Quantum Computing: From Concepts to Code

Quantum Computing, From First Principles to Working Algorithms

Quantum computing can feel like a subject split between two worlds: the physics and mathematics that explain why it works, and the code that lets you actually try it. Andrew Glassner’s Quantum Computing: From Concepts to Code is built to connect those worlds. Published by No Starch Press in 2025, it guides readers through the foundations of quantum computation and into the algorithms that make the field more than a theoretical curiosity. 💡

Inside the Book

The book is organized into two major parts. Part I: States, Operators, and Systems establishes the core vocabulary, using a memorable opening example in Chapter 1, A Curious Deck of Cards. From there, Glassner develops the mathematical and conceptual tools needed to reason about quantum systems.

Part II: Quantum Algorithms moves from foundations to specific methods. Chapters include Deutsch–Jozsa’s algorithm and Bernstein–Vazirani’s algorithm, giving readers concrete examples of how quantum approaches are structured and why they differ from classical computation.

Why the Concepts-to-Code Approach Matters

Many introductions stop at analogy. Others jump straight into equations. This book works to make the ideas usable by carrying them toward implementation. The progression from states and operators to named algorithms helps readers see how abstract principles become procedures. If you have wondered how states, operators, and systems fit together in an actual computational framework, this is the kind of guided path that can make the subject click. ⚙️

Who Will Get the Most From It

• Programmers who want a serious, structured introduction to quantum computing
• Computer science students looking for a bridge from theory to algorithms
• Technical readers with an interest in physics, mathematics, or emerging computing models
• Practitioners who want to understand the algorithms before implementing them

A comfort with technical material will help you get the most from the journey.

About Andrew Glassner

Andrew Glassner is a distinguished research scientist at Wētā FX, where he applies computer graphics and machine learning to visual effects for film and television. He holds a PhD in computer science from the University of North Carolina at Chapel Hill and has authored books including Deep Learning: A Visual Approach. His experience as a researcher, writer, and educator shapes a voice that is precise without being intimidating. 🧠

A Clear Route Into a Demanding Field

Quantum computing rewards patience, but it also rewards a good guide. Quantum Computing: From Concepts to Code offers a thoughtful, well-organized route through the subject, from the first principles of states and operators to the algorithms that define the field’s early milestones. For readers ready to move beyond the headlines and build a real conceptual foundation, this No Starch Press title is a substantial place to begin.