CS 682: Quantum Computing
Course Notes
Topic  Link 
Introduction to quantum computing  Introduction 
Linear algebra  Linear Operators 
Postulates of quantum mechanics  Postulates 
Computation, classical and quantum.  Computation 
DeutschJozsa, Fourier transform and phase estimation  Basic algorithms 
Simon's algorithm, factorization  Factor 
Grover search, Query complexity  Search 
Administrative details:
 Time: 3:304:50 MW, Venue: KD 102
 Anticheating policy: from CSE Dept
 Drop policy: from DUGC

Grading:
 Exams (55): 3 Quizzes: 5 + 10 + 10 , Midsem: 20, Endsem: 30.
 Project (25)
Course description:
Quantum computation captured the imagination of computer scientists with the discovery of efficient quantum algorithms for factoring and fast algorithm for search. The aim of
quantum computing is to do computation using the quantum mechanical effects. The study of quantum computation and information involves mathematics, physics and computer science.
This course will primarily focus on the mathematics and computer science aspect of it. We will start the course by answering "why quantum computing?" and then move on to study the basics of
linear algebra and computer science needed to understand the theory of quantum computation. Then, we will talk about quantum circuit model in which most of the quantum algorithms are designed.
The final part of the course will look at quantum algorithms and the advantage they offer over classical counterparts.
The only prerequisite for the course is the basic understanding of linear algebra. There are lot of other interesting topics in quantum computing which will not be covered in this course.
In particular, we will miss topics like physical realization of quantum computers and quantum information theory. Students are encouraged to take them as part of
the project in the course.
References
Quantum computing
 Quantum Computation and Quantum Information, M A Nielsen and I L Chuang.
 An Introduction to Quantum Computing, P Kaye, R Laflamme and M Mosca.
Linear Algebra
 Linear Algebra and its Applications, G. Strang.
 Matrix Analysis, Bhatia.
Quantum courses