Below is our 2026 shortlist of the best quantum computing books, twelve titles selected for genuine usefulness rather than Amazon ranking. Each entry is a real recommendation, picked from the best quantum computing books we have actually read and worked through. This is the master list of quantum computing books on Quantum Zeitgeist, a curated, opinionated guide to the books worth your time, organised by what you actually want to do with them. We have read every book here; the recommendations are not affiliate-driven filler. Each entry tells you the level, the prerequisites, and the use case, with deeper reviews linked where they exist.
Disclosure: book links go to Amazon and we may earn a small commission if you buy through them. Updated for 2026.
Pick from our best quantum computing books by what you want to do
| Your goal | Start with | Why |
|---|---|---|
| Understand quantum computing without maths | Bernhardt, Quantum Computing for Everyone | Most genuinely accessible book in the field. |
| Build intuition with some maths | Susskind & Friedman, The Theoretical Minimum | A working physicist’s intuition, taught patiently. |
| Learn properly as an undergraduate | Rieffel & Polak, A Gentle Introduction | Mathematically honest, well-paced, the CS-department standard. |
| Reach research level | Nielsen & Chuang, Quantum Computation and Quantum Information | The “bible” of the field. Twenty years on, still the standard reference. |
| Specialise in quantum information theory | Wilde, Quantum Information Theory | The most rigorous modern treatment. Free PDF on the author’s site. |
| Cross over from machine learning | Wittek, Quantum Machine Learning | The book that opened the QC↔ML bridge. Still the right starting point. |
| Read for intellectual fun | Aaronson, Quantum Computing since Democritus | One of the sharpest minds in the field, in his own voice. |
| Engage with the philosophy | Deutsch, The Fabric of Reality | The multiverse case from the inventor of universal quantum computation. |
| Read about quantum mechanics 2.0 | Davies, Quantum 2.0 | Veteran science writer on the next quantum revolution. |
| Use a 2026 textbook with worked examples | Herbert, Quantum Computing: Foundations and Practice | OUP textbook from a Cambridge/Quantinuum author, full of solved problems. |
Quantum Computing: Foundations and Practice by Steven Herbert
Level: Advanced undergraduate to early graduate, with maths
Steven Herbert is an affiliated lecturer at Cambridge in computer science and Head of Quantum Algorithms at Quantinuum, the full-stack company that emerged from Cambridge Quantum Computing’s merger with Honeywell’s quantum division. That dual perspective shows in this 2026 OUP textbook: complexity theory runs through the entire book rather than being parked in one chapter, every standard algorithm (Grover, Shor, HHL) gets worked examples and end-of-chapter problems with answers, and the adiabatic-optimisation chapter is one of the better treatments of near-term quantum that we have read.
If you want a serious, current, working textbook that you can read at multiple levels of mathematical depth, this is the right pick from the 2026 crop. References feel current, the error-correction chapter is well done, and you can actually use the book to test yourself against the material.
Read our full review of Quantum Computing: Foundations and Practice.
Twelve featured books: our best quantum computing books for 2026, reviewed
Quantum Computing for Everyone by Chris Bernhardt
Level: Beginner, no math required
The most genuinely accessible book on this list. Bernhardt, a maths professor with a real gift for plain-English explanation, assumes nothing and builds quantum computing up from scratch using nothing more than vectors, dot products, and matrices. By the end of the book you have actually learned how a Bell state, a CNOT, and Shor’s algorithm work, without ever feeling lost.
If you have read pop-science books on quantum computing and felt that they kept stopping just before the interesting bit, this is the book that does not stop. It is the right starting point for anyone who is technically inclined but does not want to wade through a physics textbook first.
Quantum Mechanics: The Theoretical Minimum by Leonard Susskind & Art Friedman
Level: Curious reader with some maths
Susskind is one of the founders of string theory and one of the great living lecturers in physics. Here he and Friedman walk you through quantum mechanics itself, not quantum computing, at the level a working physicist actually thinks at, but with all the workings shown. State vectors, Hermitian operators, eigenvalues, and entanglement are all introduced cleanly and intuitively.
Pair this with one of the quantum-computing-specific books below and you will have the strongest foundation possible: real intuition for the underlying physics, then the algorithmic layer on top. Required reading if you want to actually understand quantum computing rather than just describe it.
Quantum Computing: A Gentle Introduction by Eleanor Rieffel & Wolfgang Polak
Level: Undergraduate / mathematically literate
The textbook most computer-science departments use as a first formal introduction to quantum computing. Rieffel and Polak are computer scientists by training, and the book reflects that, quantum mechanics is introduced as the minimal mathematical machinery needed, then the focus shifts straight to circuits, algorithms, and complexity classes.
It is mathematically honest without being intimidating, and the treatment of quantum complexity theory and quantum algorithms is the clearest you will find at this level. The right next book once Bernhardt or Susskind has set you up.
Quantum Computation and Quantum Information by Michael A. Nielsen & Isaac L. Chuang
Level: Graduate / serious researcher
The “Mike and Ike”, the textbook every serious quantum computing researcher cites and most have on their desk. Two decades after publication it is still the standard reference for everything from quantum algorithms and information theory to error correction and physical implementations.
It is dense, rigorous, and not a casual read. But if you intend to do graduate work, contribute to research, or build an honest mental model of why quantum computing works the way it does, this is the book you need to own. The chapters on quantum error correction and stabiliser codes have aged especially well.
Quantum Information Theory by Mark M. Wilde
Level: Specialist, quantum information theory
The most rigorous modern treatment of quantum information theory available, and freely downloadable as a PDF from the author’s website if you want to try before you buy. Wilde covers classical and quantum Shannon theory side by side, then builds up to the full apparatus of channel capacities, entanglement-assisted communication, and quantum coding theorems.
Specialist material, this is not a first book, but it is the canonical reference if your work touches quantum communication, quantum networks, or the information-theoretic side of quantum computing.
Quantum Machine Learning by Peter Wittek
Level: Specialist, ML / data science crossover
The book that opened the bridge between quantum computing and machine learning, written by the late Peter Wittek before his disappearance in 2019. Wittek covers quantum-enhanced versions of classical ML algorithms, quantum support vector machines, quantum neural networks, quantum k-means, alongside the underlying quantum subroutines (HHL, amplitude amplification, quantum random walks) that make them work.
The field has moved on since 2014 and modern quantum-ML research is more cautious about claimed speed-ups, but Wittek’s book is still where to start: it gives you the mathematical machinery to read the modern literature critically.
Quantum Computing since Democritus by Scott Aaronson
Level: Reading for fun / intellectual context
Scott Aaronson’s lecture notes turned into a book, funny, opinionated, technically serious, and unlike anything else on this list. It is a tour of computational complexity, the foundations of quantum mechanics, the simulation argument, free will, and almost everything else Aaronson finds interesting, all in a voice that is unmistakably his.
Read it for context and intellectual fun rather than as a textbook. Aaronson is one of the sharpest people working in quantum complexity theory, and seeing the field through his eyes is genuinely valuable. It is the only book on this list that you might read straight through for pleasure.
The Fabric of Reality by David Deutsch
Level: Reading for the philosophical case
Written by the inventor of the universal quantum computer himself, this is the book where Deutsch makes his full case for the many-worlds interpretation of quantum mechanics, and argues that quantum computing actually demonstrates the existence of the multiverse. Even readers who reject that conclusion will find the argument worth engaging with.
It is also the clearest statement of why Deutsch built the quantum-Turing-machine framework in the first place. Pair it with our simulation theory guide for the broader conversation about computation, reality, and quantum mechanics.
Quantum 2.0 by Paul Davies
Level: General reader, no maths required
Paul Davies is one of the best science writers of the last forty years, and Quantum 2.0 is his attempt to explain what is genuinely new about the second quantum revolution, the move from quantum mechanics as a description of nature to quantum mechanics as an engineering substrate. He covers entanglement, decoherence, quantum information, and the move into quantum computing without losing the lay reader and without empty hand-waving.
If you want a single, well-written non-mathematical book to make sense of why quantum is suddenly everywhere, this is it. It complements Bernhardt at the technical end and Aaronson at the philosophical end, sitting comfortably between them as the popular-science onboarding for the field.
Read our full review of Quantum 2.0.
Quantum Computing for the Quantum Curious by Ciaran Hughes, Joshua Isaacson, Anastasia Perry, Ranbel F. Sun & Jessica C. Turner
Level: High-school / very early undergraduate
An open-access book co-developed by Fermilab physicists and physics teachers, designed specifically to bring quantum computing to high-school students. The treatment is unusually careful: every concept is explained twice, once intuitively and once mathematically, with worked exercises throughout.
If you are an educator looking for material to teach quantum computing in a classroom, this is the right starting point. It is also a good gift for a mathematically able teenager who wants to know what the fuss is about.
Quantum Computer Science: An Introduction by N. David Mermin
Level: Computer-science background, no physics
Mermin, a respected condensed-matter physicist, wrote this specifically for computer scientists who do not want to learn quantum mechanics first. The book strips away the physics that you do not need and presents the linear algebra and gate model with elegant clarity.
Shorter and tighter than Nielsen and Chuang, and the right introduction if your background is firmly in computer science rather than physics. Mermin’s writing is crisp throughout, every paragraph earns its place.
Deep dives, full lists by topic
- 17 Best Quantum Computing Books, the long, illustrated list. Beginner to PhD, every book reviewed with cover and verdict.
- Five Books to Master Quantum Computing, the tighter five-book curriculum, with a “by background” matrix.
- Five Books on Simulation Theory, Bostrom, Chalmers, Hoffman, Virk, and Vopson on whether reality is computation.
Programming glossaries, the working vocabulary
If you are reading these books and writing real code, the following 20-term reference cards are designed to live next to your editor:
- Top 20 Qiskit Terms, IBM’s Python quantum SDK.
- Top 20 Cirq Terms, Google Quantum AI’s Python framework.
- Top 20 Q# (Q Sharp) Terms, Microsoft’s quantum programming language.
Companion long-form guides for the best quantum computing books
- What Is Quantum Computing? The Complete Guide, the plain-English long-form explainer.
- Quantum Computing With Equations, the same ground covered with the maths visible.
Best quantum computing books: frequently asked questions
What is the best quantum computing book for beginners?
For someone who wants to understand quantum computing without learning physics first, the strongest single recommendation is Quantum Computing for Everyone by Chris Bernhardt, it builds the entire subject from scratch using only basic linear algebra. If you are willing to invest some time in the underlying physics, pair Bernhardt with Quantum Mechanics: The Theoretical Minimum by Leonard Susskind and Art Friedman. Together they will take you from zero to genuinely understanding what a qubit, a Bell state, and Shor’s algorithm are.
Do I need a physics background to learn quantum computing?
No. Quantum computing can be approached from a computer-science angle without ever taking a physics course. Quantum Computer Science by N. David Mermin and Quantum Computing for Computer Scientists by Yanofsky and Mannucci are both written specifically for that path. You will need comfort with linear algebra (vectors, matrices, eigenvalues, complex numbers), but not quantum mechanics in the textbook-physics sense.
What is the best quantum computing book for graduate students?
Quantum Computation and Quantum Information by Nielsen and Chuang is the standard graduate-level reference. It has been the canonical textbook for over twenty years and still is. For specialised graduate work in quantum information theory specifically, Quantum Information Theory by Mark Wilde is the most rigorous modern treatment available, and it is free as a PDF on the author’s website.
Is Nielsen and Chuang still relevant in 2026?
Yes. The fundamentals, qubits, gates, circuits, complexity classes, error-correcting codes, and the basic algorithms, have not changed since 2000. Where Nielsen and Chuang shows its age is in the practical sections on physical implementations (NMR-heavy) and on what hardware exists today. For the modern hardware story, supplement with our Complete Guide to Quantum Computing. But for the conceptual core, Nielsen and Chuang remains the standard reference.
What books cover quantum machine learning?
Quantum Machine Learning by the late Peter Wittek is the foundational text and still the right place to start. It covers quantum versions of classical ML algorithms, quantum support vector machines, quantum neural networks, quantum k-means, together with the underlying quantum subroutines (HHL, amplitude amplification) that power them. Modern research has become more cautious about claimed speed-ups, but Wittek gives you the mathematical machinery to read the recent literature critically.
Are there free quantum computing textbooks?
Yes, several. Mark Wilde’s Quantum Information Theory is freely downloadable as a PDF from the author’s site. The IBM Qiskit textbook is an excellent free online resource for learning quantum computing through code. Quantum Computing for the Quantum Curious by Hughes and colleagues is open-access and designed for high-school and early-undergraduate readers. Scott Aaronson’s lecture notes that became Quantum Computing since Democritus are also still freely available online.
Should I read a book or just use tutorials?
Both. Tutorials and notebook-based courses are excellent for getting code running and seeing quantum algorithms in action. Books give you the structure and the mental model that lets you actually understand what you are doing. Our recommendation: start with one of the introductory books (Bernhardt or Susskind), work through the IBM Qiskit textbook in parallel, and keep Nielsen and Chuang on the desk as a reference.
Outside this list: for community recommendations beyond what we cover here, see Goodreads’ community-voted shelf of the best quantum computing books, and the Amazon search results for the best quantum computing books for current pricing and availability.
A note on how we choose the best quantum computing books
Quantum computing books fall into three buckets: pop-science (often beautifully written but mathematically empty), textbooks (mathematically honest but often too dense to read for pleasure), and the rare middle tier that takes the maths seriously without losing the reader. We weight that middle tier heavily here. We do not include books that we find under-edited, hype-driven, or AI-assembled, however well they happen to rank on Amazon. If you think we have missed one, tell us, we read every recommendation.
If you would prefer to ground your reading in the field’s historical arc first, our long-form history of quantum computing covers the Feynman/Manin origins, the algorithm decade, the rise of NISQ, and the current logical-qubit race, and tells you which of these books map onto which era.
