CMSC 657 Introduction to Quantum Information Processing, Fall 2018

Course Description

Quantum computers have the potential to efficiently solve problems that are intractable for classical computers. This course will explore the foundation of quantum computing. As this is a multidisciplinary subject, the course will cover basic concepts in theoretical computer science and physics in addition to introducing core quantum computing topics. No previous background in quantum mechanics is required.

Tentative topics include: quantum mechanics of qubits; quantum entanglement; quantum protocols; quantum circuits and universality; simple quantum algorithms; quantum Fourier transform; Shor factoring algorithm; Grover search algorithm and its optimality; quantum complexity theory; selected additional topics as time permits.

Quantum Computers Animated!

New Lecture Notes from this course

• Quantum Interactive Proofs and QIP=PSPACE

• Quantum Algorithms for Linear Equation Systems

• Quantum Algorithms for Semidefinite Programs

Course Project Showcase

• A Survey Towards the Verification of Quantum Parallel Programs by Yusuf Alnawakhtha and Corbin McNeill.

• The Black Hole Information Paradox by Stefano Antonini, John Martyn, and Gautam Nambiar.

• Quantum Random Walks on Cayley Graphs by Marina Knittel and Roozbeh Bassirian.

• Quantum Error Correction by Aaron Somoroff, Ray Mencia, and Ron Belyansky.

• Representation of Quantum Images by Matt Harding and Aman Geetey.

• A Survey on Quantum Machine Learning by Turan Kaan Elgin, Yiming Huang, and Venkatraman Narayanan.

• Quantum Algorithms for Optimization by Ali Rad, Nhung Nguyen, and Sohitri Ghosh.

• Quantum Improvements to Existing Cryptanalytic Techniques Against Symmetric Key Encryption Schemes by Yaelle Goldschlag and Daniel McVicker.

• Can Quantum Computers Overheat? by Wade Hodson, Sandesh Kalantre, and Arthur Lin.

• Fault-Tolerant Quantum Computation with Topological Codes by Kaixin Huang, Yixu Wang, and Yong-Chan Yoo.

• Toric Codes by Eric Kubischta and Ian Teixeira.

• Quantum attacks on symmetric key classical cryptographic systems by Geng Lin and Bibhusa Rawal.

• Quantum Functional Programming by Cameron Moy, Andrew Witten, and Suteerth Vishnu.

• Quantum Simulation of Spin Models by Jue Xu and Shucheng Zhu.

• An Introduction to Quantum Optimization Approximation Algorithm by Qingfeng Wang and Tauqir Abdullah.

Generics

How to Navigate through the Course

• Quantum information and computation is an exciting emerging field. It is simply impossible to cover the all relevant topics, especially in an introductory course. Thus, the main goals of this course are

  • (1) understand and comprehend the theoretical foundation of quantum information and computation. It might not be the case you can understand all research papers after this course. However, it is expected that you can understand the basic language, and can find relevant references for the parts that you don't understand. Thus, one should be able to read research papers and learn more materials in the future.

  • (2) cover a selective collection of fundamental topics in quantum algorithms And quantum complexity. It is expected that you will know certain important concepts in these fields and can reason about them in both the high level and in sufficient details.

  • (3) learn about the research frontier of one specific topic via the course project. It is expected to be a valuable experience of reading research papers and making use of the knowledge from (1), (2), especially for graduate students.

• The study of this course consists of a large amount of reading materials. Given the difficulty of the materials, a significant amount of effort is expected.

• Please treat the course project as a training of your ability to navigate and collect information from literature and to efficiently understand the main points of research papers. It would be wonderful if something original comes out in the project. However, it is perfectly fine if it doesn't. The main purpose of the course project is to facilitate your research in the future.

Assignments

Homework assignments must be submitted electronically to ELMS. (Anyone having trouble with electronic submissions should contact the instructor as soon as possible.) I highly recommend the use of for the typesetting. In particular, we will reward the use of Latex by bonus points (extra 10% of your points). Here is a good reference about the use of . Here is a latex template for writing solutions. Check the homework page.

Textbooks & Lectures

We will mainly refer to notes (available online or our own) for lectures. We will also refer to parts of the following textbooks for further references.

• Paul Kaye, Raymond Laflamme, and Michele Mosca, An Introduction to Quantum Computing, Oxford University Press (2007).

• M. Nielsen and I. Chuang. Quantum Computation and Quantum Information, Cambridge University Press; 10 Anv edition, 2011.

• A. Yu. Kitaev, A. H. Shen and M. N. Vyalyi. Classical and Quantum Computation (Graduate Studies in Mathematics), AMS, 2002.

• John Watrous. The Theory of Quantum Information, Cambridge University Press, 2018.

We also maintain a collection of additional resources at the mini-library page.

Social Media

• We use Piazza as the discussion forum. Piazza is FERPA-compliant in that it protects the privacy of students, keeps the information private, and is not searchable by search engines. In order to participate, all students are expected to register with an email address of their choice.

• We use ELMS for submissions of assignments and projects and distributions of corresponding grades.

• This website serves as the collection of information about the course, syllabus, handouts, and references. Please check frequently!

Web Accessibility

• Please refer to UMD Web Accessibility.