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New script to plot SS regimes and mods to analyze new data

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This commit is contained in:
Karthik 2025-06-26 21:45:23 +02:00
parent dce4a0f067
commit d874270a62
7 changed files with 498 additions and 27 deletions
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8
Data-Analyzer/compareSpectralWeights.m
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@ -8,7 +8,7 @@ format long
font = 'Bahnschrift'; font = 'Bahnschrift';
% Load data % Load data
Data = load('D:/Results - Experiment/B2.45G/DropletsToStripes.mat', 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw'); Data = load('D:/Results - Experiment/B2.42G/DropletsToStripes.mat', 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw');
dts_scan_parameter_values = Data.unique_scan_parameter_values; dts_scan_parameter_values = Data.unique_scan_parameter_values;
dts_mean_sc = Data.mean_sc; dts_mean_sc = Data.mean_sc;
@ -16,7 +16,7 @@ dts_stderr_sc = Data.stderr_sc;
dts_mean_sw = Data.mean_sw; dts_mean_sw = Data.mean_sw;
dts_stderr_sw = Data.stderr_sw; dts_stderr_sw = Data.stderr_sw;
Data = load('D:/Results - Experiment/B2.45G/StripesToDroplets.mat', 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw'); Data = load('D:/Results - Experiment/B2.42G/StripesToDroplets.mat', 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw');
std_scan_parameter_values = Data.unique_scan_parameter_values; std_scan_parameter_values = Data.unique_scan_parameter_values;
std_mean_sw = Data.mean_sw; std_mean_sw = Data.mean_sw;
@ -48,7 +48,7 @@ errorbar(std_scan_parameter_values, std_mean_sc, std_stderr_sc, 'o--', ...
set(gca, 'FontSize', 14); % For tick labels only set(gca, 'FontSize', 14); % For tick labels only
hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex');
hYLabel = ylabel('Spectral Contrast', 'Interpreter', 'tex'); hYLabel = ylabel('Spectral Contrast', 'Interpreter', 'tex');
hTitle = title('B = 2.45 G', 'Interpreter', 'tex'); hTitle = title('B = 2.42 G', 'Interpreter', 'tex');
legend legend
set([hXLabel, hYLabel], 'FontName', font) set([hXLabel, hYLabel], 'FontName', font)
set([hXLabel, hYLabel], 'FontSize', 14) set([hXLabel, hYLabel], 'FontSize', 14)
@ -65,7 +65,7 @@ errorbar(std_scan_parameter_values, std_mean_sw, std_stderr_sw, 'o--', ...
set(gca, 'FontSize', 14); % For tick labels only set(gca, 'FontSize', 14); % For tick labels only
hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex'); hXLabel = xlabel('\alpha (degrees)', 'Interpreter', 'tex');
hYLabel = ylabel('Spectral Weight', 'Interpreter', 'tex'); hYLabel = ylabel('Spectral Weight', 'Interpreter', 'tex');
hTitle = title('B = 2.45 G', 'Interpreter', 'tex'); hTitle = title('B = 2.42 G', 'Interpreter', 'tex');
legend legend
set([hXLabel, hYLabel], 'FontName', font) set([hXLabel, hYLabel], 'FontName', font)
set([hXLabel, hYLabel], 'FontSize', 14) set([hXLabel, hYLabel], 'FontSize', 14)

12
Data-Analyzer/extractAutocorrelation.m
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@ -4,27 +4,29 @@ groupList = ["/images/MOT_3D_Camera/in_situ_absorption", "/images/ODT_1_Axi
"/images/ODT_2_Axis_Camera/in_situ_absorption", "/images/Horizontal_Axis_Camera/in_situ_absorption", ... "/images/ODT_2_Axis_Camera/in_situ_absorption", "/images/Horizontal_Axis_Camera/in_situ_absorption", ...
"/images/Vertical_Axis_Camera/in_situ_absorption"]; "/images/Vertical_Axis_Camera/in_situ_absorption"];
folderPath = "E:/Data - Experiment/2025/05/22/"; folderPath = "//DyLabNAS/Data/TwoDGas/2025/06/23/";
run = '0078'; run = '0300';
folderPath = strcat(folderPath, run); folderPath = strcat(folderPath, run);
cam = 5; cam = 5;
angle = 0; angle = 0;
center = [1375, 2020]; center = [1410, 2030];
span = [200, 200]; span = [200, 200];
fraction = [0.1, 0.1]; fraction = [0.1, 0.1];
pixel_size = 5.86e-6; pixel_size = 5.86e-6;
removeFringes = false; removeFringes = false;
scan_parameter = 'rot_mag_fin_pol_angle'; scan_parameter = 'ps_rot_mag_fin_pol_angle';
% scan_parameter = 'rot_mag_field'; % scan_parameter = 'rot_mag_field';
scan_parameter_text = 'Angle = '; scan_parameter_text = 'Angle = ';
% scan_parameter_text = 'BField = '; % scan_parameter_text = 'BField = ';
savefolderPath = 'D:/Results - Experiment/B2.42G/';
savefileName = 'DropletsToStripes.mat';
font = 'Bahnschrift'; font = 'Bahnschrift';
skipPreprocessing = true; skipPreprocessing = true;
@ -191,7 +193,7 @@ ylim([-1.5 3.0]); % Set y-axis limits here
set(gca, 'FontSize', 14); set(gca, 'FontSize', 14);
hXLabel = xlabel('$\delta\theta / \pi$', 'Interpreter', 'latex'); hXLabel = xlabel('$\delta\theta / \pi$', 'Interpreter', 'latex');
hYLabel = ylabel('$g^{(2)}(\delta\theta)$', 'Interpreter', 'latex'); hYLabel = ylabel('$g^{(2)}(\delta\theta)$', 'Interpreter', 'latex');
hTitle = title('B = 2.45 G - Droplets to Stripes', 'Interpreter', 'tex'); hTitle = title('Change across transition', 'Interpreter', 'tex');
legend(legend_entries, 'Interpreter', 'latex', 'Location', 'bestoutside'); legend(legend_entries, 'Interpreter', 'latex', 'Location', 'bestoutside');
set([hXLabel, hYLabel], 'FontName', font) set([hXLabel, hYLabel], 'FontName', font)
set([hXLabel, hYLabel], 'FontSize', 14) set([hXLabel, hYLabel], 'FontSize', 14)

62
Data-Analyzer/extractSpectralWeight.m
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@ -4,31 +4,38 @@ groupList = ["/images/MOT_3D_Camera/in_situ_absorption", "/images/ODT_1_Axi
"/images/ODT_2_Axis_Camera/in_situ_absorption", "/images/Horizontal_Axis_Camera/in_situ_absorption", ... "/images/ODT_2_Axis_Camera/in_situ_absorption", "/images/Horizontal_Axis_Camera/in_situ_absorption", ...
"/images/Vertical_Axis_Camera/in_situ_absorption"]; "/images/Vertical_Axis_Camera/in_situ_absorption"];
folderPath = "D:/Data - Experiment/2025/05/22/"; folderPath = "//DyLabNAS/Data/TwoDGas/2025/06/24/";
run = '0079'; run = '0001';
folderPath = strcat(folderPath, run); folderPath = strcat(folderPath, run);
cam = 5; cam = 5;
angle = 0; angle = 0;
center = [1375, 2020]; center = [1410, 2030];
span = [200, 200]; span = [200, 200];
fraction = [0.1, 0.1]; fraction = [0.1, 0.1];
pixel_size = 5.86e-6; pixel_size = 5.86e-6;
removeFringes = false; removeFringes = false;
scan_parameter = 'rot_mag_fin_pol_angle'; scan_parameter = 'ps_rot_mag_fin_pol_angle';
% scan_parameter = 'rot_mag_field'; % scan_parameter = 'rot_mag_field';
scan_parameter_text = 'Angle = '; scan_parameter_text = 'Angle = ';
% scan_parameter_text = 'BField = '; % scan_parameter_text = 'BField = ';
savefodlerPath = 'D:/Results - Experiment/B2.45G/'; savefolderPath = 'D:/Results - Experiment/B2.42G/';
savefileName = 'StripesToDroplets.mat'; savefileName = 'StripesToDroplets';
font = 'Bahnschrift'; font = 'Bahnschrift';
skipUnshuffling = false;
if strcmp(savefileName, 'DropletsToStripes')
scan_groups = 0:5:45;
else
scan_groups = 45:-5:0;
end
skipPreprocessing = true; skipPreprocessing = true;
skipMasking = true; skipMasking = true;
skipIntensityThresholding = true; skipIntensityThresholding = true;
@ -86,7 +93,7 @@ for k = 1 : length(files)
info = h5info(fullFileName, '/globals'); info = h5info(fullFileName, '/globals');
for i = 1:length(info.Attributes) for i = 1:length(info.Attributes)
if strcmp(info.Attributes(i).Name, scan_parameter) if strcmp(info.Attributes(i).Name, scan_parameter)
if strcmp(scan_parameter, 'rot_mag_fin_pol_angle') if strcmp(scan_parameter, 'ps_rot_mag_fin_pol_angle')
scan_parameter_values(k) = 180 - info.Attributes(i).Value; scan_parameter_values(k) = 180 - info.Attributes(i).Value;
else else
scan_parameter_values(k) = info.Attributes(i).Value; scan_parameter_values(k) = info.Attributes(i).Value;
@ -95,6 +102,43 @@ for k = 1 : length(files)
end end
end end
%% Unshuffle if necessary to do so
if ~skipUnshuffling
n_values = length(scan_groups);
n_total = length(scan_parameter_values);
% Infer number of repetitions
n_reps = n_total / n_values;
% Preallocate ordered arrays
ordered_scan_values = zeros(1, n_total);
ordered_od_imgs = cell(1, n_total);
counter = 1;
for rep = 1:n_reps
for val = scan_groups
% Find the next unused match for this val
idx = find(scan_parameter_values == val, 1, 'first');
% Assign and remove from list to avoid duplicates
ordered_scan_values(counter) = scan_parameter_values(idx);
ordered_od_imgs{counter} = od_imgs{idx};
% Mark as used by removing
scan_parameter_values(idx) = NaN; % NaN is safe since original values are 0:5:45
od_imgs{idx} = []; % empty cell so it won't be matched again
counter = counter + 1;
end
end
% Now assign back
scan_parameter_values = ordered_scan_values;
od_imgs = ordered_od_imgs;
end
%% Run Fourier analysis over images %% Run Fourier analysis over images
fft_imgs = cell(1, nimgs); fft_imgs = cell(1, nimgs);
@ -107,7 +151,7 @@ Sigma = 2;
N_shots = length(od_imgs); N_shots = length(od_imgs);
% Create VideoWriter object for movie % Create VideoWriter object for movie
videoFile = VideoWriter('Single_Shot_FFT.mp4', 'MPEG-4'); videoFile = VideoWriter([savefileName '.mp4'], 'MPEG-4');
videoFile.Quality = 100; % Set quality to maximum (0–100) videoFile.Quality = 100; % Set quality to maximum (0–100)
videoFile.FrameRate = 2; % Set the frame rate (frames per second) videoFile.FrameRate = 2; % Set the frame rate (frames per second)
open(videoFile); % Open the video file to write open(videoFile); % Open the video file to write
@ -280,7 +324,7 @@ set([hXLabel, hYLabel], 'FontSize', 14)
set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title
grid on grid on
save([savefolderPath savefileName], 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw'); save([savefolderPath savefileName '.mat'], 'unique_scan_parameter_values', 'mean_sc', 'stderr_sc', 'mean_sw', 'stderr_sw');
%% k-means Clustering %% k-means Clustering

2
Data-Analyzer/matchTFRadiiAtomNumber.m
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@ -159,5 +159,5 @@ ylabel('TF Radius - Y ($\mu$m)', 'Interpreter', 'latex', 'FontSize', 16);
legend('FontSize', 12, 'Interpreter', 'tex', 'Location', 'bestoutside'); legend('FontSize', 12, 'Interpreter', 'tex', 'Location', 'bestoutside');
axis square; grid on; axis square; grid on;
sgtitle('[ \omega_x, \omega_y, \omega_z ] = 2 \pi \times [ 50, 20, 150 ] Hz', ... sgtitle('[ \omega_x, \omega_y, \omega_z ] = 2 \pi \times [ 36.87, 17.4, 93.16 ] Hz', ...
'Interpreter', 'tex', 'FontSize', 18); 'Interpreter', 'tex', 'FontSize', 18);

9
Dipolar-Gas-Simulator/+Scripts/run_locally.m
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@ -614,11 +614,6 @@ JobNumber = 0;
SuppressPlotFlag = false; SuppressPlotFlag = false;
UCD = Scripts.extractAverageUnitCellDensity(SaveDirectory, JobNumber, Radius, PeakThreshold, SuppressPlotFlag); UCD = Scripts.extractAverageUnitCellDensity(SaveDirectory, JobNumber, Radius, PeakThreshold, SuppressPlotFlag);
NUM_ATOMS_LIST = [100000 304167 508333 712500 916667 1120833 1325000 ...
1529167 1733333 1937500 2141667 2345833 2550000 2754167 ...
2958333 3162500 3366667 3570833 3775000 3979167 4183333 ...
4387500 4591667 4795833 5000000];
%% Plot number of droplets %% Plot number of droplets
% Parameters % Parameters
Radius = 2; Radius = 2;
@ -780,7 +775,7 @@ TitleString = "[ \omega_x, \omega_y, \omega_z ] = 2 \pi \times [ 50,
SCATTERING_LENGTH_RANGE = [95.62]; SCATTERING_LENGTH_RANGE = [95.62];
NUM_ATOMS_LIST = [712500 916667 1120833 1325000 1529167 1733333 1937500 2141667 2345833 2550000 2754167 2958333 3162500 3366667 3570833]; NUM_ATOMS_LIST = [712500 916667 1120833 1325000 1529167 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));
@ -834,7 +829,7 @@ PlanckConstant = 6.62607015E-34;
PlanckConstantReduced = 6.62607015E-34/(2*pi); PlanckConstantReduced = 6.62607015E-34/(2*pi);
AtomicMassUnit = 1.660539066E-27; AtomicMassUnit = 1.660539066E-27;
BohrMagneton = 9.274009994E-24; BohrMagneton = 9.274009994E-24;
VacuumPermeability = 1.25663706212E-6;
% Dy specific constants % Dy specific constants
Dy164Mass = 163.929174751*AtomicMassUnit; Dy164Mass = 163.929174751*AtomicMassUnit;
Dy164IsotopicAbundance = 0.2826; Dy164IsotopicAbundance = 0.2826;

BIN
Estimations/20260605_ALSData.mat Normal file
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430
Estimations/PhaseCoherenceMap.m Normal file
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@ -0,0 +1,430 @@
FR_choice = 1;
ABKG_choice = 1;
% Get the full spectrum
[B, a_s] = getFullFeschbachSpectrum(FR_choice, ABKG_choice);
% Define the plotting range
x_limits = [1.15, 2.7];
y_limits = [0, 150];
% Find indices within our x-range
mask = (B >= x_limits(1)) & (B <= x_limits(2));
B_plot = B(mask);
a_s_plot = a_s(mask);
% Identify resonances to mask (looking at the spectrum, we'll mask around 2.174G and 2.336G)
resonances_to_mask = [2.174, 2.336];
mask_width = 0.1; % Width to mask around each resonance (in G)
% Create a mask for the regions to keep (1 = keep, 0 = mask)
keep_mask = true(size(B_plot));
for res = resonances_to_mask
keep_mask = keep_mask & (B_plot < (res - mask_width) | B_plot > (res + mask_width));
end
% Create masked version
B_masked = B_plot(keep_mask);
a_s_masked = a_s_plot(keep_mask);
% Interpolate over the masked regions
a_s_interp = interp1(B_masked, a_s_masked, B_plot, 'pchip');
% --- Find the remaining resonances (peaks) in the interpolated data ---
% Use findpeaks to detect peaks (adjust MinPeakProminence as needed)
[peaks, locs] = findpeaks(abs(a_s_interp), 'MinPeakProminence', 20); % Tune this!
remaining_resonances = B_plot(locs); % Positions of remaining resonances
% --- Select the two resonances of interest (1.3G and 2.59G) ---
% If automatic detection fails, manually define them:
target_resonances = [1.3, 2.59]; % Manually specified (adjust as needed)
% OR use the closest detected resonances:
% target_resonances = remaining_resonances(abs(remaining_resonances - 1.3) < 0.2 & abs(remaining_resonances - 2.59) < 0.2);
% --- Extract the curve BETWEEN these two resonances ---
res1 = min(target_resonances); % Lower resonance (1.3G)
res2 = max(target_resonances); % Upper resonance (2.59G)
between_mask = (B_plot > res1) & (B_plot < res2); % No masking here, since resonances are already removed
B_between = B_plot(between_mask);
a_s_between = a_s_interp(between_mask);
% --- Plotting ---
figure(1);
set(gcf,'Position',[100 100 950 750])
set(gca,'FontSize',16,'Box','On','Linewidth',2);
hold on;
% Plot the interpolated spectrum (without 2.174G and 2.336G)
plot(B_plot, a_s_interp, 'k-', 'LineWidth', 1, 'DisplayName', 'Interpolated spectrum');
% Highlight the region between 1.3G and 2.59G
plot(B_between, a_s_between, 'm-', 'LineWidth', 2, 'DisplayName', 'Between 1.3G and 2.59G');
% Formatting
xlim(x_limits);
ylim([0, 150]);
xlabel('Magnetic Field (G)');
ylabel('Scattering Length (a_0)');
title('Interpolated Spectrum: Region Between 1.3G and 2.59G');
legend('Location', 'southeast');
grid on;
hold off;
%%
% Load data
FSData = load('20260605_ALSData.mat');
x = FSData.data(:,1);
y = FSData.data(:,2) * 166 * 1E-5;
y_err = FSData.data(:,3) * 166 * 1E-5;
% --- Plotting ---
figure(2); clf;
set(gcf,'Position',[100 100 950 750])
set(gca,'FontSize',16,'Box','On','Linewidth',2);
hold on;
% Plot data with error bars, no connecting lines (only points)
errorbar(x, y, y_err, 'ko', ...
'MarkerFaceColor', 'r', ... % Filled black circles
'MarkerSize', 6, ... % Size of data points
'LineStyle', 'none', ... % No connecting line
'LineWidth', 1.5, ... % Width of error bars
'DisplayName', 'As measured with ALS on a cold thermal cloud');
% Formatting
xlabel('Magnetic Field (G)');
ylabel('Atom Number');
legend('Location', 'southeast');
grid on;
box on;
hold off;
%% Combined plot
figure(3); clf;
set(gcf, 'Position', [100, 100, 950, 750]);
set(gca, 'FontSize', 16, 'Box', 'On', 'LineWidth', 2);
hold on;
% ========== Define Shaded Regions ==========
% Format: [x_start, x_end, label]
regions = [
2.45, 2.52, "BEC";
2.35, 2.45, "SSD/SS";
2.1, 2.35, "ID/IS";
1.4, 2.1, "TBD"
];
% Colors for each region (semi-transparent)
region_colors = [
0.85, 0.9, 1.0; % light blue
0.9, 1.0, 0.85; % light green
1.0, 0.9, 0.85; % light red
0.95, 0.95, 0.95 % light gray
];
ylims = [0, 150]; % Adjust as needed
for i = 1:size(regions,1)
x1 = str2double(regions(i,1));
x2 = str2double(regions(i,2));
label = string(regions(i,3));
fill([x1 x2 x2 x1], [ylims(1) ylims(1) ylims(2) ylims(2)], ...
region_colors(i,:), ...
'FaceAlpha', 0.9, 'EdgeColor', 'none', 'HandleVisibility', 'off');
text((x1 + x2)/2, mean(ylims), label, ...
'HorizontalAlignment', 'center', ...
'VerticalAlignment', 'middle', ...
'FontSize', 14, 'FontWeight', 'bold', ...
'Rotation', 90); % Vertical orientation
end
% ========== LEFT Y-AXIS ==========
yyaxis left
plot(B_plot, a_s_interp, 'k-', 'LineWidth', 1.5, 'DisplayName', 'Interpolated Dy-164 Feshbach spectrum');
plot(B_between, a_s_between, 'm-', 'LineWidth', 2.5, 'DisplayName', 'Region between 1.3G and 2.59G');
ylabel('Scattering Length (a_0)');
ylim(ylims);
% ========== RIGHT Y-AXIS ==========
yyaxis right
ax = gca;
ax.YColor = [0.75 0 0]; % Make right y-axis red to match data points
FSData = load('20260605_ALSData.mat');
x = FSData.data(:,1);
y = FSData.data(:,2) * 166 * 1E-5;
y_err = FSData.data(:,3) * 166 * 1E-5;
errorbar(x, y, y_err, 'ko', ...
'MarkerFaceColor', 'r', ...
'MarkerSize', 6, ...
'LineStyle', 'none', ...
'LineWidth', 1.5, ...
'DisplayName', 'As measured with ALS on a cold thermal cloud');
ylabel('Atom Number');
% ========== Shared Formatting ==========
xlabel('Magnetic Field (G)');
xlim([1.15, 2.7]);
grid on;
legend('Location', 'southeast');
title('BEC-SSD/SS-ID/IS Regimes');
hold off;
%% Helper functions
function [t, B_ramp, a_check] = generateSmoothBRamp(FR_choice, ABKG_choice, a_start, a_end, selectedResRange, T, Nt, opts)
% Time array
t = linspace(0, T, Nt);
if strcmp(opts.rampShape, 'linear')
% Directly call helper for linear LUT ramp generation
[t, B_ramp, a_check] = generateLinearBRampUsingLUT(FR_choice, ABKG_choice, a_start, a_end, selectedResRange, T, Nt);
return
end
% Get target a_s(t) based on rampShape choice
a_target = getTargetScatteringLength(t, T, a_start, a_end, opts.rampShape);
% --- a(B) interpolation ---
[B_between, a_between] = extractBetweenResonances(FR_choice, ABKG_choice, selectedResRange);
valid_idx = a_between > 0 & a_between < 150;
[a_sorted, sort_idx] = sort(a_between(valid_idx));
B_sorted = B_between(valid_idx);
B_sorted = B_sorted(sort_idx);
B_of_a = @(a) interp1(a_sorted, B_sorted, a, 'linear', 'extrap');
B_raw = B_of_a(a_target);
% --- Smoothing ---
switch opts.smoothingMethod
case 'sgolay'
B_smooth = sgolayfilt(B_raw, opts.sgolayOrder, opts.sgolayFrameLength);
case 'lowpass'
dt = T / (Nt - 1); Fs = 1 / dt;
B_smooth = lowpass(B_raw, Fs / 20, Fs);
case 'none'
B_smooth = B_raw;
otherwise
error('Unknown smoothing method');
end
% --- Bound the ramp ---
B_smooth = min(max(B_smooth, opts.Bmin), opts.Bmax);
% --- Enforce max dB/dt ---
dt = T / (Nt - 1);
for i = 2:Nt
delta = B_smooth(i) - B_smooth(i-1);
if abs(delta/dt) > opts.maxRampRate
delta = sign(delta) * opts.maxRampRate * dt;
B_smooth(i) = B_smooth(i-1) + delta;
end
end
B_ramp = B_smooth;
% --- Verify a_s(t) from B_ramp ---
[a_bkg, resonanceB, resonancewB] = getResonanceParams(FR_choice, ABKG_choice, selectedResRange);
a_of_B = @(B) arrayfun(@(b) ...
a_bkg * prod(1 - resonancewB ./ (b - resonanceB)), B);
a_check = a_of_B(B_ramp);
end
function a_target = getTargetScatteringLength(t, T, a_start, a_end, rampShape)
% If rampShape is a function handle, use it directly (for flexibility)
if isa(rampShape, 'function_handle')
a_target = rampShape(t);
return
end
switch lower(rampShape)
case 'exponential'
tau = T / 3;
base = (1 - exp(-t / tau)) / (1 - exp(-T / tau));
a_target = a_start + (a_end - a_start) * base;
case 'sigmoid'
s = 10 / T; center = T / 2;
sigmoid = @(x) 1 ./ (1 + exp(-s * (x - center)));
base = (sigmoid(t) - sigmoid(t(1))) / (sigmoid(t(end)) - sigmoid(t(1)));
a_target = a_start + (a_end - a_start) * base;
otherwise
error('Unknown ramp shape: %s', rampShape);
end
end
function [B_between, a_between] = extractBetweenResonances(FR_choice, ABKG_choice, selectedRange)
[a_bkg, resonanceB, resonancewB] = getResonanceParams(FR_choice, ABKG_choice, selectedRange);
[~, idx] = sort(resonancewB, 'descend');
B1 = resonanceB(idx(1)); B2 = resonanceB(idx(2));
w1 = resonancewB(idx(1)); w2 = resonancewB(idx(2));
Bvis = linspace(min(B1, B2) - 20*min(w1,w2), max(B1, B2) + 20*min(w1,w2), 2000);
a_of_B = @(B) arrayfun(@(b) ...
a_bkg * prod(1 - resonancewB ./ (b - resonanceB)), B);
avis = a_of_B(Bvis);
between_idx = Bvis >= min(B1,B2) & Bvis <= max(B1,B2);
B_between = Bvis(between_idx);
a_between = avis(between_idx);
end
function [B_range, a_values] = fullResonanceCurve(FR_choice, ABKG_choice, selectedRange)
[a_bkg, resonanceB, resonancewB] = getResonanceParams(FR_choice, ABKG_choice, selectedRange);
B_range = linspace(min(resonanceB)-0.2, max(resonanceB)+0.2, 3000);
a_of_B = @(B) arrayfun(@(b) ...
a_bkg * prod(1 - resonancewB ./ (b - resonanceB)), B);
a_values = a_of_B(B_range);
end
function [a_bkg, resonanceB, resonancewB] = getResonanceParams(FR_choice, ABKG_choice, selectedRange)
if FR_choice == 1
a_bkg_list = [85.5, 93.5, 77.5];
resonanceB = [1.295, 1.306, 2.174, 2.336, 2.591, 2.740, 2.803, ...
2.780, 3.357, 4.949, 5.083, 7.172, 7.204, 7.134, 76.9];
resonancewB = [0.009, 0.010, 0.0005, 0.0005, 0.001, 0.0005, 0.021, ...
0.015, 0.043, 0.0005, 0.130, 0.024, 0.0005, 0.036, 3.1];
else
a_bkg_list = [87.2, 95.2, 79.2];
resonanceB = [1.298, 2.802, 3.370, 5.092, 7.154, 2.592, 2.338, 2.177];
resonancewB = [0.018, 0.047, 0.048, 0.145, 0.020, 0.008, 0.001, 0.001];
end
a_bkg = a_bkg_list(ABKG_choice);
% --- Filter resonanceB and resonancewB if selectedRange is provided ---
if nargin >= 3 && ~isempty(selectedRange)
minB = min(selectedRange); maxB = max(selectedRange);
keep_idx = (resonanceB >= minB) & (resonanceB <= maxB);
% Keep only the lowest and highest resonance in the selected range
if sum(keep_idx) >= 2
B_sub = resonanceB(keep_idx);
w_sub = resonancewB(keep_idx);
[~, idx_lo] = min(B_sub);
[~, idx_hi] = max(B_sub);
resonanceB = [B_sub(idx_lo), B_sub(idx_hi)];
resonancewB = [w_sub(idx_lo), w_sub(idx_hi)];
else
error('Selected resonance range does not include at least two resonances.');
end
end
end
function [t, B_ramp, a_check] = generateLinearBRampUsingLUT(FR_choice, ABKG_choice, a_start, a_end, selectedResRange, T, Nt)
% Time vector
t = linspace(0, T, Nt);
% 1) Generate LUT of B and a_s(B)
[B_between, a_between] = extractBetweenResonances(FR_choice, ABKG_choice, selectedResRange);
% Restrict to physically meaningful range (optional)
valid_idx = a_between > 0 & a_between < 150;
B_lut = B_between(valid_idx);
a_lut = a_between(valid_idx);
% 2) Generate linear a_s ramp in time
a_target = linspace(a_start, a_end, Nt);
% 3) Interpolate B(t) from LUT a_s -> B
% Make sure a_lut is sorted ascending
[a_lut_sorted, idx_sort] = sort(a_lut);
B_lut_sorted = B_lut(idx_sort);
B_ramp = interp1(a_lut_sorted, B_lut_sorted, a_target, 'linear', 'extrap');
% 4) Compute resulting a_s(t) for verification
[a_bkg, resonanceB, resonancewB] = getResonanceParams(FR_choice, ABKG_choice, selectedResRange);
a_of_B = @(B) arrayfun(@(b) ...
a_bkg * prod(1 - resonancewB ./ (b - resonanceB)), B);
a_check = a_of_B(B_ramp);
end
function [B, a_s] = getFullFeschbachSpectrum(FR_choice, ABKG_choice)
% plotScatteringLength(FR_choice, ABKG_choice)
% Plots the Dy-164 scattering length vs B field based on PhysRevX.9.021012 Suppl. Fig. S5
%
% Inputs:
% FR_choice: 1 = new resonance parameters, 2 = old
% ABKG_choice: 1 = lower a_bkg, 2 = mid, 3 = upper
%
% Example:
% plotScatteringLength(1, 1);
if nargin < 1, FR_choice = 1; end
if nargin < 2, ABKG_choice = 1; end
% Choose background scattering length
if FR_choice == 1 % New values
switch ABKG_choice
case 1, a_bkg = 85.5;
case 2, a_bkg = 93.5;
case 3, a_bkg = 77.5;
end
% Resonance positions (G) and widths (G)
resonanceB = [1.295, 1.306, 2.174, 2.336, 2.591, 2.740, 2.803, 2.780, ...
3.357, 4.949, 5.083, 7.172, 7.204, 7.134, 76.9];
resonancewB = [0.009, 0.010, 0.0005, 0.0005, 0.0010, 0.0005, 0.021, ...
0.015, 0.043, 0.0005, 0.130, 0.024, 0.0005, 0.036, 3.1];
else % Old values
switch ABKG_choice
case 1, a_bkg = 87.2;
case 2, a_bkg = 95.2;
case 3, a_bkg = 79.2;
end
% Resonance positions (G) and widths (G)
resonanceB = [1.298, 2.802, 3.370, 5.092, 7.154, 2.592, 2.338, 2.177];
resonancewB = [0.018, 0.047, 0.048, 0.145, 0.020, 0.008, 0.001, 0.001];
end
% Magnetic field range for plotting (G)
B = linspace(0.5, 8, 2000);
% Compute scattering length using product formula
a_s = a_bkg * ones(size(B));
for j = 1:length(resonanceB)
a_s = a_s .* (1 - resonancewB(j) ./ (B - resonanceB(j)));
end
end
function [t, B_ramp, a_check] = generateLinearBRamp(B_between, a_s_between, a_start, a_end, T, Nt)
% Generates a B-field ramp (B_ramp) to produce a linear a_s ramp from a_start to a_end.
% Uses precomputed LUT: B_between (magnetic field) and a_s_between (scattering length).
%
% Inputs:
% B_between - Magnetic field values (G) between resonances [vector]
% a_s_between - Corresponding scattering lengths (a_0) [vector]
% a_start, a_end - Target scattering length range (a_0)
% T - Total ramp time (s)
% Nt - Number of time steps
%
% Outputs:
% t - Time vector (s)
% B_ramp - Generated B-field ramp (G)
% a_check - Verified a_s(t) using interpolation (a_0)
% --- 1. Time vector ---
t = linspace(0, T, Nt);
% --- 2. Ensure LUT is sorted and unique ---
[a_s_sorted, sort_idx] = unique(a_s_between); % Remove duplicates and sort
B_sorted = B_between(sort_idx);
% --- 3. Generate target linear a_s ramp ---
a_target = linspace(a_start, a_end, Nt);
% --- 4. Interpolate B(t) from a_s -> B ---
B_ramp = interp1(a_s_sorted, B_sorted, a_target, 'pchip', 'extrap');
% --- 5. Verify a_s(t) by re-interpolating ---
a_check = interp1(B_sorted, a_s_sorted, B_ramp, 'pchip');
end