronous Programming Features 1st Edition
114647
Caleb Hattingh
1'650 ₴
Data Visualization with Python and JavaScript: Scrape, Clean, Explore & Transform Your Data 1st Edition
67148
Kyran Dale
1'496 ₴1'700 ₴
Advanced Analytics with PySpark. Patterns for Learning from Data at Scale Using Python and Spark
197692
Sandy RyzaAkash TandonUri LasersonSean Owen
1'700 ₴
Computational Mathematics: An introduction to Numerical Analysis and Scientific Computing with Python
246257
Dimitrios Mitsotakis
1'700 ₴
Learning Ray: Flexible Distributed Python for Machine Learning
246259
Max PumperlaEdward OakesRichard Liaw
1'700 ₴
FastAPI: Modern Python Web Development 1st Edition
265490
Bill Lubanovic
1'700 ₴
Web Scraping With Python: Data Extraction from the Modern Web 3rd Edition
275380
Ryan Mitchell
1'700 ₴
Mastering NLP from Foundations to LLMs: Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python
283758
Lior GazitMeysam GhaffariAsha Saxena
1'700 ₴
Django in Action
282314
Christopher Trudeau
1'400 ₴
Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications 1st Edition
292935
5/1
John BerrymanAlbert Ziegler
1'800 ₴
Kotlin Design Patterns and Best Practices - Third Edition: Elevate your Kotlin skills with classical and modern design patterns, coroutines, and microservices 3rd ed. Edition
277681
Alexey Soshin
1'960 ₴
AI and Machine Learning for On-Device Development: A Programmer's Guide. 1st Ed.
244740
Laurence Moroney
2'200 ₴
Build Your Own IoT Platform. 2nd Ed.
244668
Anand Tamboli
1'700 ₴
Think Like a Software Engineering Manager
308852
Akanksha Gupta
1'700 ₴
A Brief Introduction to Web3: Decentralized Web Fundamentals for App Development 1st ed. Edition
259268
Shashank Mohan Jain
1'300 ₴
Kubernetes: Preparing for the CKA and CKAD Certifications. 1st Ed.
244694
Philippe Martin
1'400 ₴
Pro Jakarta Persistence in Jakarta EE 10. An In-Depth Guide to Persistence in Enterprise Java Development. 4th Ed.
244722
Lukas Jungmann, Mike Keith
2'200 ₴
How Large Language Models Work
308167
Edward RaffDrew FarrisStella Biderman
1'700 ₴