Make textbooks great again
In Korea, saying “I studied from textbooks” is something of a meme. In a notoriously competitive school system where every exam score matters, students work through piles of workbooks and practice tests for each subject, often using materials available only through private tutoring centers. These are supposed to give students an edge over the textbooks everyone gets at school. So when a student who tops the college entrance exam says “I studied from textbooks” in an interview, people tend to hear one of two things: “I’m a genius” or “I’m not telling you the whole story”. More often, it’s the second.
I can imagine a near AI-powered future where “I studied from textbooks” becomes a clear sign of genius. One pessimistic possibility is that our brains will be so fried by instant chatbot responses that working through a textbook will become extremely challenging. Another is that the world will move so fast that students will either be too busy catching up or give up early on, leaving little time or energy to digest established knowledge.
It’s a hard time to be a junior researcher in the AI era. Producing research that stands out amid a flood of results generated by prompts like You can do it, bro is daunting, to say the least. Perhaps ironically, the best move in such a fast-paced landscape might be to slow down and build a solid foundation. Actually reading textbooks and appreciating ideas from half a century ago might just be the sign of genius that gives you an edge over those who produce profusely but never internalize.
I’m not being anti-AI here. I’m a huge fan of how AI is enabling unpredecedented research, and I’m deeply committed to being part of that transformation. I see this as a yin and yang situation: those who master both the discipline of internalizing fundamental knowledge and the skill of making AI-pilled progress can do great research. The two are not opposite; they are complementary, interconnected, and interdependent.
In hopes of making textbooks great again, I’m sharing a list of my favorite textbooks I read from 2016 to 2026. Obviously, I only read a few chapters from the more advanced textbooks to apply to my own research. For those of you with a better list, it would be great if this post inspires you to share your own reading list. Click the triangle for my thoughts on the book.
Even now, when AI models seem to have digested every textbook out there, the legacy of these books lives on when we take the time to understand their ideas. Only then will our orchestration of knowledge production be firmly grounded in a deep understanding of first principles. And if you ask me, textbooks are best read in print, with a pencil in hand.
General
David J. Griffiths. Introduction to Quantum Mechanics (2nd ed.).
I'm not sure if this is still a thing, but when I was an undergrad, physics nerds used to quarrel over which quantum mechanics textbook was best - Shankar, Ballentine, Sakurai, and so on. I'm team Griffiths - this book is about as friendly as it gets for confused undergraduates. Even so, it keeps a firm grip on advanced topics like atomic physics, WKB theory, Berry phase, and scattering.
L. D. Landau and E. M. Lifshitz. Mechanics.
The first 20 pages are the most compact account of the classical laws of physics. They aren't meant to be understood on the first pass, but that's why it is rewarding to grasp them after several reads over a few months. I also think Chapter 7 offers great insight for those who wonder how Heisenberg might have arrived at his formulation of quantum mechanics.
L. D. Landau and E. M. Lifshitz. Statistical Physics, Part 1.
The thing about Landau & Lifshitz textbooks (although I've only managed to read these two) is that they take great care to be precise about first principles. It's like travelling back to the origins of ideas like phase space and entropy that you usually take for granted. The first 30 pages lay out the foundations of the laws of macroscopic systems without sweeping anything under the rug.
Atomic physics & open quantum systems
Claude Cohen-Tannoudji, Jacques Dupont-Roc, and Gilbert Grynberg. Atom–Photon Interactions: Basic Processes and Applications.
This book is an encyclopedia of atomic transitions. It is humbling to think of how such deep theoretical work has sustained the marvels that atomic physics experiments give today. And this is only one of the many textbooks from Cohen-Tannoudji! Someone thinks he's satanic though.
Heinz-Peter Breuer and Francesco Petruccione. The Theory of Open Quantum Systems.
One of the struggles with math-y textbooks is getting stuck between one equation and the next because either there's an error or the authors skipped an important step they deemed trivial. This book had none of those issues and really delivered on physical and mathematical intuition. It's a pleasant experience to study the Born–Markov approximation in Chapter 3 and then move beyond it in Chapter 9.
Crispin Gardiner and Peter Zoller. Quantum Noise: A Handbook of Markovian and Non-Markovian Quantum Stochastic Methods with Applications to Quantum Optics.
It's amusing that Breuer and Petruccione's book only briefly covers the quantum Langevin equation and doesn't touch on input-output theory, while this one introduces both right at the start of the technical discussion (Chapter 3). In my opinion, this book speaks more directly to experimentalists, which is great for theorists too!
Quantum error correction (QEC)
Dan Browne. Lectures on Topological Codes and Quantum Computation (lecture notes).
Life is short. Quantum computing is already too much. When am I supposed to learn topology? Fortunately, these lecture notes help you understand why people keep bringing up homology and chain complexes in QEC research. The fundamental idea that encoding quantum information in topology can protect it from noise is just beautiful, and it also underlies today's state-of-the-art QEC demonstrations.
Daniel Gottesman. Surviving as a Quantum Computer in a Classical World (2026 draft, PDF).
Syndrome extraction for arbitrary CSS codes ({Shor, Steane, Knill}-style EC) is clearly important but rarely gets the spotlight in QEC theory. Chapter 12 gives the cleanest explanation I've seen of the three styles of error correction, all in one place. If you want to learn about the rigorous mathematical theory of fault tolerance, this is a great book to have around. Start with Chapter 10 to get to know r-filters and gadgets - you'll be seeing a lot of them.
Quantum chemistry
Attila Szabo and Neil S. Ostlund. Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory.
An absolute must-read for quantum chemistry. I felt like the authors already knew exactly where I'd get confused and wrote the textbook to give me room to think for myself without getting unnecessarily lost. The notation is carefully chosen, and the explanations are insightful. The problems are also worth solving, especially because there's a very nice solution set.
Abraham Nitzan. Chemical Dynamics in Condensed Phases: Relaxation, Transfer, and Reactions in Condensed Molecular Systems.
Electronic structure theory is cool, but if we're talking about chemistry, what about the solvent? This textbook covers the theory of chemical reactions in a realistic setting, where molecules vibrate while surrounded by a condensed-phase environment (solid or liquid). It was the only place where I could find insightful discussions on the effects of vibrational dephasing.
Others
Anthony Zee. Quantum Field Theory in a Nutshell.
This book is well known for offering the clearest explanation of Feynman's path integral. Unlike more standard textbooks such as Schwartz (which is also amazing) that start by defining field operators, this one goes straight into action. Highly recommended for anyone who wants to understand Feynman diagrams just by reading the first chapter.
Steven M. Girvin and Kun Yang. Modern Condensed Matter Physics.
I picked up this textbook in hopes of understanding the fractional quantum Hall effect (FQHE). Many would agree that FQHE has all the qualities of a beautiful theory: it offers an unexpected explanation for exotic behavior in nature that shows up so cleanly in experiments. With this textbook in hand, I'm confident that I can pretend to understand it. Perhaps adding it to this list will get me to read the other chapters one day too.
Jakob Schwichtenberg. Physics from Symmetry.
Lie algebras are so important in physics, but they're often crammed into a single lecture, which makes them hard to internalize. Sitting down with Chapter 3 of this book helps. If Lie groups, generators, and algebras make your head spin, this book will at least help you describe the rotation in the standard representation of SO(3). The side-by-side notes in the wide margins are very helpful.
G. W. Stewart and Ji-guang Sun. Matrix Perturbation Theory.
The newest addition to my textbook collection. I picked this up for my latest paper - I needed to understand how errors in matrix elements translate into errors in eigenvalues in a generalized eigenvalue problem. Along the way, I learned a lot of fundamental concepts like QR decomposition and Gershgorin theory. And this is exactly the kind of detour you can enjoy only by reading textbooks!
Michael A. Nielsen and Isaac L. Chuang. Quantum Computation and Quantum Information.
The GOAT textbook that needs no introduction. I highly recommend reading it from cover to cover if you want to do quantum research. Anything fundamental in quantum science (the Solovay–Kitaev theorem, Shor's algorithm, quantum error correction, and so much more...) is best explained in this book. Undergraduates should be legally banned from doing quantum research if they haven't gone through Chapter 4.