Computational light scattering

Last modified by aipentti@helsinki_fi on 2024/01/09 08:28

Course page for Computational light scattering — Laskennallinen valonsironta

Advanced Course, 5 credits, PAP315, Autumn 2022, Period 1

Computational light scattering assesses elastic light scattering (electromagnetic scattering) by particles of arbitrary sizes, shapes, and optical properties. Particular attention is paid to advanced computational methods for both single and multiple scattering, that is, to methods for isolated particles and extended media of particles (cf. dust particles in cometary comae and particulate media on asteroids). Theoretical foundations are described for the physics of light scattering based on the Maxwell equations and for a number of computational methods. In single scattering, the methods include, for example, the volume integral equation, discrete-dipole approximation, T-matrix or transition matrix, and finite-difference time-domain methods. In multiple scattering, the methods are typically based on Monte Carlo ray tracing. These include far-field radiative transfer and coherent backscattering methods and their extensions incorporating full-wave interactions. Students are engaged in developing numerical methods for specific scattering problems. The development and computations take place in both laptop and supercomputing environments.

Course is held on Mondays 10-12 and Fridays 12-14. Lectures are given in hybrid mode, both in Zoom and at Physicum D116. Exercise sessions are on Physicum D104, Fridays 14-16.

Lectures by Karri Muinonen, Anne Virkki, and Antti Penttilä.

Recommended preliminary knowledge: basic courses in Physics, basic courses in Mathematics, Electrodynamics, Mathematical Methods for Physicists I & II, Scientific Computing I.

Information

Information package about course details

Lecture material

Lecture 1
Lecture 2, part 1, 2, and 3
Lecture 3, part 1, 2, 3, and 4
Lecture 4, part 1, 2, 3, 4, 5, 6, and 7
Lecture 5, part 1, 2, 3, 4, and 5
Lecture 6
Lecture 7, part 1, 2, and 3
Lecture 8, part 1, 2, and 3
Lecture 9, part 1 and 2
Lecture 10, part 1, 2, and 3
Lecture 11, part 1, 2, and
3
Lecture 12, part 1, 2
Lecture 13

Exercises

Background material

P. C.Y. Chang, J.G. Walker, K.I. Hopcraft. Ray tracing in absorbing media. JQSRT 96 (2005).
Mie codes in Python: mie.pyor in Fortran77:mie.f
Mishchenko's T-matrix code for particles in random orientation, modified to read parameters from an input file: tmd-lp.f, lpd.f, tmd.par.f. An example input file default.in, and article explaining the parameters: 98_jqsrt_60_309.pdf
Example input file for Mackowski's MSTM code:mstm-input.inp
Example input files for RT-CB code: rayleigh-plane.inp
Alternative Makefile for RT-CB, copy to directory src\dsfmt under the rt-cb root folder