Find the Fourier transform using MATLAB (ff) for a Gaussian pulse https://www.ma

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Find the Fourier transform using MATLAB (ff) for a Gaussian pulse https://www.mathworks.com/help/matlab/ref/fft html Save the output plot (and place your balzerid in the title of the plot- https://www.mathworks.com/help/matlab/creating plots/add-title-axis-labels-and-legend- to-graph.html) CO

Explanation / Answer

%% Fourier transform of Gaussian pulse clear; close all; clc c = 3e+8; % Speed of light [m/sec] lambda = 800e-9; % Wavelength [nm] freq = c/lambda; % Actual Frequency of light [THz] %% % % Nyquist sampling theorem % The sampling frequency should be at least twice the highest frequency % contained in the signal, fs>2*f % fsamp = freq*10; % Sampling frequency T = 1/fsamp; % Unit time [fs] L = 200; % Length of signal sigma = 8e-15; % Pulse duration t = (0:L-1)*T; % Time base t0 = max(t)/2; % Used to centering the pulse %% Electric field Egauss = (exp(-2*log(2)*(t-t0).^2/(sigma)^2)).*cos(-2*pi*freq*(t-t0)); subplot(2,1,1) plot(t/1e-15,real(Egauss),'b'); title(['Gaussian Pulse sigma=', num2str(sigma),'s']); xlabel('Time (fs)'); ylabel('Amplitude'); ylim([-1 1]) %xlim([30e-15 70e-15]) grid on NFFT = 2^nextpow2(L); %NFFT = 1900; % Frequency sampling number, it will define how X = fft(Egauss,NFFT)/L; %Pxx=X.*conj(X)/(NFFT*NFFT); %computing power with proper scaling freq = 0.5*fsamp*linspace(0,1,NFFT/2+1); % (full range) Frequency Vector subplot(2,1,2) plot(freq/1e+12,2*abs(X(1:NFFT/2+1))) title('Magnitude of FFT'); xlabel('Frequency (THz)') ylabel('Magnitude |X(f)|'); %xlim([340 380]) grid on

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