Lecture

Plasmonic Modes: Bright and Dark

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

MICRO-420: Selected topics in advanced optics

This course proposes a selection of different facets of modern optics and photonics. ...

Description

This lecture covers the concepts of plasmonic bright and dark modes, including their characteristics, numerical techniques for analysis, Lorentzian lineshape, Fano resonances, and coupled oscillator models. The instructor discusses the interaction between bright and dark modes, Fano resonance engineering, and the impact of losses on the modulation and resonance width.

Instructor

Olivier Martin

Olivier J.F. Martin received the M.Sc. and Ph.D. degrees in physics in 1989 and 1994, respectively, from the Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland. In 1989, he joined IBM Zurich Research Laboratory, where he investigated thermal and optical properties of semiconductor laser diodes. Between 1994 and 1997 he was a research staff member at the Swiss Federal Institute of Technology, Zurich (ETHZ). In 1997 he received a Lecturer fellowship from the Swiss National Science Foundation (SNSF). During the period 1996-1999, he spent a year and a half in the U.S.A., as invited scientist at the University of California in San Diego (UCSD). In 2001 he received a Professorship grant from the SNSF and became Professor of Nano-Optics at the ETHZ. In 2003, he was appointed Professor of Nanophotonics and Optical Signal Processing at the Swiss Federal Institute of Technology, Lausanne (EPFL), where he is currently head of the Nanophotonics and Metrology Laboratory and Director of the Microengineering Section.

Official source

Related concepts (27)

Numerical analysis

Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). It is the study of numerical methods that attempt at finding approximate solutions of problems rather than the exact ones. Numerical analysis finds application in all fields of engineering and the physical sciences, and in the 21st century also the life and social sciences, medicine, business and even the arts.

Numerical methods for partial differential equations

Numerical methods for partial differential equations is the branch of numerical analysis that studies the numerical solution of partial differential equations (PDEs). In principle, specialized methods for hyperbolic, parabolic or elliptic partial differential equations exist. Finite difference method In this method, functions are represented by their values at certain grid points and derivatives are approximated through differences in these values.

Numerical integration

In analysis, numerical integration comprises a broad family of algorithms for calculating the numerical value of a definite integral, and by extension, the term is also sometimes used to describe the numerical solution of differential equations. This article focuses on calculation of definite integrals. The term numerical quadrature (often abbreviated to quadrature) is more or less a synonym for numerical integration, especially as applied to one-dimensional integrals.

Numerical methods for ordinary differential equations

Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals. Many differential equations cannot be solved exactly. For practical purposes, however – such as in engineering – a numeric approximation to the solution is often sufficient. The algorithms studied here can be used to compute such an approximation.

Resonance

Resonance describes the phenomenon of increased amplitude that occurs when the frequency of an applied periodic force (or a Fourier component of it) is equal or close to a natural frequency of the system on which it acts. When an oscillating force is applied at a resonant frequency of a dynamic system, the system will oscillate at a higher amplitude than when the same force is applied at other, non-resonant frequencies. Frequencies at which the response amplitude is a relative maximum are also known as resonant frequencies or resonance frequencies of the system.

Related lectures (64)

Numerical Differentiation: Part 1

Covers numerical differentiation, forward differences, Taylor's expansion, Big O notation, and error minimization.

Power Systems Dynamics: Transient Stability

Explores transient stability in power systems dynamics, covering algebraic equations, generator models, and numerical integration techniques.

Numerical Methods in Biomechanics: Hip-A

Explores numerical methods in biomechanics for hip implants and emphasizes understanding conditions for improved designs and patient outcomes.

ODEs: Introduction and Solutions

Covers Ordinary Differential Equations, first-order solutions, and numerical methods for IVP and BVP.

Harmonic Oscillator: Numerical Stability Analysis