ps beta 2.5的妙用

1、https://pan.baidu.com/s/1CCw6RGlzEJ7TPWou8pPADQ?pwd=2023 

2、下载新便携版。

3、解压到c:\myapp文件夹下。

4、运行。

5、登录us账号。

6、使用智能移除。

 效果如下:

使用滤镜。

先将C:\myApp\(新便携版)Adobe Photoshop (25.0.0 m2265 Beta) Portable\App\Roaming\Adobe\UXP\PluginsStorage下的把PHSP改名为PHSPBETA,重新打开软件即可。

1)新建图像。

2)导入图像。

3)滤镜->neural filters

 使用滤镜。

 效果如下。

 

% Two-segment Erbium-doped fiber model with SWCNT and NPR mode-locking clc; clear; % Simulation parameters Nz = 200; % Number of steps in fiber length Nt = 4096; % Number of time points Tmax = 10; % Maximum time window (ps) dz = 0.1; % Step size in z (m) % User-adjustable parameters z_max = input('Enter total cavity length (m): '); % Total propagation distance (m) fiber_split = input('Enter EDF80 length (m): '); % EDF80 segment length fiber_split_2 = input('Enter Er80 length (m): '); % Er80 segment length pump_power_EDF80 = input('Enter pump power for EDF80 (mW): '); pump_power_Er80 = input('Enter pump power for Er80 (mW): '); % Fiber parameters for EDF80 and Er80 beta2_EDF80 = -480e-24; % Group velocity dispersion for EDF80 (s^2/m) beta2_Er80 = 160e-24; % Group velocity dispersion for Er80 (s^2/m) gamma_EDF80 = 2.5e-20; % Nonlinear coefficient for EDF80 (W^-1 m^-1) gamma_Er80 = 2.5e-20; % Nonlinear coefficient for Er80 (W^-1 m^-1) alpha_EDF80 = 0.2; % Loss coefficient for EDF80 (dB/m) alpha_Er80 = 0.2; % Loss coefficient for Er80 (dB/m) P_sat_pump = 150; % 泵浦饱和功率 (mW) gain_EDF80 = (pump_power_EDF80 / (1 + pump_power_EDF80 / P_sat_pump)) * 0.5; gain_Er80 = (pump_power_Er80 / (1 + pump_power_Er80 / P_sat_pump)) * 0.5; % 降低饱和功率以增强饱和效应 saturation_power = 150; % 泵浦饱和功率 (mW) % Time grid dt = 2 * Tmax / Nt; % Time step (ps) t = linspace(-Tmax, Tmax, Nt); % Time vector (ps) f = linspace(-1 / (2 * dt), 1 / (2 * dt), Nt); % Frequency vector (THz) % Initial Gaussian pulse P0 = 5; % Peak power (W) T0 = 1; % Pulse width (ps) A0 = sqrt(P0) * exp(-t.^2 / (2 * T0^2)); % Initial pulse % Single-Walled Carbon Nanotube Model (SWCNT) R_swcnt = 0.5; % Modulation depth tau_swcnt = 0.08; % Recovery time (ps) % Initialize the pulse A = A0; % Define propagation loop z = 0:dz:z_max; % Propagation distance pulse_width = zeros(size(z)); spectrum_width = zeros(size(z)); output_pulse = zeros(size(A)); % To store 10% output pulse for step = 1:length(z) % Determine fiber segment if z(step) < fiber_split beta2 = beta2_EDF80; gamma = gamma_EDF80; g = gain_EDF80 - alpha_EDF80; % Net gain for EDF80 elseif z(step) < (fiber_split + fiber_split_2) beta2 = beta2_Er80; gamma = gamma_Er80; g = gain_Er80 - alpha_Er80; % Net gain for Er80 else beta2 = 0; % Assume standard fiber with no additional effects gamma = 0; g = -0.1; % Loss-only region end % Calculate effective gain P_avg = mean(abs(A).^2); % Average power g_eff = g / (1 + P_avg / saturation_power); % Effective gain % Apply gain A = A .* exp(0.5 * g_eff * dz); % Apply nonlinear Schr枚dinger equation (SSFM) A = ssfm(A, dz, beta2, gamma, dt); % Apply SWCNT saturable absorber A = A .* (1 - R_swcnt * exp(-abs(A).^2 / P0)); % Extract 10% of the pulse as output if step == length(z) % At the end of the cavity output_pulse = 0.1 * A; A = 0.9 * A; % Remaining 90% continues in the cavity end % Compute pulse and spectrum widths pulse_width(step) = sqrt(trapz(t, t.^2 .* abs(A).^2) / trapz(t, abs(A).^2)); spectrum = fftshift(fft(A)); spectrum_width(step) = sqrt(trapz(f, f.^2 .* abs(spectrum).^2) / trapz(f, abs(spectrum).^2)); % Outpu6t diagnostics fprintf('Step %d/%d: Pulse energy = %.3e J, Pulse width = %.3e ps, Spectrum width = %.3e THz\n', ... step, Nz, trapz(t, abs(A).^2) * dt, pulse_width(step), spectrum_width(step)); end % Convert spectrum to wavelength f_center = 3e8 / (1550 * 1e-9); % Central frequency for 1550 nm lambda = 3e8 ./ (f_center + f*1e12) * 1e9; % 杞崲鍒? nm spectrum_output = abs(fftshift(fft(output_pulse))).^2 / Nt; % Sort wavelength and spectrum for plotting [lambda_sorted, sort_idx] = sort(lambda); spectrum_sorted = spectrum_output(sort_idx); % Plot results figure; subplot(2, 1, 1); plot(t, abs(output_pulse).^2, 'b'); xlabel('Time (ps)'); ylabel('Intensity (a.u.)'); title('Temporal Profile of Output Pulse'); FWHM_time = calculate_FWHM(t, abs(output_pulse).^2); peak_time = t(abs(output_pulse).^2 == max(abs(output_pulse).^2)); time_range = 10 * FWHM_time; xlim([peak_time - time_range, peak_time + time_range]); text(0.6 * max(peak_time - time_range), 0.8 * max(abs(output_pulse).^2), sprintf('FWHM = %.2f ps', FWHM_time)); subplot(2, 1, 2); plot(lambda_sorted, spectrum_sorted, 'r'); xlabel('Wavelength (nm)'); ylabel('Spectral Intensity (a.u.)'); title('Spectral Profile of Output Pulse'); FWHM_spectrum = calculate_FWHM(lambda_sorted, spectrum_sorted); peak_wavelength = lambda_sorted(spectrum_sorted == max(spectrum_sorted)); spectrum_range = 10 * FWHM_spectrum; xlim([peak_wavelength - spectrum_range, peak_wavelength + spectrum_range]); % Automatically adjust range text(mean(peak_wavelength - spectrum_range), 0.8 * max(spectrum_sorted), sprintf('FWHM = %.2f nm', FWHM_spectrum)); x1 = t; y1 = abs(output_pulse).^2; x2 = lambda_sorted; y2 = spectrum_sorted; function A = ssfm(A, dz, beta2, gamma, dt) % Split-step Fourier method (SSFM) for nonlinear Schr枚dinger equation Nt = length(A); omega = 2 * pi * linspace(-1 / (2 * dt), 1 / (2 * dt), Nt); % Frequency grid % Linear operator (dispersion) L = exp(1i * beta2 * (omega.^2) * dz / 2); % Nonlinear operator A = ifft(L .* fft(A .* exp(1i * gamma * abs(A).^2 * dz / 2))); % SSFM step end function FWHM = calculate_FWHM(x, y) half_max = max(y) / 2; indices = find(y >= half_max); if isempty(indices) || length(indices) == 1 FWHM = 0; % 澶勭悊寮傚父鎯呭喌 else FWHM = abs(x(indices(end)) - x(indices(1))); end end 解释一下这篇代码
09-11
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