Physics 680-01

Class Number 46523

Physics building, room 128

**Office Hours: Tuesday and Thursday from 9:50 am till 10:50am **

Instructors: Vladimir Korepin

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, describibng channel capacity] will be related to statistical physics [including Maxwell's demon and Landauer's Principle] and probability theory.

**Algorithm theory**: Grover's quantum algorithms [hardware adjusted quantum search]. Quantum cryptography also will be explained, starting from BB84. Different approaches to building of quantum computers: solid state [Josephson junction], topological and quantum optics [including optical lattices, cold atoms, ion traps, electromagnetically induced transparency and chiral materials]. Different architectures of quantum computation: circuit, adiabatic, topological and measurement based quantum computation. Quantum networking will be a part of the course.

Application of ideas of quantum information to condensed matter and high energy physics also will be explained: Thirring model, XXZ spin chain, Lieb-Linger model of anyons, Lipatov's spin chain. Simulation of models of mathematical physics in optical lattices also will be explained.

Computational physics also will be mentioned: matrix product states and relation to algebraic Bethe ansatz.

Highly entangled spin chains [Motzkin and Fredkin] will be mentioned.

Quantum machine learning will be explained. A lecture on qiskit and noisy intermediate scale quantum computers will be organized.

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
- Understand of information theory and their relation to statistical mechanics and probability theory

**M. Nielsen and I. Chuang**, Cambridge University Press, edition, 2003 ; [ corrections to NC book ]- Andrew Steane, Quantum Computing
- J. Preskill lecture notes
- Introduction to Quantum Algorithms by P.Shor
- Measurement based quantum computation
- QISKIT
- Topological quantum computation
- Reinforced Quantum Machine Learning , by Hans Briegel
- Quantum Machine Learning and Data Mining, by Peter Wittek
- Machine Learning Phase Transitions
- Machine Learning by Biamonte
- Project Q
- Holographic approach to entanglement and structure of entanglement in quantum field theory
- Introduction to Tensor Networks
- Quantum 101
- Tensor Flow
- Landauer's Principle in a Quantum Szilard Engine
- Maxwell's Demon
- Graphene

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

Quantum algorithm for partial search

Algebraic Bethe Ansatz and Tensor networks.

Web page of professor Wei : phy680; quantum

Quantum Information Processing

For your information. If you have a physical, psychological, medical or learning disability that may impact your course work, please contact Disability Support Services (631) 632-6748. They will determine with you what accommodations are necessary and appropriate. All information and documentation is confidential.

Students requiring emergency evacuation are encouraged to discuss their needs with their professors and Disability Support Services. For procedures and information, go to the following web site http://studentaffairs.stonybrook.edu/dss/

Disability Support Services, Academic Integrity and Critical Incident Management, see http://www.stonybrook.edu/provost/facultyinfo/index.shtml

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