Laser Spectrum Analysis

Description

This lecture explains two methods to measure a laser spectrum: using a grating-based optical spectrum analyzer and a Michelson interferometer. The Wiener-Khinchin theorem is introduced to relate autocorrelation functions and spectra, with practical examples and implications for single-sided spectral density.

Official source

https://mediaspace.epfl.ch/media/0_ktelqucg

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In statistical signal processing, the goal of spectral density estimation (SDE) or simply spectral estimation is to estimate the spectral density (also known as the power spectral density) of a signal from a sequence of time samples of the signal. Intuitively speaking, the spectral density characterizes the frequency content of the signal. One purpose of estimating the spectral density is to detect any periodicities in the data, by observing peaks at the frequencies corresponding to these periodicities.

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