Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Publication
“Slow Light” in stimulated Brillouin scattering: on the influence of the spectral width of pump radiation on the group index: Comment
Abstract
In a recent paper by Kovalev et al [Optics Express 17, 17317 (2009)] the coupled equations describing stimulated Brillouin scattering (SBS) were solved in the Fourier domain. The main conclusion driven by the authors was that SBS pump spectral broadening was not effective in increasing the interaction bandwidth. While the calculations are essentially correct, the interpretation of the results leads to erroneous conclusions.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related concepts (26)
Frequency domain
In mathematics, physics, electronics, control systems engineering, and statistics, the frequency domain refers to the analysis of mathematical functions or signals with respect to frequency, rather than time. Put simply, a time-domain graph shows how a signal changes over time, whereas a frequency-domain graph shows how the signal is distributed within different frequency bands over a range of frequencies. A frequency-domain representation consists of both the magnitude and the phase of a set of sinusoids (or other basis waveforms) at the frequency components of the signal.
Fourier transform
In physics and mathematics, the Fourier transform (FT) is a transform that converts a function into a form that describes the frequencies present in the original function. The output of the transform is a complex-valued function of frequency. The term Fourier transform refers to both this complex-valued function and the mathematical operation. When a distinction needs to be made the Fourier transform is sometimes called the frequency domain representation of the original function.
Fourier analysis
In mathematics, Fourier analysis (ˈfʊrieɪ,_-iər) is the study of the way general functions may be represented or approximated by sums of simpler trigonometric functions. Fourier analysis grew from the study of Fourier series, and is named after Joseph Fourier, who showed that representing a function as a sum of trigonometric functions greatly simplifies the study of heat transfer. The subject of Fourier analysis encompasses a vast spectrum of mathematics.
Related publications (71)
An optimal preconditioned FFT-accelerated finite element solver for homogenization
Till Junge, Ali Falsafi, Martin Ladecký
We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...
ELSEVIER SCIENCE INC2023pyFFS: A Python Library for Fast Fourier Series Computation and Interpolation with GPU Acceleration
Martin Vetterli, Paul Hurley, Eric Bezzam, Sepand Kashani, Matthieu Martin Jean-André Simeoni
Fourier transforms are an often necessary component in many computational tasks, and can be computed efficiently through the fast Fourier transform (FFT) algorithm. However, many applications involve an underlying continuous signal, and a more natural choi ...
2022On discrete Fourier uniqueness sets in Euclidean space
In this paper we present a new construction of a discrete Fourier uniqueness set in Euclidean space. ...
ICM2022Related MOOCs (11)
Digital Signal Processing I
Basic signal processing concepts, Fourier analysis and filters. This module can
be used as a starting point or a basic refresher in elementary DSP
Digital Signal Processing II
Adaptive signal processing, A/D and D/A. This module provides the basic
tools for adaptive filtering and a solid mathematical framework for sampling and
quantization
Digital Signal Processing III
Advanced topics: this module covers real-time audio processing (with
examples on a hardware board), image processing and communication system design.