PTCCS359 Syllabus - Quantum Computing - 2023 Regulation Anna University

PTCCS359 Syllabus - Quantum Computing - 2023 Regulation Anna University

PTCCS359

QUANTUM COMPUTING

 L T P C

2 0 2 3

COURSE OBJECTIVES:
• To know the background of classical computing and quantum computing.
• To learn the fundamental concepts behind quantum computation.
• To study the details of quantum mechanics and its relation to Computer Science.
• To gain knowledge about the basic hardware and mathematical models of quantum computation.
• To learn the basics of quantum information and the theory behind it.

UNIT I

QUANTUM COMPUTING BASIC CONCEPTS

6

Complex Numbers - Linear Algebra - Matrices and Operators - Global Perspectives Postulates of Quantum Mechanics – Quantum Bits - Representations of Qubits - Superpositions

UNIT II

QUANTUM GATES AND CIRCUITS

5

Universal logic gates - Basic single qubit gates - Multiple qubit gates - Circuit development - Quantum error correction

UNIT III

QUANTUM ALGORITHMS

7

Quantum parallelism - Deutsch’s algorithm - The Deutsch–Jozsa algorithm - Quantum Fourier transform and its applications - Quantum Search Algorithms: Grover’s Algorithm

UNIT IV

QUANTUM INFORMATION THEORY

6

Data compression - Shannon’s noiseless channel coding theorem - Schumacher’s quantum noiseless channel coding theorem - Classical information over noisy quantum channels

UNIT V

QUANTUM CRYPTOGRAPHY

6

Classical cryptography basic concepts - Private key cryptography - Shor’s Factoring Algorithm - Quantum Key Distribution - BB84 - Ekart 91

30 PERIODS

PRACTICAL EXERCISES: 30 PERIODS
1. Single qubit gate simulation - Quantum Composer
2. Multiple qubit gate simulation - Quantum Composer
3. Composing simple quantum circuits with q-gates and measuring the output into classical bits.
4. IBM Qiskit Platform Introduction
5. Implementation of Shor’s Algorithms
6. Implementation of Grover’s Algorithm
7. Implementation of Deutsch’s Algorithm
8. Implementation of Deutsch-Jozsa’s Algorithm
9. Integer factorization using Shor’s Algorithm
10. QKD Simulation
11. Mini Project such as implementing an API for efficient search using Grover’s Algorithms or

COURSE OUTCOMES: On completion of the course, the students will be able to:
CO1: Understand the basics of quantum computing.
CO2: Understand the background of Quantum Mechanics.
CO3: Analyze the computation models.
CO4: Model the circuits using quantum computation. environments and frameworks.
CO5: Understand the quantum operations such as noise and error–correction.

TOTAL:60 PERIODS

TEXT BOOKS:
1. Parag K Lala, Mc Graw Hill Education, “Quantum Computing, A Beginners Introduction”, First edition (1 November 2020).
2. Michael A. Nielsen, Issac L. Chuang, “Quantum Computation and Quantum Information”, Tenth Edition, Cambridge University Press, 2010.
3. Chris Bernhardt, The MIT Press; Reprint edition (8 September 2020), “Quantum Computing for Everyone”.

REFERENCES:
1. Scott Aaronson, “Quantum Computing Since Democritus”, Cambridge University Press, 2013.
2. N. David Mermin, “Quantum Computer Science: An Introduction”, Cambridge University Press, 2007.

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