Qc_book_list

I hope this repo can help those who want to self-study and explore the awesome of quantum computing.

if any resources link having Copyright / License / Issues please post a new issue.

few points to address:

1. please support the author, those pdf are open access by universities, authors, or organizations.
2. welcome open a new issue or a new pull request for books suggestion, please read CONTRIBUTING.md.
3. I only recommend those stand-out books, you can read with the order.

check my stars learning resources and library

Contents

• 🆕New to CS and QC
• 🆕New to QC
• 💪Good Exercise
• 🎓Certificate
• 🧐General background to proceed intermediate and advanced level
• 🤔Intermediate level
• 🤯Advanced level
• ⚛️Quantum chemistry
• 🤖Quantum machine learning
• 🔒Quantum cryptography
• 🎨Quantum music and art
• 🎮 Quantum game
• 📚Cool software sources
• 🔥Current hot research
• 🔍Other awesome resources

🆕💻🧮 new to cs and QC(all-in-one, pre-require math):

• Qiskit Textbook by qiskit contributor, keep on updating and having much friendly introduction content, in high school math.
• Lecture notes by John Watrous, contains most of the deep-level content of quantum computing.

🆕💻 new to quantum computing:

• Dancing with qubits by Robert S. Sutor, introduction concept from basic math.
• Introduction to Classical and Quantum Computing by Thomas Wong, is a super introduction book that explains basic Classical computing to Quantum computing.
• Quantum Computing: An Applied Approach -Springer (2021) by Hidary, Jack D., talks about the foundation and tools you need for QC.
• Quantum computing since Democritus -Cambridge University Press (2013) by Aaronson, Scott, talks about popular science.
• Medium article - Preliminary Thoughts on Fault-Tolerant Quantum Computing, Quantum Error Correction, and Logical Qubits by Jack Krupansky, answering a list of good questions and thoughts.

💪 Good Exercise:

• Xanadu Quantum Codebook by Catalina Albornoz, Guillermo Alonso, Mikhail Andrenkov, and more. it is a fantastic codebook that gives you a good basic understanding of quantum computing, you should go over it before going for more exercise or content, if you get stuck hard check the walkthrough from Owen Lockwood.
• IBM Quantum Challenge by the qiskit community, each year has a different topic, where you can learn more about quantum computing, if you need help, go to qiskit slack, each challenge has different channels, where you can search for previous hints or questions asked.
• QOSF Monthly Challenges by qosf contributor, contains a lot of challenges and interesting topics in quantum computing.

🎓 Certificate:

• IBM Certified Associate Developer - Quantum Computation using Qiskit v0.2X, you can find all kinds of exam related resources and information from qiskit slack channel #qiskit-cert-exam, this certificate proven yourself able to demonstrates fundamental knowledge of quantum computing concepts and is able to express them using the qiskit open sources SDK. This also open opportunity for you to join qiskit-advocate.

🧐 General background to proceed intermediate and advanced level (click me for more comprehensive guide):

Quantum computing (theory) is at the intersection of math, physics, and computer science. (Experiment also can involve electrical engineering.) Eventually, you will want to learn aspects of all of these fields, but when starting you can use any for an entry into the field. Within each field, the subjects you will want to know are:

• Physics: First learn quantum mechanics. At more advanced levels, various aspects of quantum information overlap with AMO, condensed matter, and high energy.
• Math: First linear algebra and probability. Later my preferences would be to learn some group and representation theory, random matrix theory, and functional analysis, but eventually, most fields of math overlap with quantum information, and other researchers may emphasize different areas of math.
• Computer Science: Most theory topics are relevant although are less crucial at first: i.e. algorithms, cryptography, information theory, error-correcting codes, optimization, complexity, and machine learning. If you haven't had any CS theory exposure, undergrad algorithms are a good place to start because they will show you CS-theory ways of thinking, including ideas like the asymptotic analysis.

🤔 intermediate level:

• 2020 Qiskit Global Summer School on Quantum Computing and Quantum Hardware by qiskit team, it introduce the key quantum algorithms and thier implementations using quantum circuits, as well as the quantum hardware is designed o run these algorihtms.
• Quantum computer science an introduction-Cambridge University Press (2007) by N. David Mermin, you will learn what quantum computer doing, and why is it important.
• Introduction to Quantum Mechanics by David J. Griffiths, Darrell F. Schroeter, a good introduction to QM.
• Quantum Computation and Quantum Information_ 10th Anniversary Edition-Cambridge University Press (2011) by Michael A. Nielsen, Isaac L. Chuang, the bible of quantum computing.
• Picturing Quantum Processes Cambridge University Press by B Coecke, explain quantum processing with diagrammatic language.
• Lecture Notes on Quantum Algorithms by Andrew Childs, explain deeper broader into quantum algorithms.

🤯 advanced level:

• Modern Quantum Mechanics (2nd Edition) 2nd Edition by J. J. Sakurai, Jim J. Napolitano, talks about the important concepts that use in QC.
• Principles of Quantum Mechanics by Ramamurti Shankar, it goes deeper into QM, instead of introduction.
• The Mathematics of Entanglement by Brandao, Christandl, Walter, and Aram Harrow. Idiosyncratic and incomplete lecture notes on some of mit pet topics.
• The Theory of Open Quantum Systems by Heinz-Peter Breuer, Francesco Petruccione, it explains deeper into how quantum computing work. lecture note by Daniel A. Lidar
• Alice and Bob Meet Banach: The Interface of Asymptotic Geometric Analysis and Quantum Information Theory (Mathematical Surveys and Monographs) by Guillaume Aubrun, Stanislaw J. Szarek, use math like asymptotic geometric analysis(AGA) to explain quantum information theory.
• Quantum Information Theory by Mark Wilde, is a more theoretical aspect.
• The Theory of Quantum Information by John Watrous, is focused on math and proof of the theory.
• The Functional Analysis of Quantum Information Theory - a collection of notes based on lectures by Gilles Pisier, K. R. Parthasarathy, Vern Paulsen, and Andreas Winter, it dives deeper into theory with math.
• Circuit_QED_Superconducting_Qubits_Coupled_to_Microwave_Photons by Steven M. Girvin, it is experiment physics book of superconducting computing.
• Introduction to Elementary Particles 2nd Edition by David Griffiths, it is for advanced undergraduates who are majoring in physics.

⚛️ Quantum chemistry:

• 2022 Qiskit global summer school on quantum simulation by group of experts and the qiskit team, it is a 2-week intensive summer school teach a brief introduction and overview of quantum simulation from basics to Quantum dynamics.
• Quantum Chemistry in the Age of Quantum Computing by Yudong Cao, Jonathan Romero, etc. introduction of quantum chemistry from history.
• Emerging quantum computing algorithms for quantum chemistry by Mario Motta, Julia Rice, brief introduction of computing algorithms for quantum chemistry.
• Quantum Chemistry Seven Edition by Ira N. Levine.

🤖 Quantum machine learning:

• 2021 Qiskit Global Summer School on Quantum Machine Learning by a group of experts and the qiskit team, it teaches from fundamental quantum computing to important concepts of quantum computing, and qiskit machine learning textbook for more.
• pennylane guide good comprehensive guide to the quantum concept of quantum machine learning.
• Quantum algorithms for data analysis by contributors, it contains a brief content introduction to the basic quantum algorithm to machine learning with a lot of math, and it accepts the suggestion and keeps on update.
• QML guide brief content of quantum machine learning resources.
• Awesome Quantum Machine Learning contain a very clear explanation of most of the areas in quantum machine learning, from basic quantum computing and math concepts to other complex ideas.

🔒 Quantum cryptography:

my list of quantum-cryptography repo stars

• Practical introduction to quantum-safe cryptography a course from IBM quantum, specifically designed for both expert and non-expert developers who want to learn about how quantum computing poses a risk to existing cryptography as new quantum algorithms are able break existing encryption schemes.
• Awesome-post-quantum contain a curated list of resources about post-quantum cryptography.

🎶🎨 Quantum music and art:

• Quantum music playground Playground for composing music using quantum states. Implemented as a Max for Live device in Ableton Live 11, and includes a MicroQiskit quantum simulator. Free, open source, Apache 2.0 licensed. Developed by James L. Weaver, @JavaFXpert on Twitter.
• There’s A Burgeoning Quantum Art Scene This article briefly conclude the possibilities of quantum art, by Russell Huffman, and there is lots of creative art work project can be found in his medium.
• Quantum fractals its explain some moethod to visualizing Quantum Computing using fractals, infinitely complex patterns that are self-similar across different scales, by Wiktor Mazin, Principal Data Scientist and IBM Quantum Ambassador.

🎮 Quantum game

• Awesome Quantum Games by Junyu Huang, contain a list of game that contain the component of quantum mechanics, help to learn quantum computing quickly.
• List of Quantum Games by kiedos, contain a list of games including categories.

💻🔍📚 Cool software sources:

• Quantum Open Source Foundation organization that supporting the development and standardization of open tools for quantum computing. Where you can find learning resources, list of open sources quantum software, qosf mentorship information which any background with related experience can join and more.
• Open Sources Physics provides curriculum resources that engage students in physics, computation, and computer modeling. Computational physics and computer modeling provide students with new ways to understand, describe, explain, and predict physical phenomena. even though its a very old website, but its worth to explore, if you interest in physics, where you can find useful resources and cool simulation.

🔥 If you want to see what research is currently hot, you can take a look:

• QIP workshops
• check the most cited papers
• Qiskit Seminar
• Qutech seminar
• Quantum Computer System Lecture Series
• Fact based insight
• Quantum youtube channels

🔍 Other awesome resources:

• Quantum-Computing-Collection-Of-Resources
• Awesome Quantum Computing
• quantum-resource-list
• polarization
• Open-Source Quantum Software Projects
• Explore different encyclopedia:
  • Quantum Algorithm Zoo
  • Quantum Protocol Zoo
  • Qubit Zoo
• Careers in Quantum
• Musty Thoughts
• Quantum Grad
• The Quantum Classroom

🤝 Contributing

please read CONTRIBUTING.md

📜 License