Transfer Matrix Method in MATLAB

  • Absolute best and fastest method for simulating layered structures like thin film optical filters.

  • Learn how to approximate 2D and 3D structures so they can be simulated very fast with the TMM

  • See how to setup TMM to simulate your own ideas.

What You'll Learn

With this course, you will be able to simulate layered structures many times faster and more efficiently than commercial software. Use the speed to study and design your own devices and to run more comprehensive optimizations.

The Implementation of Transfer Matrix Method in MATLAB course will get you simulating your own ideas very quickly. In this course, you will learn every line of code in MATLAB to implement TMM using scattering matrices. You will learn how to perform approximate simulations of many 3D and 2D structures so that you can get to the answer faster than your competition.

Updated for 2024: The course has been updated with an entire new chapter that includes calculation and visualization of the fields within layers. This includes a detailed video on the theory of calculating internal fields and a block diagram of the method. The chapter also includes three MATLAB sessions where the TMM code is modified to calculate and visualize internal fields. In the last video, a simple technique is taught for calculating and visualizing the fields in external regions. 

Students who had purchased the full course more than a year ago and would like to restore their access to view the new material can email [email protected] for access. 

Course curriculum

    1. Download test_star.p

    2. star() function that performs the Redheffer star product

    3. Create the header and dashboard for the transfer matrix method

    4. Initialize the transfer matrix method

    5. Add the main loop

    6. Connect external regions

    7. Finish the transfer matrix method

    1. Lecture - Calculating the Internal Fields

    2. Notes - Calculating Internal Fields

    3. MATLAB Session 1 - Modify Main Loop

    4. MATLAB Session 2 - Calculating the Internal Fields

    5. MATLAB Session 3 - Visualizing the Fields

About this course

  • $295.00
  • 18 lessons
  • 2 hours of video content

Pricing options

The paid course grants you access to all course videos and instructional materials for one year from date of enrollment.

Meet Your Instructor

Dr. Raymond Rumpf

Dr. Raymond (Tipper) Rumpf is the EMProfessor, world renowned research and educator in the fields of computation and electromagnetics. He is the Schellenger Professor of Electrical Research in the Department of Electrical & Computer Engineering at the University of Texas at El Paso (UTEP) and the Director of the EM Lab. Dr. Rumpf formed the EM Lab with a mission to develop revolutionary technologies in electromagnetics and photonics. Under Dr. Rumpf’s leadership, the EM Lab has produced numerous breakthroughs, discoveries, and first-ever achievements. Raymond earned his BS and MS in Electrical Engineering from the Florida Institute of Technology in 1995 and 1997 respectively. He earned his PhD in Optics in 2006 from the University of Central Florida. Raymond has been awarded many research, mentoring, and teaching awards including the 2019 Dean’s Award for Excellence in Research, Most Outstanding Faculty Member in 2016/2017, and the highly prestigious University of Texas Regents’ Outstanding Teaching Award. Raymond holds five world records for skydiving and has been awarded more than a dozen United States patents. He is an Associate Editor for SPIE Optical Engineering, a Fellow of SPIE, and a Senior Member of both IEEE and the National Academy of Inventors. He is also a member of OSA, and ARRL. Raymond is active in outreach with local grade schools in El Paso as well as helping students in third-world countries.

Unleash the speed and power of TMM

The Transfer Matrix Method is the fastest and most powerful method for simulating 1D electromagnetic structures.The ability to quickly and accurately produce simulation results will give you an advantage over your competition.