Lecture

Numerical Methods for Schrödinger Equation

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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 numerical methods to solve the time-dependent Schrödinger equation, starting with the representation of wave functions on a grid with n points and discussing the common idiom change of representation via Fourier transform. It also delves into the split-operator algorithm, second-order methods, and the Crank-Nicolson method for approximating the solution. The instructor emphasizes the importance of accurate discretization and provides insights into the algorithmic details and mathematical foundations behind these numerical techniques.

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

Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Related concepts (30)

Schrödinger equation

The Schrödinger equation is a linear partial differential equation that governs the wave function of a quantum-mechanical system. Its discovery was a significant landmark in the development of quantum mechanics. The equation is named after Erwin Schrödinger, who postulated the equation in 1925 and published it in 1926, forming the basis for the work that resulted in his Nobel Prize in Physics in 1933. Conceptually, the Schrödinger equation is the quantum counterpart of Newton's second law in classical mechanics.

Numerical methods for linear least squares

Numerical methods for linear least squares entails the numerical analysis of linear least squares problems. A general approach to the least squares problem can be described as follows. Suppose that we can find an n by m matrix S such that XS is an orthogonal projection onto the image of X. Then a solution to our minimization problem is given by simply because is exactly a sought for orthogonal projection of onto an image of X (see the picture below and note that as explained in the next section the image of X is just a subspace generated by column vectors of X).

Numerical stability

In the mathematical subfield of numerical analysis, numerical stability is a generally desirable property of numerical algorithms. The precise definition of stability depends on the context. One is numerical linear algebra and the other is algorithms for solving ordinary and partial differential equations by discrete approximation. In numerical linear algebra, the principal concern is instabilities caused by proximity to singularities of various kinds, such as very small or nearly colliding eigenvalues.

Discretization

In applied mathematics, discretization is the process of transferring continuous functions, models, variables, and equations into discrete counterparts. This process is usually carried out as a first step toward making them suitable for numerical evaluation and implementation on digital computers. Dichotomization is the special case of discretization in which the number of discrete classes is 2, which can approximate a continuous variable as a binary variable (creating a dichotomy for modeling purposes, as in binary classification).

New Foundations

In mathematical logic, New Foundations (NF) is an axiomatic set theory, conceived by Willard Van Orman Quine as a simplification of the theory of types of Principia Mathematica. Quine first proposed NF in a 1937 article titled "New Foundations for Mathematical Logic"; hence the name. Much of this entry discusses NF with urelements (NFU), an important variant of NF due to Jensen and clarified by Holmes. In 1940 and in a revision in 1951, Quine introduced an extension of NF sometimes called "Mathematical Logic" or "ML", that included proper classes as well as sets.

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