Quantum Time Correlation Functions in an Open-Chain Path Integral Distribution
Institute for Pure & Applied Mathematics (IPAM) via YouTube
PowerBI Data Analyst - Create visualizations and dashboards from scratch
Become an AI & ML Engineer with Cal Poly EPaCE — IBM-Certified Training
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Explore an advanced lecture on quantum time correlation functions presented by Mark Tuckerman of New York University Chemistry and Courant Institute. Delve into a novel approach for calculating thermal quantum time correlation functions in condensed phases using open-chain path integrals. Discover how this method transforms the problem into a sampling task using path-sum variables, offering a fresh perspective on semiclassical approximations. Examine the advantages of this technique over traditional approaches like centroid and ring-polymer MD algorithms, particularly for non-linear operators. Learn about practical implementation strategies, comparisons with existing methods, and potential applications in rate theory calculations and electronic excitation spectroscopy. Gain insights into complex concepts such as Feynman path integrals, Monte Carlo sampling, and enhanced path-integral molecular dynamics in this comprehensive exploration of quantum mechanics and computational chemistry.
Syllabus
Partition functions
Quantum time correlation
Correlation functions
Kuba transform
Complex time
Path integral
Transformation
Theorem
Positive definite
Rate theory
Openchain formulation
Boltzmann factor
Comparison
Normalization
Sampling
Histogram
Outlooks
Taught by
Institute for Pure & Applied Mathematics (IPAM)