Quantum Information and Quantum Computation
Class Number 47436
Tuesday and Thursday at 8:30-9:50am
Physics building, room P128
Office Hours: Tuesday and Thursday at 10-11 am
Office: Physics D-147
Office Hours: Thursday 10am-11am
The course will start with a brief reminder of quantum mechanics [QM]. All sections of QM necessary for information processing will be introduced: interaction with the environment, measurements theory, trace preserving completely positive maps, as well as Bell inequalities. The course will proceed to entanglement theory. Application of entanglement to analysis of dynamical systems will be explained.
Information theory [starting from Shannon theorems about channel capacity] will be related to statistical physics and probability theory.
Algorithm theory: Shor's and Grover's quantum algorithms. Quantum cryptography also will be explained, starting from BB84.
Different approaches to building of quantum computers: solid state [fractional quantum Hall effect and Josephson junction] and quantum optics [including optical lattices, cold atoms, ion traps and electromagnetically induced transparency]. Different architectures of quantum computation: circuit, adiabatic, topological quantum computation [including models of anyons] and measurement based quantum computation.
Application of ideas of quantum information to condensed matter also will be explained: topological phases of matter [including CFT], Kitaev model, spin chains, topological Kondo and SYK model. Simulation of models of mathematical physics in optical lattices [massive Thirring model, XXZ spin chain and Lieb-Linger model].
Computational physics also will be mentioned: MERA (and its relation to AdS) matrix product states and relation to algebraic Bethe ansatz.
Highly entangled spin chains [Motzkin and Fredkin] will be mentioned.
Quantum machine learning as well as qiskit will be explained. Guest lecturers will be invited. Quantum computer learning club will be organized.
- Understanding of foundations of quantum mechanics: measurement theory, interaction with environment and the role of entanglement
- Understanding of quantum algorithms such as Shor's and Grover's
- Understand of information theory and their relation to statistical mechanics and probability theory
Mid Term Exam: March 12
Final Exam: May 9
Entanglement in quantum spin chains
Isotropic XY model
Renyi entropy in XY model
Entanglement in AKLT model
AKLT on arbitrary graph
Richard Feynman On quantum physics and computer simulation .
Quantum Mechanics: Photons Corpuscles of Light by Richard Feynman
Claude Shannon Father of the Information Age
Popular lecture by Michael Freedman
Quantum Information Processing with Superconducting Circuits
Anyons in one dimension
Quantum algorithm for partial search
Algebraic Bethe Ansatz and Tensor networks.
Web page of professor Wei : phy680; quantum
Quantum Information Processing
For your information.
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may impact your course work, please contact Disability Support Services
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Last updated Monday, 28-Jan-2019 13:50:34 EST