Merge branch 'main' of cau-git.rz.uni-kiel.de:nt/mitarbeiter/silas/imdd_simulation
This commit is contained in:
Silas Oettinghaus
@@ -1,135 +1,3 @@
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% plot_dispersion_models
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% ------------------------------------------------------------
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% Visualizes exact and linearized chromatic dispersion D(λ)
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% around the zero-dispersion wavelength (ZDW).
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%
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% Inputs:
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% lambda0_nm - ZDW in nm
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% S0 - dispersion slope at ZDW [ps/(nm^2·km)]
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% ------------------------------------------------------------
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%% ZDW 1
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lambda0_nm = [1310];
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S0 = [0.075,0.095]';
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% wavelength axis around ZDW
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lambda_nm = linspace(1240, 1360, 400);
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% exact dispersion model
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D_exact_1 = (S0./4) .* ( ...
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lambda_nm - (lambda0_nm^4)./(lambda_nm.^3) );
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%% ZDW 2
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lambda0_nm = [1320];
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% exact dispersion model
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D_exact_2 = (S0./4) .* ( ...
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lambda_nm - (lambda0_nm^4)./(lambda_nm.^3) );
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%% plot
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figure('Color','w'); hold on;
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cols = [0.6510 0.8078 0.8902;...
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0.1216 0.4706 0.7059;...
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0.6980 0.8745 0.5412;...
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0.2000 0.6275 0.1725];
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plot(lambda_nm, D_exact_1(1,:), 'LineWidth',2, 'DisplayName',sprintf('$S_0=\SI{0.09}{\Dslope}$'),'Color',[0,0,0]);
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plot(lambda_nm, D_exact_1(2,:), 'LineWidth',2, 'DisplayName',sprintf('$S_0=\SI{0.09}{\Dslope}$'),'Color',[0,0,0]);
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% plot(lambda_nm, D_exact_2(1,:), 'LineWidth',2, 'HandleVisibility','on', 'DisplayName',sprintf('$S_0=\SI{0.09}{\Dslope}$'),'Color',[0,0,0]);
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% plot(lambda_nm, D_exact_2(2,:), 'LineWidth',2, 'HandleVisibility','on', 'DisplayName',sprintf('$S_0=\SI{0.09}{\Dslope}$'),'Color',[0,0,0]);
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xlabel('Wavelength $\lambda$ [nm]','Interpreter','latex');
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ylabel('D($\lambda$) [ps/(nm km)]','Interpreter','latex');
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title('Chromatic Dispersion Around the ZDW');
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legend('Location','best');
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grid on; box on;
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xlim([min(lambda_nm) max(lambda_nm)])
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ylim([-5 5]);
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% mat2tikz_improved('C:\Users\Silas\Documents\6971e0b65b380ca6d71c837f\02_IMDD_System\tikz\dispersion\dispersion')
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%%
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%% plot_dispersion_dual_ZDW
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% Visualizes two ZDW fiber types, each with an S0 tolerance range.
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%% plot_dispersion_minimal_for_tikz
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% Minimal setup for clean TikZ tuning
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% 1. Parameters
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lambda_nm = linspace(1240, 1360, 400);
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S0_range = [0.075, 0.095];
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ZDW_range = [1300, 1325];
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% 2. Calculate Envelope and Nominal
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[S_mesh, Z_mesh] = meshgrid(S0_range, ZDW_range);
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D_all = zeros(length(lambda_nm), 4);
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for i = 1:4
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D_all(:,i) = (S_mesh(i)/4) .* (lambda_nm - (Z_mesh(i)^4)./(lambda_nm.^3));
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end
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D_env_min = min(D_all, [], 2);
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D_env_max = max(D_all, [], 2);
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D_nominal = (mean(S0_range)/4) .* (lambda_nm - (mean(ZDW_range)^4)./(lambda_nm.^3));
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% 3. Plotting
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figure('Color','w'); hold on;
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env_col = [0.1216, 0.4706, 0.7059];
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% Shaded area
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[hl, hp] = boundedline(lambda_nm, (D_env_min+D_env_max)/2, ...
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(D_env_max-D_env_min)/2, 'alpha', 'cmap', env_col);
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set(hl, 'YData', D_nominal, 'Color', 'k', 'LineWidth', 1.5);
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% Generate the outline and capture the handle
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ho = outlinebounds(hl, hp);
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% Change properties
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set(ho, 'Color', 'k', ... % Make it black
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'LineStyle', '--', ... % Make it dashed
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'LineWidth', 0.5, ... % Make it thin
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'HandleVisibility', 'off'); % Hide from legend
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% 4. "Minimal" Measurement Lines (Tweak these in TikZ later)
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% Vertical measurement at 1290nm
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lambda_v = 1290;
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[~, idx] = min(abs(lambda_nm - lambda_v));
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y_bot = D_env_min(idx);
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y_top = D_env_max(idx);
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% Simple line - in TikZ this will be a single \draw command
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line([lambda_v, lambda_v], [y_bot, y_top], 'Color', 'r', 'LineWidth', 1.2, 'Tag', 'VertArrow');
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text(lambda_v + 2, (y_top+y_bot)/2, '$\Delta D$', 'Color', 'r', 'Interpreter', 'latex');
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% Horizontal measurement at D=0
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z1 = ZDW_range(1);
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z2 = ZDW_range(2);
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line([z1, z2], [0, 0], 'Color', [0.1 0.5 0.1], 'LineWidth', 1.2, 'Tag', 'HorizArrow');
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text(mean(ZDW_range), 0.5, '$\Delta \lambda_0$', 'Color', [0.1 0.5 0.1], ...
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'Interpreter', 'latex', 'HorizontalAlignment', 'center');
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% 5. Aesthetics
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xlabel('Wavelength $\lambda$ [nm]', 'Interpreter', 'latex');
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ylabel('$D(\lambda)$ [ps/(nm km)]', 'Interpreter', 'latex');
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grid on; box on;
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xlim([1240 1360]); ylim([-5 5]);
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line(xlim, [0 0], 'Color', [0.4 0.4 0.4], 'LineStyle', '--', 'HandleVisibility', 'off');
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% Legend using the handles we have
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legend([hp, hl], {'Worst-case Envelope', 'Nominal Realization'}, ...
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'Location', 'northwest', 'Interpreter', 'latex');
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% To export, run:
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% matlab2tikz('dispersion.tex', 'standalone', true);
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%% plot_dispersion_for_tikz
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% Optimized for matlab2tikz compatibility with manual arrows
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%% plot_dispersion_statistical_envelopes
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% Visualizes hard spec limits vs. 98% statistical distribution
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%% plot_dispersion_final_for_tikz
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lambda_nm = linspace(1240, 1360, 400);
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@@ -181,6 +49,14 @@ for k = 1:size(scenarios, 1)
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% 'HandleVisibility', 'off'); % Hide from legend
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% Capture Wide Spec (k=1) bounds for the TikZ measurement lines
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hp.FaceAlpha = 0.5;
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% ho = outlinebounds(hl, hp);
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% % Change properties
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% set(ho, 'Color', 'k', ... % Make it black
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% 'LineStyle', '--', ... % Make it dashed
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% 'LineWidth', 1, ... % Make it thin
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% 'HandleVisibility', 'off'); % Hide from legend
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% Capture Wide Spec (k=1) bounds for the TikZ measurement lines
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hp.FaceAlpha = 0.5;
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else
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hp.FaceAlpha = 0.8;
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end
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@@ -18,7 +18,7 @@ Dacc_surface = zeros(numel(L_values), numel(f_targets));
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for iL = 1:numel(L_values)
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L = L_values(iL);
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[lambda_vec, Dacc_vec] = lambda_for_first_null_full(f_targets, L, lambda0, S0);
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% Store the 1x absolute offset |lambda - lambda0|
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lambda_surface(iL, :) = abs(lambda0 - lambda_vec);
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Dacc_surface(iL, :) = Dacc_vec;
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@@ -38,7 +38,7 @@ hold on;
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lambda_levels = unique([50:-10:30, 30:-5:5]);
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% Contour plot
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[C,h] = contour(f_GHz, L_km, lambda_surface_nm, lambda_levels, ...
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[C,h] = contourf(f_GHz, L_km, lambda_surface_nm, lambda_levels, ...
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'LineWidth', 1.2, ...
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'ShowText', 'off');
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@@ -53,19 +53,19 @@ ylabel(cb, '$\Delta \lambda$ [nm]', 'Interpreter', 'latex');
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% Find placement along the first-null curve for each level
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for i = 1:length(lambda_levels)
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lvl = lambda_levels(i);
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% Re-calculate the specific (f, L) curve for this delta-lambda
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lambda_target = lambda0 - (lvl * 1e-9);
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LHS = -( (S0*1e3) / 4 ) * (lambda_target - (lambda0^4)/(lambda_target^3)) * lambda_target^2;
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const_val = (c*0.5) / LHS;
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f_curve_GHz = linspace(min(f_GHz), max(f_GHz), 500);
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L_curve_km = const_val ./ (f_curve_GHz * 1e9).^2 / 1000;
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% Filter for points within the plot axes
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in_bounds = find(L_curve_km >= min(L_km)*1.1 & L_curve_km <= max(L_km)*0.9 & ...
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f_curve_GHz >= min(f_GHz)*1.1 & f_curve_GHz <= max(f_GHz)*0.9);
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if ~isempty(in_bounds)
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% Specific alternating pattern for weight to minimize overlapping
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if i < 9
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@@ -74,7 +74,7 @@ for i = 1:length(lambda_levels)
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weight = 0.05 + 0.1 * mod(i, 2);
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end
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idx = in_bounds(max(1, min(length(in_bounds), round(length(in_bounds) * weight))));
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text(f_curve_GHz(idx), L_curve_km(idx), sprintf('%g nm', lvl), ...
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'Color', 'k', 'BackgroundColor', 'w', 'Margin', 1.5, ...
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'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle', ...
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@@ -98,7 +98,7 @@ if 0
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max_D = max(Dacc_surface(:), [], 'omitnan');
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% Calculate 3 integer levels well within the data range
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D_levels = unique(round(linspace(min_D*0.8, max_D*0.8, 3)));
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[CS, h] = contour(f_GHz, L_km, Dacc_surface, D_levels, 'k--', 'LineWidth', 0.8);
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clabel(CS, h, 'Color','k', 'FontSize',8);
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end
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@@ -106,7 +106,7 @@ end
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%% Export
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% Hier erzwingen wir die rote Colormap für pgfplots, damit mat2tikz es nicht blau exportiert!
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mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/02_IMDD_System/tikz/dispersion/dispersion_power_fading_contour2.tikz");
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% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/02_IMDD_System/tikz/dispersion/dispersion_power_fading_contour2.tikz");
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function [lambda_vec, Dacc_vec] = lambda_for_first_null_full(f_target, L, lambda0, S0)
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% lambda_for_first_null_full (stable, single-branch + validity checks)
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@@ -148,10 +148,10 @@ Dacc_vec = NaN(N,1);
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for k = 1:N
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RHS = c * 0.5 / (f_target(k)^2 * L);
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% Normal-dispersion branch (λ < λ0)
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fun = @(lambda) -(S0_si/4).*(lambda - (lambda0^4)./(lambda.^3)).*lambda.^2 - RHS;
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% Limit the search to [λ_min, λ0)
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try
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lambda_sol = fzero(fun, [lambda_min, lambda0 * 0.999]);
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@@ -159,18 +159,18 @@ for k = 1:N
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% If the zero is not within bounds, skip this point
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lambda_sol = NaN;
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end
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% Validate solution
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if isnan(lambda_sol) || lambda_sol < lambda_min || lambda_sol > lambda_max
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lambda_vec(k) = NaN;
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Dacc_vec(k) = NaN;
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continue
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end
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% Compute D(lambda) and accumulated dispersion
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D_lambda = (S0_si/4) * (lambda_sol - (lambda0^4)/(lambda_sol^3)) / 1e-6; % ps/(nm·km)
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Dacc_val = D_lambda * (L/1000); % ps/nm
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% Sanity bound on dispersion (avoid unphysical > ±100 ps/nm)
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if abs(Dacc_val) > 100
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lambda_vec(k) = NaN;
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@@ -16,6 +16,9 @@ D_lambda = (S0/4) * (lambda*1e9 - (lambda0*1e9)^4/(lambda*1e9)^3); % ps/(nm·km)
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D_si = D_lambda * 1e-6; % → s/m²
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b2 = -D_si * lambda^2 / (2*pi*c); % s²/m
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Dacc = D_lambda * L;
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fprintf('Accumulated Dispersion: %.2f ps/nm \n', Dacc / 1e3);
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%% Frequency grid
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f_max = 200e9;
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f = linspace(0, f_max, 5000); % [Hz]
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