Thermalization of Quantum Memories - A Tensor Networks Approach
Offered By: Erwin Schrödinger International Institute for Mathematics and Physics (ESI) via YouTube
Course Description
Overview
Explore the thermalization of quantum memories through a tensor networks approach in this comprehensive lecture. Delve into the commonly held belief that 2D quantum memories cannot be self-correcting when exposed to a thermal bath. Examine recent results confirming this belief for 2D Kitaev's quantum double models. Learn about the proof based on representing the Gibbs state of quantum double models as a PEPS (Projected Entangled Pair State). Understand how this representation allows for rigorous estimation of the spectral gap of the corresponding parent Hamiltonian. Gain insights into the implications of these findings for quantum memory stability and relaxation times as a function of system size.
Syllabus
Angelo Lucia - Thermalization of quantum memories - a tensor networks approach
Taught by
Erwin Schrödinger International Institute for Mathematics and Physics (ESI)
Related Courses
Quantum Information and ComputingIndian Institute of Technology Bombay via Swayam Quantum Computing
Indian Institute of Technology Kanpur via Swayam Understanding Quantum Computers
Keio University via FutureLearn Quantum Information Science I, Part 1
Massachusetts Institute of Technology via edX Quantum Information Science II: Quantum states, noise and error correction
Massachusetts Institute of Technology via edX