Lecture

Correlation Functions & Spectra

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In course

CH-453: Molecular quantum dynamics

The course covers several exact, approximate, and numerical methods to solve the time-dependent molecular Schrödinger equation, and applications including calculations of molecular electronic spectra. More advanced topics include introduction to the semicl ...

Description

This lecture covers correlation functions, Franck-Condon transitions, Born-Oppenheimer approximation, and spectra. It discusses the calculation of correlation functions, molecular transitions, and matrix elements of transitions. The lecture also explores the interaction with the far field and dipole moments.

Instructor

Jiri Vanicek

Teaching & PhD PhD Students Liam Oliver Marsh, Yeha Lee, Davide Barbiero, Yannick Calvino Alonso, Manas Nagda Past EPFL PhD Students Cesare Mollica, Ray Marcel Marin Florez, Marius Wehrle, Aurélien Patoz, Konstantin Karandashev, Tomislav Begusic, Julien Roulet, Seonghoon Choi, Roya Moghaddasi Fereidani, Zhan Tong Zhang, Eriks Kletnieks, Alan Scheidegger, Fabian Kröninger Courses Mathematical methods in chemistry CH-250 This course consists of two parts. The first part covers basic concepts

Official source

Related concepts (30)

Matrix decomposition

In the mathematical discipline of linear algebra, a matrix decomposition or matrix factorization is a factorization of a matrix into a product of matrices. There are many different matrix decompositions; each finds use among a particular class of problems. In numerical analysis, different decompositions are used to implement efficient matrix algorithms. For instance, when solving a system of linear equations , the matrix A can be decomposed via the LU decomposition.

Diagonal matrix

In linear algebra, a diagonal matrix is a matrix in which the entries outside the main diagonal are all zero; the term usually refers to square matrices. Elements of the main diagonal can either be zero or nonzero. An example of a 2×2 diagonal matrix is , while an example of a 3×3 diagonal matrix is. An identity matrix of any size, or any multiple of it (a scalar matrix), is a diagonal matrix. A diagonal matrix is sometimes called a scaling matrix, since matrix multiplication with it results in changing scale (size).

Matrix multiplication

In mathematics, particularly in linear algebra, matrix multiplication is a binary operation that produces a matrix from two matrices. For matrix multiplication, the number of columns in the first matrix must be equal to the number of rows in the second matrix. The resulting matrix, known as the matrix product, has the number of rows of the first and the number of columns of the second matrix. The product of matrices A and B is denoted as AB.

Matrix (mathematics)

In mathematics, a matrix (plural matrices) is a rectangular array or table of numbers, symbols, or expressions, arranged in rows and columns, which is used to represent a mathematical object or a property of such an object. For example, is a matrix with two rows and three columns. This is often referred to as a "two by three matrix", a " matrix", or a matrix of dimension . Without further specifications, matrices represent linear maps, and allow explicit computations in linear algebra.

Dipole

In physics, a dipole () is an electromagnetic phenomenon which occurs in two ways: An electric dipole deals with the separation of the positive and negative electric charges found in any electromagnetic system. A simple example of this system is a pair of charges of equal magnitude but opposite sign separated by some typically small distance. (A permanent electric dipole is called an electret.) A magnetic dipole is the closed circulation of an electric current system. A simple example is a single loop of wire with constant current through it.

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