M. Scully and M. S. Zubairy
A comprehensive introduction into quantum optics, perfectly suitable even for undergraduate students. After quantization of the Maxwell's equations, the book covers almost all topics which are relavant in the field, such as light-matter interaction, lasing or advanced quantum optical effects. A careful study of the book will prepare quantum-optics newcomers to do access the present-day literature, and carry out their own research.
S. Mukamel
The book provides a detailed theoretical introduction on a wide variety of topics related to basics spectroscopic experiments. Starting from a microscopic quantization of the Maxwell equations, the author introduces basic theoretical methods, needed to describe spectroscopic light-matter interaction, such as perturbation theory, phase-space methods, and the cumulant-expansion approach. Based on these methods, common spectroscopic effects and measurements are explained and carefully analyzed.
C. W. Gardiner and P. Zoller
This book approaches the charactization and control of quantum systems by a systematic introduction of essential quantum stochastic methods. While the main focus is on optical systems, the methods can also be applied to other fields of quantum physics. The book comprises Markovian and non-Markovian methods including, Langevin equations (in particular the input-output formalism), the quantum Master equations, and the stochastic Schroedinger equations. The final chapter introduce also intriguing applications of these stochastic methods to quantum control in optical networks.
M. M. Wild
This book gives a pedagogical introduction into quantum information with particular focus on quantum communication. The book is accesible even without any preexisting knowledge in the field and thus suitable for graduate students without a specified mathematical background. Nevertheless, the book is selfconsistent and provides all mathematical proofs in a rigurous fashion.
M. Hayashi
This books is a comprehense introduction into quantum information theory which covers divers topics, in particular, hyphothesis testing and quantum communication, in a mathematically elegant fashion. It is suitable for readers who have a basic understanding of quantum information and want to dive deeper into the field. A strong point of this book is the numeros exercies and their solutions, which are very helpful to develop a deeper understanding for the theoretical concepts and derivations.
H. Wiseman and G. Milburn
The authors give a comprehensive introduction into the theory of quantum measurements and feedback control, and relate it to practical experimental applications. The theoretical framework is mainly based on quantum trajecory methods, which are developed from a quantum measurement point of view. The book is well suited for researchers with basic knowledge in quantum mechanics, who aim to enter the field of quantum control.
B. L. Bernevig and T.L. Hughes
In my experiance, it is very challenging to enter the thriving field of topological insulators and superconductors for researchers with no prior experiance in this direction. This book offers a pedagogical introduction into this exciting field by carefully explaining the basic concepts, as well as the underlying mathematical and physical ideas.
L. Mandel and E. Wolf
This textbook gives an extensive introduction to all basic topics realted to classical and quantum optics. The first part is dedicated to classical optics, in particular, to coherence theory and the acurate analysis of the photo-electric effect. The second part covers in detail the mathematical framework of quantum optics, and analyzes a serious of intriguing quantum phenomena. Much attention is given to light-matter interaction, laser physics and non-linear optics.
M. A. Nielson and I. L. Chuang
Probably the best book to get a first introduction into quantum computation. Starting from a very basic introduction into quantum mechanics, the authors cover all topics related to quantum computation, such as computational complexity, computer science, quantum circuits, basic quantum algoritms, quantum error correction and fault tollerant quantum computation. Without going into too much details in each topic, thus book succeeds to give the reader more than just a basic introduction to the field. This book is perfectly suitable even for undergrate students.
J. E. Hopcraft, R. Motwani, J. D. Ullman
I thourogh understanding of classical computation is the basic requirement for scientifc working on quantum computation. This book give an introduction to the theoretical concepts of computer science. The book explains fundamental concepts to readers, who require only a fundemental understanding of logic to understand the sophisticated content. The authors successively introduce finite automata, context-free languages, and the Turing machine in a fashion such that the readers can understand advanced concepts such computational complexity classes (e.g., P and NP hard). Given the profound importance of computational science in our nowaday's life, I recommend this book even for readers who are not planing to do research in this direction.
J. C. Scott
While this is strictly speaking not a scientic textbook, but a popular science book, I strongly recommend it to everyone, who always wanted now how computers work in very simple terms. Staring from the working principle of transitors, the book explains the operation of integral computer components, such as CPUs, random-access memories, decoders, registers, flags and so on. As the book is written for non-scientists, it is also very entertaining to read while de-mystifiying computers.
E. N. Economou
This book gives a mathematical riguorous introduction to Green's functions in quantum physics. The formalism is applied to theoretically analyze conductivity in the presence of disorder. Later chapters are dedicated to Green's functions in many-body systems. This textbook is well-suited for graduate students who are interested into doing research in condensed-matter physics.
A. Altland and B. Simons
In this book, the authors give a detailed introduction into methods and phenomena of condensed-matter theory. After a through pedagogical introduction into Feynman path integrals, the books explains other basics theoretical tools such as response functions and renormalization group analysis. Special attention is given to collective phenomena, topology and non-equilibirum systems. I strongly reccommend this books to researchers, who are interested to understand the details of path integrals and Green's functions expansion.
D. A. Lidar and T. A. Brun (Editors)
This book is a collection of chapters independently written by authors who are experts in this field. Besides covering basic topics related to quantum error correction such as the Knill-Laflamme theorem, stabilizer codes, and dynamical decoupling, the books also explains more specialzied topics such as quantum convolutional codes, topological surface codes and entanglement distillation. While the chapters occasionaly lack a mutual relation, it is nevertheless a well-suited starting point to get a comprehensive overview over the field of quantum error correction.
R. S. Sutton and A.G. Barto
Reinforcement learning is a subdirection of machine learining that is deployed in the development of AlphaGo or software for selfdriving cars, besides other many intriguing prospects. This textbook provides a simple introduction into reinforcement learning which is accesible with only basic knowledge about programming, optimization, and statistics. The many exercises and projects in this books give the reader the possibility for practical appliactions of the well-explained theoretical content. One of the highlights of this book is the introduction to the algorithm of AlphaGo.
Z.-H. Zhou （周志华）
This textbook is the perfect introduction into machine learning suitable for students with only basic knowledge in linear algebra and statistics. The author introduces nearly all basics machine-learning techniques such as the support-vector machine, Bayesian learning, deep-learning and reinforcement learning. Very helpful are the numerous pseodo-codes which help the reader to quickly implement the theoretical content. This book prepares the reader to independently carry out their own machine-learning projects. After the book has been sold more than 200k in China, it is now also available in English.
J.J. Sakuari and J. Napolitano
This is the standard textbook for an introduction into quantum mechanics. Perfectly suitable for undergraduate students with only basic knowledge in linear algegra. The authors start with an illustrative explanation of fundamental concepts of quantum mechanics, explain the basic mathematical framework, and finally also introduce frequently applied computational methods. The last chapter gives a condense introduction into relativistic quantum mechanics.
C. Bishop
This textbook is an excellent introduction into the principles of pattern recognition and machine learning. It has a more theoretical focus as compared to the book of Z.-H. Zhou, with special focus on Bayesian inferences. The explanations in this book help the reader to develop a good feeling and intuitive understanding how neural networks and other machine-learning techniques work internally.