From 047a1b2d854993cda3eb58fd055cec2a01f65e30 Mon Sep 17 00:00:00 2001 From: Karthik Chandrashekara Date: Sat, 7 Jun 2025 16:39:00 +0200 Subject: [PATCH] Added scripts to analyse simulation data, now possible to extract spectral contrast, weight and autocorrelation. --- .../analyzePhaseTransitionSimulation.m | 554 ++++++++++++++++++ Data-Analyzer/compareSpectralWeights.m | 55 +- Data-Analyzer/execution_scripts.m | 2 +- Data-Analyzer/extractAutocorrelation.m | 144 ----- Data-Analyzer/extractSpectralWeight.m | 81 ++- Data-Analyzer/matchTFRadii.m | 164 ++++++ Dipolar-Gas-Simulator/+Scripts/run_locally.m | 47 +- 7 files changed, 868 insertions(+), 179 deletions(-) create mode 100644 Data-Analyzer/analyzePhaseTransitionSimulation.m create mode 100644 Data-Analyzer/matchTFRadii.m diff --git a/Data-Analyzer/analyzePhaseTransitionSimulation.m b/Data-Analyzer/analyzePhaseTransitionSimulation.m new file mode 100644 index 0000000..dc94bb6 --- /dev/null +++ b/Data-Analyzer/analyzePhaseTransitionSimulation.m @@ -0,0 +1,554 @@ +%% Extract Images + +baseDir = 'D:/Results - Numerics/Data_Full3D/PhaseTransition/DTS/'; +JobNumber = 0; +runFolder = sprintf('Run_%03d', JobNumber); +movieFileName = 'DropletsToStripes.mp4'; % Output file name +datafileName = './DropletsToStripes.mat'; +reverseOrder = false; % Set this to true to reverse the theta ordering + +TitleString = 'Change across transition: Droplets To Stripes'; + +%% +baseDir = 'D:/Results - Numerics/Data_Full3D/PhaseTransition/STD/'; +JobNumber = 0; +runFolder = sprintf('Run_%03d', JobNumber); +movieFileName = 'StripesToDroplets.mp4'; % Output file name +datafileName = './StripesToDroplets.mat'; +reverseOrder = true; % Set this to true to reverse the theta ordering + + + TitleString = 'Change across transition: Stripes To Droplets'; + +%% +folderList = dir(baseDir); +isValid = [folderList.isdir] & ~ismember({folderList.name}, {'.', '..'}); +folderNames = {folderList(isValid).name}; +nimgs = numel(folderNames); + +% Extract theta values from folder names +PolarAngleVals = zeros(1, nimgs); +for k = 1:nimgs + tokens = regexp(folderNames{k}, 'theta_(\d{3})', 'tokens'); + if isempty(tokens) + warning('No theta found in folder name: %s', folderNames{k}); + PolarAngleVals(k) = NaN; + else + PolarAngleVals(k) = str2double(tokens{1}{1}); + end +end + +% Choose sort direction +sortDirection = 'ascend'; +if reverseOrder + sortDirection = 'descend'; +end + +% Sort folderNames based on polar angle +[~, sortIdx] = sort(PolarAngleVals, sortDirection); +folderNames = folderNames(sortIdx); +PolarAngleVals = PolarAngleVals(sortIdx); % Optional: if you still want sorted list + +imgs = cell(1, nimgs); +alphas = zeros(1, nimgs); + +for k = 1:nimgs + folderName = folderNames{k}; + SaveDirectory = fullfile(baseDir, folderName, runFolder); + + % Extract alpha (theta) again from folder name + tokens = regexp(folderName, 'theta_(\d{3})', 'tokens'); + alpha_val = str2double(tokens{1}{1}); + alphas(k) = alpha_val; + + matPath = fullfile(SaveDirectory, 'psi_gs.mat'); + if ~isfile(matPath) + warning('Missing psi_gs.mat in %s', SaveDirectory); + continue; + end + + try + Data = load(matPath, 'psi', 'Params', 'Transf', 'Observ'); + catch ME + warning('Failed to load %s: %s', matPath, ME.message); + continue; + end + + Params = Data.Params; + Transf = Data.Transf; + Observ = Data.Observ; + + psi = Data.psi; + if isgpuarray(psi) + psi = gather(psi); + end + if isgpuarray(Observ.residual) + Observ.residual = gather(Observ.residual); + end + + % Axes and projection + x = Transf.x * Params.l0 * 1e6; + y = Transf.y * Params.l0 * 1e6; + z = Transf.z * Params.l0 * 1e6; + dx = x(2)-x(1); dy = y(2)-y(1); dz = z(2)-z(1); + + % Calculate frequency increment (frequency axes) + Nx = length(x); % grid size along X + Ny = length(y); % grid size along Y + dx = mean(diff(x)); % real space increment in the X direction (in micrometers) + dy = mean(diff(y)); % real space increment in the Y direction (in micrometers) + dvx = 1 / (Nx * dx); % reciprocal space increment in the X direction (in micrometers^-1) + dvy = 1 / (Ny * dy); % reciprocal space increment in the Y direction (in micrometers^-1) + + % Create the frequency axes + vx = (-Nx/2:Nx/2-1) * dvx; % Frequency axis in X (micrometers^-1) + vy = (-Ny/2:Ny/2-1) * dvy; % Frequency axis in Y (micrometers^-1) + + % Calculate maximum frequencies + % kx_max = pi / dx; + % ky_max = pi / dy; + + % Generate reciprocal axes + % kx = linspace(-kx_max, kx_max * (Nx-2)/Nx, Nx); + % ky = linspace(-ky_max, ky_max * (Ny-2)/Ny, Ny); + + % Create the Wavenumber axes + kx = 2*pi*vx; % Wavenumber axis in X + ky = 2*pi*vy; % Wavenumber axis in Y + + n = abs(psi).^2; + nxy = squeeze(trapz(n * dz, 3)); + + imgs{k} = nxy; +end + +%% Analyze Images + + +makeMovie = true; % Set to false to disable movie creation +font = 'Bahnschrift'; + +skipPreprocessing = true; +skipMasking = true; +skipIntensityThresholding = true; +skipBinarization = true; + +% Run Fourier analysis over images + +fft_imgs = cell(1, nimgs); +spectral_contrast = zeros(1, nimgs); +spectral_weight = zeros(1, nimgs); +g2_all = cell(1, nimgs); +theta_values_all = cell(1, nimgs); + +N_bins = 180; +Threshold = 25; +Sigma = 2; + +if makeMovie + % Create VideoWriter object for movie + videoFile = VideoWriter(movieFileName, 'MPEG-4'); + videoFile.Quality = 100; % Set quality to maximum (0–100) + videoFile.FrameRate = 2; % Set the frame rate (frames per second) + open(videoFile); % Open the video file to write +end + +% Display the cropped image +for k = 1:nimgs + IMG = imgs{k}; + [IMGFFT, IMGPR] = computeFourierTransform(IMG, skipPreprocessing, skipMasking, skipIntensityThresholding, skipBinarization); + [theta_vals, S_theta] = computeNormalizedAngularSpectralDistribution(IMGFFT, 10, 35, N_bins, Threshold, Sigma); + + g2 = zeros(1, N_bins); % Preallocate + + for dtheta = 0:N_bins-1 + profile = S_theta; + profile_shifted = circshift(profile, -dtheta, 2); + + num = mean(profile .* profile_shifted); + denom = mean(profile)^2; + + g2(dtheta+1) = num / denom - 1; + end + + g2_all{k} = g2; + theta_values_all{k} = theta_vals; + + figure(1); + clf + set(gcf,'Position',[500 100 1000 800]) + t = tiledlayout(2, 2, 'TileSpacing', 'compact', 'Padding', 'compact'); % 1x4 grid + + y_min = min(y); + y_max = max(y); + x_min = min(x); + x_max = max(x); + + % Display the cropped OD image + ax1 = nexttile; + imagesc(x, y, IMG') + % Define normalized positions (relative to axis limits) + x_offset = 0.025; % 5% offset from the edges + y_offset = 0.025; % 5% offset from the edges + % Top-right corner (normalized axis coordinates) + hText = text(1 - x_offset, 1 - y_offset, ['Angle = ', num2str(alphas(k), '%.1f')], ... + 'Color', 'white', 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontSize', 20, 'Units', 'normalized', 'HorizontalAlignment', 'right', 'VerticalAlignment', 'top'); + axis square; + hcb = colorbar; + colormap(ax1, 'jet'); + set(gca, 'FontSize', 14); % For tick labels only + hL = ylabel(hcb, 'Optical Density'); + set(hL,'Rotation',-90); + set(gca,'YDir','normal') + % set(gca, 'YTick', linspace(y_min, y_max, 5)); % Define y ticks + % set(gca, 'YTickLabel', flip(linspace(y_min, y_max, 5))); % Flip only the labels + hXLabel = xlabel('x (pixels)', 'Interpreter', 'tex'); + hYLabel = ylabel('y (pixels)', 'Interpreter', 'tex'); + hTitle = title('Density', 'Interpreter', 'tex'); + set([hXLabel, hYLabel, hL, hText], 'FontName', font) + set([hXLabel, hYLabel, hL], 'FontSize', 14) + set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title + + % Plot the power spectrum + ax2 = nexttile; + [rows, cols] = size(IMGFFT); + zoom_size = 50; % Zoomed-in region around center + mid_x = floor(cols/2); + mid_y = floor(rows/2); + fft_imgs{k} = IMGFFT(mid_y-zoom_size:mid_y+zoom_size, mid_x-zoom_size:mid_x+zoom_size); + imagesc(log(1 + abs(fft_imgs{k}).^2)); + % Define normalized positions (relative to axis limits) + x_offset = 0.025; % 5% offset from the edges + y_offset = 0.025; % 5% offset from the edges + axis square; + hcb = colorbar; + colormap(ax2, 'jet'); + set(gca, 'FontSize', 14); % For tick labels only + set(gca,'YDir','normal') + hXLabel = xlabel('k_x', 'Interpreter', 'tex'); + hYLabel = ylabel('k_y', 'Interpreter', 'tex'); + hTitle = title('Power Spectrum - S(k_x,k_y)', 'Interpreter', 'tex'); + set([hXLabel, hYLabel, hText], 'FontName', font) + set([hXLabel, hYLabel], 'FontSize', 14) + set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title + + % Plot the angular distribution + nexttile + spectral_contrast(k) = computeSpectralContrast(fft_imgs{k}, 10, 25, Threshold); + [theta_vals, S_theta] = computeNormalizedAngularSpectralDistribution(fft_imgs{k}, 10, 25, N_bins, Threshold, Sigma); + spectral_weight(k) = trapz(theta_vals, S_theta); + plot(theta_vals/pi, S_theta,'Linewidth',2); + axis square; + set(gca, 'FontSize', 14); % For tick labels only + hXLabel = xlabel('\theta/\pi [rad]', 'Interpreter', 'tex'); + hYLabel = ylabel('Normalized magnitude (a.u.)', 'Interpreter', 'tex'); + hTitle = title('Angular Spectral Distribution - S(\theta)', 'Interpreter', 'tex'); + set([hXLabel, hYLabel, hText], 'FontName', font) + set([hXLabel, hYLabel], 'FontSize', 14) + set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title + grid on + + nexttile + plot(theta_vals/pi, g2, 'o-', 'LineWidth', 1.2, 'MarkerSize', 5); + set(gca, 'FontSize', 14); + ylim([-1.5 3.0]); % Set y-axis limits here + hXLabel = xlabel('$\delta\theta / \pi$', 'Interpreter', 'latex'); + hYLabel = ylabel('$g^{(2)}(\delta\theta)$', 'Interpreter', 'latex'); + hTitle = title('Autocorrelation', 'Interpreter', 'tex'); + set([hXLabel, hYLabel], 'FontName', font) + set([hXLabel, hYLabel], 'FontSize', 14) + set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title + grid on; + + if makeMovie + frame = getframe(gcf); + writeVideo(videoFile, frame); + else + pause(0.5); % Only pause when not recording + end + +end + +if makeMovie + close(videoFile); + disp(['Movie saved to ', movieFileName]); +end + +%% Track across the transition + +figure(2); +set(gcf,'Position',[100 100 950 750]) +plot(alphas, spectral_contrast, 'o--', ... + 'LineWidth', 1.5, 'MarkerSize', 6); +set(gca, 'FontSize', 14); % For tick labels only +hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); +% hXLabel = xlabel('B_z (G)', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Contrast', 'Interpreter', 'tex'); +hTitle = title(TitleString, 'Interpreter', 'tex'); +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on + +figure(3); +set(gcf,'Position',[100 100 950 750]) +plot(alphas, spectral_weight, 'o--', ... + 'LineWidth', 1.5, 'MarkerSize', 6); +set(gca, 'FontSize', 14); % For tick labels only +hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); +% hXLabel = xlabel('B_z (G)', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Weight', 'Interpreter', 'tex'); +hTitle = title(TitleString, 'Interpreter', 'tex'); +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on + +save(datafileName, 'alphas', 'spectral_contrast', 'spectral_weight'); + +figure(4); +clf; +set(gcf,'Position',[100 100 950 750]) +hold on; + +% Reconstruct theta axis from any one of the stored values +theta_vals = theta_values_all{1}; % assuming it's in radians + +legend_entries = cell(nimgs, 1); + +% Generate a colormap with enough unique colors +cmap = sky(nimgs); % You can also try 'jet', 'turbo', 'hot', etc. + +for i = 1:nimgs + plot(theta_vals/pi, g2_all{i}, ... + 'o-', 'Color', cmap(i,:), 'LineWidth', 1.2, ... + 'MarkerSize', 5); + legend_entries{i} = sprintf('$\\alpha = %g^\\circ$', alphas(i)); +end + +ylim([-1.5 3.0]); % Set y-axis limits here +set(gca, 'FontSize', 14); +hXLabel = xlabel('$\delta\theta / \pi$', 'Interpreter', 'latex'); +hYLabel = ylabel('$g^{(2)}(\delta\theta)$', 'Interpreter', 'latex'); +hTitle = title(TitleString, 'Interpreter', 'tex'); +legend(legend_entries, 'Interpreter', 'latex', 'Location', 'bestoutside'); +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on; + +%% Track across the transition + +set(0,'defaulttextInterpreter','latex') +set(groot, 'defaultAxesTickLabelInterpreter','latex'); set(groot, 'defaultLegendInterpreter','latex'); + +format long + +font = 'Bahnschrift'; + +% Load data +Data = load('./DropletsToStripes.mat', 'alphas', 'spectral_contrast', 'spectral_weight'); +dts_alphas = Data.alphas; +dts_sc = Data.spectral_contrast; +dts_sw = Data.spectral_weight; + +Data = load('./StripesToDroplets.mat', 'alphas', 'spectral_contrast', 'spectral_weight'); +std_alphas = Data.alphas; +std_sc = Data.spectral_contrast; +std_sw = Data.spectral_weight; + +% Normalize dts data +dts_min = min(dts_sw); +dts_max = max(dts_sw); +dts_range = dts_max - dts_min; +dts_sf_norm = (dts_sw - dts_min) / dts_range; + +% Normalize std data +std_min = min(std_sw); +std_max = max(std_sw); +std_range = std_max - std_min; +std_sf_norm = (std_sw - std_min) / std_range; + +figure(5); +set(gcf,'Position',[100 100 950 750]) +plot(dts_alphas, dts_sc, 'o--', 'LineWidth', 1.5, 'MarkerSize', 6, 'DisplayName' , 'Droplets to Stripes'); +hold on +plot(std_alphas, std_sc, 'o--', 'LineWidth', 1.5, 'MarkerSize', 6, 'DisplayName' , 'Stripes to Droplets'); +set(gca, 'FontSize', 14); % For tick labels only +hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Contrast', 'Interpreter', 'tex'); +hTitle = title('Change across transition', 'Interpreter', 'tex'); +legend +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on + +figure(6); +set(gcf,'Position',[100 100 950 750]) +plot(dts_alphas, dts_sw, 'o--', 'LineWidth', 1.5, 'MarkerSize', 6, 'DisplayName' , 'Droplets to Stripes'); +hold on +plot(std_alphas, std_sw, 'o--', 'LineWidth', 1.5, 'MarkerSize', 6, 'DisplayName' , 'Stripes to Droplets'); +set(gca, 'FontSize', 14); % For tick labels only +hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Weight', 'Interpreter', 'tex'); +hTitle = title('Change across transition', 'Interpreter', 'tex'); +legend +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on + +%% +function [IMGFFT, IMGPR] = computeFourierTransform(I, skipPreprocessing, skipMasking, skipIntensityThresholding, skipBinarization) + % computeFourierSpectrum - Computes the 2D Fourier power spectrum + % of binarized and enhanced lattice image features, with optional central mask. + % + % Inputs: + % I - Grayscale or RGB image matrix + % + % Output: + % F_mag - 2D Fourier power spectrum (shifted) + + if ~skipPreprocessing + % Preprocessing: Denoise + filtered = imgaussfilt(I, 10); + IMGPR = I - filtered; % adjust sigma as needed + else + IMGPR = I; + end + + if ~skipMasking + [rows, cols] = size(IMGPR); + [X, Y] = meshgrid(1:cols, 1:rows); + % Elliptical mask parameters + cx = cols / 2; + cy = rows / 2; + + % Shifted coordinates + x = X - cx; + y = Y - cy; + + % Ellipse semi-axes + rx = 0.4 * cols; + ry = 0.2 * rows; + + % Rotation angle in degrees -> radians + theta_deg = 30; % Adjust as needed + theta = deg2rad(theta_deg); + + % Rotated ellipse equation + cos_t = cos(theta); + sin_t = sin(theta); + + x_rot = (x * cos_t + y * sin_t); + y_rot = (-x * sin_t + y * cos_t); + + ellipseMask = (x_rot.^2) / rx^2 + (y_rot.^2) / ry^2 <= 1; + + % Apply cutout mask + IMGPR = IMGPR .* ellipseMask; + end + + if ~skipIntensityThresholding + % Apply global intensity threshold mask + intensity_thresh = 0.20; + intensity_mask = IMGPR > intensity_thresh; + IMGPR = IMGPR .* intensity_mask; + end + + if ~skipBinarization + % Adaptive binarization and cleanup + IMGPR = imbinarize(IMGPR, 'adaptive', 'Sensitivity', 0.0); + IMGPR = imdilate(IMGPR, strel('disk', 2)); + IMGPR = imerode(IMGPR, strel('disk', 1)); + IMGPR = imfill(IMGPR, 'holes'); + F = fft2(double(IMGPR)); % Compute 2D Fourier Transform + IMGFFT = abs(fftshift(F))'; % Shift zero frequency to center + else + F = fft2(double(IMGPR)); % Compute 2D Fourier Transform + IMGFFT = abs(fftshift(F))'; % Shift zero frequency to center + end +end + +function [theta_vals, S_theta] = computeNormalizedAngularSpectralDistribution(IMGFFT, r_min, r_max, num_bins, threshold, sigma) + % Apply threshold to isolate strong peaks + IMGFFT(IMGFFT < threshold) = 0; + + % Prepare polar coordinates + [ny, nx] = size(IMGFFT); + [X, Y] = meshgrid(1:nx, 1:ny); + cx = ceil(nx/2); + cy = ceil(ny/2); + R = sqrt((X - cx).^2 + (Y - cy).^2); + Theta = atan2(Y - cy, X - cx); % range [-pi, pi] + + % Choose radial band + radial_mask = (R >= r_min) & (R <= r_max); + + % Initialize the angular structure factor array + S_theta = zeros(1, num_bins); % Pre-allocate for 180 angle bins + % Define the angle values for the x-axis + theta_vals = linspace(0, pi, num_bins); + + % Loop through each angle bin + for i = 1:num_bins + angle_start = (i-1) * pi / num_bins; + angle_end = i * pi / num_bins; + + % Define a mask for the given angle range + angle_mask = (Theta >= angle_start & Theta < angle_end); + + bin_mask = radial_mask & angle_mask; + + % Extract the Fourier components for the given angle + fft_angle = IMGFFT .* bin_mask; + + % Integrate the Fourier components over the radius at the angle + S_theta(i) = sum(sum(abs(fft_angle).^2)); % sum of squared magnitudes + end + + % Create a 1D Gaussian kernel + half_width = ceil(3 * sigma); + x = -half_width:half_width; + gauss_kernel = exp(-x.^2 / (2 * sigma^2)); + gauss_kernel = gauss_kernel / sum(gauss_kernel); % normalize + + % Apply convolution (circular padding to preserve periodicity) + S_theta = conv([S_theta(end-half_width+1:end), S_theta, S_theta(1:half_width)], gauss_kernel, 'same'); + S_theta = S_theta(half_width+1:end-half_width); % crop back to original size + + % Normalize to 1 + S_theta = S_theta / max(S_theta); +end + +function contrast = computeSpectralContrast(IMGFFT, r_min, r_max, threshold) + % Apply threshold to isolate strong peaks + IMGFFT(IMGFFT < threshold) = 0; + + % Prepare polar coordinates + [ny, nx] = size(IMGFFT); + [X, Y] = meshgrid(1:nx, 1:ny); + cx = ceil(nx/2); + cy = ceil(ny/2); + R = sqrt((X - cx).^2 + (Y - cy).^2); + + % Ring region (annulus) mask + ring_mask = (R >= r_min) & (R <= r_max); + + % Squared magnitude in the ring + ring_power = abs(IMGFFT).^2 .* ring_mask; + + % Maximum power in the ring + ring_max = max(ring_power(:)); + + % Power at the DC component + dc_power = abs(IMGFFT(cy, cx))^2; + + % Avoid division by zero + if dc_power == 0 + contrast = Inf; % or NaN or 0, depending on how you want to handle this + else + contrast = ring_max / dc_power; + end +end diff --git a/Data-Analyzer/compareSpectralWeights.m b/Data-Analyzer/compareSpectralWeights.m index 94f075e..fd1e852 100644 --- a/Data-Analyzer/compareSpectralWeights.m +++ b/Data-Analyzer/compareSpectralWeights.m @@ -8,42 +8,63 @@ format long font = 'Bahnschrift'; % Load data -Data = load('C:/Users/Karthik/Documents/GitRepositories/Calculations/Data-Analyzer/B2.45G/DropletsToStripes.mat', 'unique_scan_parameter_values', 'mean_sf', 'stderr_sf'); +Data = load('D:/Results - Experiment/B2.45G/DropletsToStripes.mat', 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw'); dts_scan_parameter_values = Data.unique_scan_parameter_values; -dts_mean_sf = Data.mean_sf; -dts_stderr_sf = Data.stderr_sf; +dts_mean_sc = Data.mean_sc; +dts_stderr_sc = Data.stderr_sc; +dts_mean_sw = Data.mean_sw; +dts_stderr_sw = Data.stderr_sw; -Data = load('C:/Users/Karthik/Documents/GitRepositories/Calculations/Data-Analyzer/B2.45G/StripesToDroplets.mat', 'unique_scan_parameter_values', 'mean_sf', 'stderr_sf'); +Data = load('D:/Results - Experiment/B2.45G/StripesToDroplets.mat', 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw'); std_scan_parameter_values = Data.unique_scan_parameter_values; -std_mean_sf = Data.mean_sf; -std_stderr_sf = Data.stderr_sf; +std_mean_sw = Data.mean_sw; +std_stderr_sw = Data.stderr_sw; +std_mean_sc = Data.mean_sc; +std_stderr_sc = Data.stderr_sc; % Normalize dts data -dts_min = min(dts_mean_sf); -dts_max = max(dts_mean_sf); +dts_min = min(dts_mean_sw); +dts_max = max(dts_mean_sw); dts_range = dts_max - dts_min; -dts_mean_sf_norm = (dts_mean_sf - dts_min) / dts_range; -dts_stderr_sf_norm = dts_stderr_sf / dts_range; +dts_mean_sw_norm = (dts_mean_sw - dts_min) / dts_range; +dts_stderr_sw_norm = dts_stderr_sw / dts_range; % Normalize std data -std_min = min(std_mean_sf); -std_max = max(std_mean_sf); +std_min = min(std_mean_sw); +std_max = max(std_mean_sw); std_range = std_max - std_min; -std_mean_sf_norm = (std_mean_sf - std_min) / std_range; -std_stderr_sf_norm = std_stderr_sf / std_range; +std_mean_sw_norm = (std_mean_sw - std_min) / std_range; +std_stderr_sw_norm = std_stderr_sw / std_range; figure(1); set(gcf,'Position',[100 100 950 750]) -errorbar(dts_scan_parameter_values, dts_mean_sf_norm, dts_stderr_sf_norm, 'o--', ... +errorbar(dts_scan_parameter_values, dts_mean_sc, dts_stderr_sc, 'o--', ... 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 5, 'DisplayName' , 'Droplets to Stripes'); hold on -errorbar(std_scan_parameter_values, std_mean_sf_norm, std_stderr_sf_norm, 'o--', ... +errorbar(std_scan_parameter_values, std_mean_sc, std_stderr_sc, 'o--', ... 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 5, 'DisplayName', 'Stripes to Droplets'); set(gca, 'FontSize', 14); % For tick labels only hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); -hYLabel = ylabel('Normalized Spectral Weight', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Contrast', 'Interpreter', 'tex'); +hTitle = title('B = 2.45 G', 'Interpreter', 'tex'); +legend +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on + +figure(2); +set(gcf,'Position',[100 100 950 750]) +errorbar(dts_scan_parameter_values, dts_mean_sw, dts_stderr_sw, 'o--', ... + 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 5, 'DisplayName' , 'Droplets to Stripes'); +hold on +errorbar(std_scan_parameter_values, std_mean_sw, std_stderr_sw, 'o--', ... + 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 5, 'DisplayName', 'Stripes to Droplets'); +set(gca, 'FontSize', 14); % For tick labels only +hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Weight', 'Interpreter', 'tex'); hTitle = title('B = 2.45 G', 'Interpreter', 'tex'); legend set([hXLabel, hYLabel], 'FontName', font) diff --git a/Data-Analyzer/execution_scripts.m b/Data-Analyzer/execution_scripts.m index 653cfda..2fb647e 100644 --- a/Data-Analyzer/execution_scripts.m +++ b/Data-Analyzer/execution_scripts.m @@ -60,4 +60,4 @@ IMG = nxy; [psi, ratio, N] = computeBondOrderParameters(IMG); fprintf('Points: %d\n⟨|ψ₂|⟩ = %.3f, ⟨|ψ₄|⟩ = %.3f, ⟨|ψ₆|⟩ = %.3f\n', N, psi.psi2, psi.psi4, psi.psi6); -fprintf('(⟨|ψ₆|⟩ / ⟨|ψ₂|⟩) = %.3f\n', ratio); +fprintf('(⟨|ψ₆|⟩ / ⟨|ψ₂|⟩) = %.3f\n', ratio); \ No newline at end of file diff --git a/Data-Analyzer/extractAutocorrelation.m b/Data-Analyzer/extractAutocorrelation.m index 7e66f76..073ab11 100644 --- a/Data-Analyzer/extractAutocorrelation.m +++ b/Data-Analyzer/extractAutocorrelation.m @@ -198,150 +198,6 @@ set([hXLabel, hYLabel], 'FontSize', 14) set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title grid on; -%% Extract g2 from simulation data - -Data = load('E:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta0/HighN/aS_9.562000e+01_theta_000_phi_000_N_712500/Run_000/psi_gs.mat','psi','Params','Transf','Observ'); - -% Data = load('E:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta40/HighN/aS_9.562000e+01_theta_040_phi_000_N_508333/Run_000/psi_gs.mat','psi','Params','Transf','Observ'); - -Params = Data.Params; -Transf = Data.Transf; -Observ = Data.Observ; - -if isgpuarray(Data.psi) - psi = gather(Data.psi); -else - psi = Data.psi; -end -if isgpuarray(Data.Observ.residual) - Observ.residual = gather(Data.Observ.residual); -else - Observ.residual = Data.Observ.residual; -end - -% Axes scaling and coordinates in micrometers -x = Transf.x * Params.l0 * 1e6; -y = Transf.y * Params.l0 * 1e6; -z = Transf.z * Params.l0 * 1e6; - -dx = x(2)-x(1); dy = y(2)-y(1); dz = z(2)-z(1); - -% Calculate frequency increment (frequency axes) -Nx = length(x); % grid size along X -Ny = length(y); % grid size along Y -dx = mean(diff(x)); % real space increment in the X direction (in micrometers) -dy = mean(diff(y)); % real space increment in the Y direction (in micrometers) -dvx = 1 / (Nx * dx); % reciprocal space increment in the X direction (in micrometers^-1) -dvy = 1 / (Ny * dy); % reciprocal space increment in the Y direction (in micrometers^-1) - -% Create the frequency axes -vx = (-Nx/2:Nx/2-1) * dvx; % Frequency axis in X (micrometers^-1) -vy = (-Ny/2:Ny/2-1) * dvy; % Frequency axis in Y (micrometers^-1) - -% Calculate maximum frequencies -% kx_max = pi / dx; -% ky_max = pi / dy; - -% Generate reciprocal axes -% kx = linspace(-kx_max, kx_max * (Nx-2)/Nx, Nx); -% ky = linspace(-ky_max, ky_max * (Ny-2)/Ny, Ny); - -% Create the Wavenumber axes -kx = 2*pi*vx; % Wavenumber axis in X -ky = 2*pi*vy; % Wavenumber axis in Y - -% Compute probability density |psi|^2 -n = abs(psi).^2; - -nxz = squeeze(trapz(n*dy,2)); -nyz = squeeze(trapz(n*dx,1)); -nxy = squeeze(trapz(n*dz,3)); - -skipPreprocessing = true; -skipMasking = true; -skipIntensityThresholding = true; -skipBinarization = true; - -font = 'Bahnschrift'; -% Extract g2 - -N_bins = 90; -Threshold = 75; -Sigma = 2; - -IMG = nxy; - -[IMGFFT, IMGPR] = computeFourierTransform(IMG, skipPreprocessing, skipMasking, skipIntensityThresholding, skipBinarization); - -[theta_vals, S_theta] = computeNormalizedAngularSpectralDistribution(IMGFFT, 10, 35, N_bins, Threshold, Sigma); - -g2_all = zeros(1, N_bins); % Preallocate - -for dtheta = 0:N_bins-1 - profile = S_theta; - profile_shifted = circshift(profile, -dtheta, 2); - - num = mean(profile .* profile_shifted); - denom = mean(profile)^2; - - g2_all(dtheta+1) = num / denom - 1; -end - -figure(2); -clf -set(gcf,'Position',[500 100 1000 800]) -t = tiledlayout(2, 2, 'TileSpacing', 'compact', 'Padding', 'compact'); % 1x4 grid - -% Display the cropped OD image -nexttile -plotxy = pcolor(x,y,IMG'); -set(plotxy, 'EdgeColor', 'none'); -cbar1 = colorbar; -cbar1.Label.Interpreter = 'latex'; -colormap(gca, Helper.Colormaps.plasma()) -xlabel('$x$ ($\mu$m)', 'Interpreter', 'latex', 'FontSize', 14) -ylabel('$y$ ($\mu$m)', 'Interpreter', 'latex', 'FontSize', 14) -title('$|\Psi(x,y)|^2$', 'Interpreter', 'latex', 'FontSize', 14) - -% Plot the power spectrum -nexttile; -imagesc(kx, ky, log(1 + abs(IMGFFT).^2)); -axis square; -hcb = colorbar; -colormap(gca, Helper.Colormaps.plasma()) -set(gca, 'FontSize', 14); % For tick labels only -set(gca,'YDir','normal') -hXLabel = xlabel('k_x', 'Interpreter', 'tex'); -hYLabel = ylabel('k_y', 'Interpreter', 'tex'); -hTitle = title('Power Spectrum - S(k_x,k_y)', 'Interpreter', 'tex'); -set([hXLabel, hYLabel], 'FontName', font) -set([hXLabel, hYLabel], 'FontSize', 14) -set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title - -% Plot the angular distribution -nexttile -plot(theta_vals/pi, S_theta,'Linewidth',2); -set(gca, 'FontSize', 14); % For tick labels only -hXLabel = xlabel('\theta/\pi [rad]', 'Interpreter', 'tex'); -hYLabel = ylabel('Normalized magnitude (a.u.)', 'Interpreter', 'tex'); -hTitle = title('Angular Spectral Distribution - S(\theta)', 'Interpreter', 'tex'); -set([hXLabel, hYLabel], 'FontName', font) -set([hXLabel, hYLabel], 'FontSize', 14) -set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title -grid on - -nexttile -plot(theta_vals/pi, g2_all, 'o-', 'LineWidth', 1.2, 'MarkerSize', 5); -set(gca, 'FontSize', 14); -ylim([-1.5 3.0]); % Set y-axis limits here -hXLabel = xlabel('$\delta\theta / \pi$', 'Interpreter', 'latex'); -hYLabel = ylabel('$g^{(2)}(\delta\theta)$', 'Interpreter', 'latex'); -hTitle = title('Autocorrelation', 'Interpreter', 'tex'); -set([hXLabel, hYLabel], 'FontName', font) -set([hXLabel, hYLabel], 'FontSize', 14) -set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title -grid on; - %% Helper Functions function [IMGFFT, IMGPR] = computeFourierTransform(I, skipPreprocessing, skipMasking, skipIntensityThresholding, skipBinarization) % computeFourierSpectrum - Computes the 2D Fourier power spectrum diff --git a/Data-Analyzer/extractSpectralWeight.m b/Data-Analyzer/extractSpectralWeight.m index 526838a..accaf48 100644 --- a/Data-Analyzer/extractSpectralWeight.m +++ b/Data-Analyzer/extractSpectralWeight.m @@ -6,7 +6,7 @@ groupList = ["/images/MOT_3D_Camera/in_situ_absorption", "/images/ODT_1_Axi folderPath = "D:/Data - Experiment/2025/05/22/"; -run = '0078'; +run = '0079'; folderPath = strcat(folderPath, run); @@ -25,7 +25,9 @@ scan_parameter = 'rot_mag_fin_pol_angle'; scan_parameter_text = 'Angle = '; % scan_parameter_text = 'BField = '; -font = 'Bahnschrift'; +savefodlerPath = 'D:/Results - Experiment/B2.45G/'; +savefileName = 'StripesToDroplets.mat'; +font = 'Bahnschrift'; skipPreprocessing = true; skipMasking = true; @@ -96,6 +98,7 @@ end %% Run Fourier analysis over images fft_imgs = cell(1, nimgs); +spectral_contrast = zeros(1, nimgs); spectral_weight = zeros(1, nimgs); N_bins = 180; @@ -197,6 +200,7 @@ for k = 1:N_shots % Plot the angular distribution nexttile + spectral_contrast(k) = computeSpectralContrast(fft_imgs{k}, 10, 25, Threshold); [theta_vals, S_theta] = computeNormalizedAngularSpectralDistribution(fft_imgs{k}, 10, 20, N_bins, Threshold, Sigma); spectral_weight(k) = trapz(theta_vals, S_theta); plot(theta_vals/pi, S_theta,'Linewidth',2); @@ -220,25 +224,51 @@ end % Close the video file close(videoFile); -%% Track spectral weight across the transition +%% Track across the transition % Assuming scan_parameter_values and spectral_weight are column vectors (or row vectors of same length) [unique_scan_parameter_values, ~, idx] = unique(scan_parameter_values); % Preallocate arrays -mean_sf = zeros(size(unique_scan_parameter_values)); -stderr_sf = zeros(size(unique_scan_parameter_values)); +mean_sc = zeros(size(unique_scan_parameter_values)); +stderr_sc = zeros(size(unique_scan_parameter_values)); % Loop through each unique theta and compute mean and standard error for i = 1:length(unique_scan_parameter_values) - group_vals = spectral_weight(idx == i); - mean_sf(i) = mean(group_vals); - stderr_sf(i) = std(group_vals) / sqrt(length(group_vals)); % standard error = std / sqrt(N) + group_vals = spectral_contrast(idx == i); + mean_sc(i) = mean(group_vals); + stderr_sc(i) = std(group_vals) / sqrt(length(group_vals)); % standard error = std / sqrt(N) end figure(2); set(gcf,'Position',[100 100 950 750]) -errorbar(unique_scan_parameter_values, mean_sf, stderr_sf, 'o--', ... +errorbar(unique_scan_parameter_values, mean_sc, stderr_sc, 'o--', ... + 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 5); +set(gca, 'FontSize', 14); % For tick labels only +hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); +% hXLabel = xlabel('B_z (G)', 'Interpreter', 'tex'); +hYLabel = ylabel('Spectral Contrast', 'Interpreter', 'tex'); +hTitle = title('Change across transition', 'Interpreter', 'tex'); +set([hXLabel, hYLabel], 'FontName', font) +set([hXLabel, hYLabel], 'FontSize', 14) +set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title +grid on + + +% Preallocate arrays +mean_sw = zeros(size(unique_scan_parameter_values)); +stderr_sw = zeros(size(unique_scan_parameter_values)); + +% Loop through each unique theta and compute mean and standard error +for i = 1:length(unique_scan_parameter_values) + group_vals = spectral_weight(idx == i); + mean_sw(i) = mean(group_vals); + stderr_sw(i) = std(group_vals) / sqrt(length(group_vals)); % standard error = std / sqrt(N) +end + +figure(3); +set(gcf,'Position',[100 100 950 750]) +errorbar(unique_scan_parameter_values, mean_sw, stderr_sw, 'o--', ... 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 5); set(gca, 'FontSize', 14); % For tick labels only hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); @@ -250,6 +280,8 @@ set([hXLabel, hYLabel], 'FontSize', 14) set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title grid on +save([savefolderPath savefileName], 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw'); + %% k-means Clustering % Reshape to column vector @@ -433,6 +465,37 @@ function [theta_vals, S_theta] = computeNormalizedAngularSpectralDistribution(IM S_theta = S_theta / max(S_theta); end +function contrast = computeSpectralContrast(IMGFFT, r_min, r_max, threshold) + % Apply threshold to isolate strong peaks + IMGFFT(IMGFFT < threshold) = 0; + + % Prepare polar coordinates + [ny, nx] = size(IMGFFT); + [X, Y] = meshgrid(1:nx, 1:ny); + cx = ceil(nx/2); + cy = ceil(ny/2); + R = sqrt((X - cx).^2 + (Y - cy).^2); + + % Ring region (annulus) mask + ring_mask = (R >= r_min) & (R <= r_max); + + % Squared magnitude in the ring + ring_power = abs(IMGFFT).^2 .* ring_mask; + + % Maximum power in the ring + ring_max = max(ring_power(:)); + + % Power at the DC component + dc_power = abs(IMGFFT(cy, cx))^2; + + % Avoid division by zero + if dc_power == 0 + contrast = Inf; % or NaN or 0, depending on how you want to handle this + else + contrast = ring_max / dc_power; + end +end + function ret = getBkgOffsetFromCorners(img, x_fraction, y_fraction) % image must be a 2D numerical array [dim1, dim2] = size(img); diff --git a/Data-Analyzer/matchTFRadii.m b/Data-Analyzer/matchTFRadii.m new file mode 100644 index 0000000..8b5d4d2 --- /dev/null +++ b/Data-Analyzer/matchTFRadii.m @@ -0,0 +1,164 @@ +% ---------------------------- +% Experimental data +% ---------------------------- +PixelSize = 5.86; % microns + +AtomNumbers = [9.14950197, 8.6845907 , 8.82521245, 8.5899089 , 8.21675841, ... + 8.96234044, 8.8636914 , 8.70332154, 8.82930706, 8.91869919, ... + 8.58553165, 8.73391981, 8.71943552, 8.11717678, 8.59490351, ... + 8.57514491, 8.81628891, 8.37211343, 8.76077699, 8.71297796, ... + 9.17634469, 8.81424285, 8.61176745, 8.40555897, 8.97137861, ... + 8.88393124, 8.66625724, 8.30688943, 9.02338201, 8.57729816, ... + 8.50333458, 8.67617084, 8.8936879 , 9.02031475, 8.98459233, ... + 8.76525048, 8.76801503, 8.58302559, 8.4617431 , 8.74479855, ... + 8.83882896, 8.69091377, 8.79282459, 8.51785483, 8.75629649, ... + 8.58994308, 8.36816564, 9.2429294 , 8.6583425 , 8.55827961]; + +EstimatedAtomNumber = mean(AtomNumbers) * 1E4; + +TF_Radii_X_pixels = [48.44308968, 46.01326593, 46.45950681, 46.41644117, 45.56176919, ... + 46.60816438, 46.85307478, 47.61086543, 46.66687703, 46.17986721, ... + 46.67877165, 46.07789481, 46.42285497, 46.22167708, 45.95144492, ... + 47.05400117, 49.03005788, 45.84588659, 46.85742777, 45.9824117 , ... + 47.14731188, 47.4984484 , 45.9055646 , 47.31804553, 47.52321888, ... + 47.76823968, 46.459749 , 45.4498851 , 45.38339308, 46.68736642, ... + 45.76607233, 48.1796053 , 46.94291541, 47.54092708, 48.26130406, ... + 47.44092616, 48.73463214, 46.39356452, 48.74120217, 45.57014182, ... + 47.56467835, 46.62867035, 46.62322802, 46.03032919, 44.78559832, ... + 46.31282562, 46.83537518, 47.68015029, 47.71093571, 47.34079816]; + +TF_Radii_Y_pixels = [113.52610841, 113.68862761, 112.84031747, 114.22062324, ... + 112.45378285, 114.53863928, 111.39181472, 112.67024271, ... + 113.65387448, 113.57576769, 110.22576589, 110.45091803, ... + 109.97966067, 112.84785553, 109.3836049 , 111.22290862, ... + 111.17028727, 110.71088554, 111.72973603, 112.39623635, ... + 113.18160954, 112.00016346, 109.66542778, 111.98705097, ... + 112.35983901, 110.21703075, 112.14565939, 111.2029942 , ... + 110.74296 , 112.56607054, 112.58015318, 111.93031032, ... + 111.59774288, 112.30723266, 112.79543793, 111.08288891, ... + 113.85269603, 111.77349741, 113.58639434, 111.28694353, ... + 112.1993445 , 111.72215918, 111.93271101, 112.17593036, ... + 110.82246602, 113.61806907, 114.13693144, 114.27245731, ... + 114.24223538, 112.61704196]; + +% ---------------------------- +% Load simulation data for fitting +% ---------------------------- +% baseDir = 'D:\Results - Numerics\Data_Full3D\PhaseDiagram\TFRadii\LowN'; +baseDir = 'C:\Users\Karthik\Documents\GitRepositories\Calculations\Estimations\ThomasFermiRadius'; +refData = load(fullfile(baseDir, 'TFFermi_Theta0.mat')); + +% ---------------------------- +% Find simulation values at the estimated atom number +% ---------------------------- +[~, idxClosest] = min(abs(refData.NUM_ATOMS_LIST - EstimatedAtomNumber)); + +if ndims(refData.TF_Radii) > 2 + TF_Radii = squeeze(refData.TF_Radii); + TF_X_target = TF_Radii(idxClosest, 1); + TF_Y_target = TF_Radii(idxClosest, 2); +else + TF_X_target = refData.TF_Radii(idxClosest, 1); + TF_Y_target = refData.TF_Radii(idxClosest, 2); +end + +fprintf('Target radii from simulation at N = %.0f:\n', refData.NUM_ATOMS_LIST(idxClosest)); +fprintf('TF_X_target = %.2f µm\n', TF_X_target); +fprintf('TF_Y_target = %.2f µm\n', TF_Y_target); + +% ---------------------------- +% Find optimal magnification +% ---------------------------- +errorFunc = @(mag) ... + (mean(TF_Radii_X_pixels)*PixelSize/mag - TF_X_target)^2 + ... + (mean(TF_Radii_Y_pixels)*PixelSize/mag - TF_Y_target)^2; + +Magnification = fminbnd(errorFunc, 10, 50); +fprintf('Best-fit magnification: %.4f\n', Magnification); + +% ---------------------------- +% Convert to real space and get stats +% ---------------------------- +TF_Radii_X_Real = TF_Radii_X_pixels * PixelSize / Magnification; +TF_Radii_Y_Real = TF_Radii_Y_pixels * PixelSize / Magnification; + +Avg_X = mean(TF_Radii_X_Real); +Avg_Y = mean(TF_Radii_Y_Real); +Std_X = std(TF_Radii_X_Real); +Std_Y = std(TF_Radii_Y_Real); + +fprintf('TF Radius X = %.2f ± %.2f µm\n', Avg_X, Std_X); +fprintf('TF Radius Y = %.2f ± %.2f µm\n', Avg_Y, Std_Y); + +% ---------------------------- +% Plotting +% ---------------------------- +fileList = {'TFFermi_Theta0.mat'}; +thetaLabels = {'\theta = 0^\circ', '\theta = 20^\circ', '\theta = 40^\circ'}; + +fig = figure(1); clf; +set(gcf,'Position', [100, 100, 1200, 500]) +t = tiledlayout(1, 2, 'TileSpacing', 'compact', 'Padding', 'compact'); +colors = lines(length(fileList)); +legendEntries = cell(1, length(fileList)); + +for j = 1:length(fileList) + data = load(fullfile(baseDir, fileList{j})); + + aS = data.SCATTERING_LENGTH_RANGE; + NUM_ATOMS_LIST = data.NUM_ATOMS_LIST; + if ndims(data.TF_Radii) > 2 + TF_Radii = squeeze(data.TF_Radii); + else + TF_Radii = data.TF_Radii; + end + + legendEntries{j} = sprintf('%s, a_s = %.2f a_0', thetaLabels{j}, aS); + + % Rx + nexttile(1); + plot(NUM_ATOMS_LIST, TF_Radii(:,1), '-', ... + 'Color', colors(j,:), 'LineWidth', 1.5, ... + 'DisplayName', legendEntries{j}); hold on; + + % Ry + nexttile(2); + plot(NUM_ATOMS_LIST, TF_Radii(:,2), '-', ... + 'Color', colors(j,:), 'LineWidth', 1.5, ... + 'DisplayName', legendEntries{j}); hold on; +end + +% ---------------------------- +% Add experimental point w/ error bars and annotation +% ---------------------------- +% TF Radius X +nexttile(1); +errorbar(EstimatedAtomNumber, Avg_X, Std_X, ... + 'd', 'MarkerSize', 8, 'MarkerFaceColor', [0.2 0.2 0.8], ... + 'MarkerEdgeColor', 'k', 'Color', 'k', 'LineWidth', 1.2, ... + 'DisplayName', '\theta = 0^\circ, Experimental Value'); + +% TF Radius Y +nexttile(2); +errorbar(EstimatedAtomNumber, Avg_Y, Std_Y, ... + 'd', 'MarkerSize', 8, 'MarkerFaceColor', [0.2 0.2 0.8], ... + 'MarkerEdgeColor', 'k', 'Color', 'k', 'LineWidth', 1.2, ... + 'DisplayName', '\theta = 0^\circ, Experimental Value'); + +% ---------------------------- +% Finalize +% ---------------------------- +nexttile(1); +xlabel('Number of Atoms', 'FontSize', 16); +ylabel('TF Radius - X ($\mu$m)', 'Interpreter', 'latex', 'FontSize', 16); +legend('FontSize', 12, 'Interpreter', 'tex', 'Location', 'bestoutside'); +axis square; grid on; + +nexttile(2); +xlabel('Number of Atoms', 'FontSize', 16); +ylabel('TF Radius - Y ($\mu$m)', 'Interpreter', 'latex', 'FontSize', 16); +legend('FontSize', 12, 'Interpreter', 'tex', 'Location', 'bestoutside'); +axis square; grid on; + +sgtitle('[ \omega_x, \omega_y, \omega_z ] = 2 \pi \times [ 50, 20, 150 ] Hz', ... + 'Interpreter', 'tex', 'FontSize', 18); diff --git a/Dipolar-Gas-Simulator/+Scripts/run_locally.m b/Dipolar-Gas-Simulator/+Scripts/run_locally.m index 75ff163..c41a1aa 100644 --- a/Dipolar-Gas-Simulator/+Scripts/run_locally.m +++ b/Dipolar-Gas-Simulator/+Scripts/run_locally.m @@ -573,9 +573,14 @@ JobNumber = 0; Plotter.visualizeGSWavefunction(SaveDirectory, JobNumber) %% -SaveDirectory = 'D:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta0/HighN/aS_9.562000e+01_theta_000_phi_000_N_712500'; +SaveDirectory = 'D:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta0/HighN/aS_9.562000e+01_theta_000_phi_000_N_1733333'; JobNumber = 0; Plotter.visualizeGSWavefunction(SaveDirectory, JobNumber) +%% +SaveDirectory = 'D:/Results - Numerics/Data_Full3D/PhaseTransition/STD/aS_9.562000e+01_theta_025_phi_000_N_500000'; +JobNumber = 0; +Plotter.visualizeGSWavefunction(SaveDirectory, JobNumber) + %% Identify and count droplets Radius = 2; % The radius within which peaks will be considered duplicates @@ -591,7 +596,7 @@ PeakThreshold = 3E3; SaveDirectory = 'D:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta0/HighN/aS_9.562000e+01_theta_000_phi_000_N_712500'; JobNumber = 0; SuppressPlotFlag = false; -AveragePCD = Scripts.extractAveragePeakColumnDensity(SaveDirectory, JobNumber, Radius, PeakThreshold, SuppressPlotFlag); +AveragePCD = Scripts.extractAveragePeakColumnDensity(SaveDirectory, JobNumber, Radius, PeakThreshold, SuppressPlotFlag); %% Extract average unit cell density - Droplets Radius = 2; % The radius within which peaks will be considered duplicates @@ -604,7 +609,7 @@ UCD = Scripts.extractAverageUnitCellDensity(SaveDirectory, J %% Extract average unit cell density - Stripes Radius = 2; % The radius within which peaks will be considered duplicates PeakThreshold = 3E3; -SaveDirectory = 'D:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta0/HighN/aS_9.562000e+01_theta_000_phi_000_N_1529167'; +SaveDirectory = 'D:/Results - Numerics/Data_Full3D/PhaseDiagram/ImagTimePropagation/Theta0/HighN/aS_9.562000e+01_theta_000_phi_000_N_1325000'; JobNumber = 0; SuppressPlotFlag = false; UCD = Scripts.extractAverageUnitCellDensity(SaveDirectory, JobNumber, Radius, PeakThreshold, SuppressPlotFlag); @@ -766,10 +771,10 @@ xlabel(inset_ax, 'N', 'FontSize', 9); ylabel(inset_ax, 'CD', 'FontSize', 9); %% Plot average unit cell density -Radius = 2; -PeakThreshold = 3E3; -JobNumber = 0; -SuppressPlotFlag = true; % Suppress plots during batch processing +Radius = 2; +PeakThreshold = 3E3; +JobNumber = 0; +SuppressPlotFlag = true; % Suppress plots during batch processing TitleString = "[ \omega_x, \omega_y, \omega_z ] = 2 \pi \times [ 50, 20, 150 ] Hz; \theta = 0^\circ"; @@ -777,7 +782,7 @@ SCATTERING_LENGTH_RANGE = [95.62]; NUM_ATOMS_LIST = [712500 916667 1120833 1325000 1529167 1733333 1937500 2141667 2345833 2550000 2754167 2958333 3162500 3366667 3570833]; -UCD_values = zeros(length(SCATTERING_LENGTH_RANGE), length(NUM_ATOMS_LIST)); +UCD_values = zeros(length(SCATTERING_LENGTH_RANGE), length(NUM_ATOMS_LIST)); % Prepare figure figure(1); @@ -824,6 +829,32 @@ legend(arrayfun(@(aS) sprintf('a_s = %.2f a_0', aS), SCATTERING_LENGTH_RANGE, .. set(gca, 'FontSize', 14); grid on; +% Physical constants +PlanckConstant = 6.62607015E-34; +PlanckConstantReduced = 6.62607015E-34/(2*pi); +AtomicMassUnit = 1.660539066E-27; +BohrMagneton = 9.274009994E-24; + +% Dy specific constants +Dy164Mass = 163.929174751*AtomicMassUnit; +Dy164IsotopicAbundance = 0.2826; +DyMagneticMoment = 9.93*BohrMagneton; + +add = VacuumPermeability*DyMagneticMoment^2*Dy164Mass/(12*pi*PlanckConstantReduced^2); % Dipole length +nadd2s = 0.01:0.01:0.25; +ppmum = nadd2s.*(1E12*add^2)^-1; +% +figure(2); +clf; +set(gcf,'Position', [100, 100, 850, 700]); +hold on +plot(nadd2s, ppmum, 'o-', 'LineWidth', 1.5) +xlabel('na_{dd}^2', 'Interpreter', 'tex', 'FontSize', 16); +ylabel('Unit Cell Density (UCD) [$\mu m^{-2}$]', 'Interpreter', 'latex', 'FontSize', 16); +title("[ \omega_x, \omega_y, \omega_z ] = 2 \pi \times [ 0, 0, 72.4 ] Hz; \theta = 0^\circ", 'Interpreter', 'tex', 'FontSize', 18); +set(gca, 'FontSize', 14); +grid on; + %% Plot TF radii of unmodulated states % Parameters JobNumber = 0;