DOI: 10.48323/s005b-fzk38
title: Supporting Data for "Optimised spectral purity of unfiltered photons via pump and nonlinearity shaping"

description: Supporting Data for the manuscript  "Optimised spectral purity of unfiltered photons via pump and nonlinearity shaping"



Overview

This repository contains the complete dataset supporting the experimental results presented in "Optimised spectral purity of unfiltered photons via engineered phase matching and pump spectral shaping". Refer to the manuscript for a detailed discussion of the experiment.

The data include the joint spectral intensity (JSI) characterisation from time-of-flight spectrometry (TOFS), two-photon interference (TPI) measurements, referred here as Hong-Ou-Mandel (HOM) interference, characterisation of the pump laser spectral shaping, and additional studies made in the Supplementary.


Data Structure


Main Data (`Main/`)


JSI Data (`Main/JSI Data/`)

Contains Joint Spectral Intensity measurements from Sagnac interferometer configurations:





File format: `.txt` files







Naming convention: "JSI_Sagnac1_*.txt" where "*" contains the measurement sequence number and additional information.







Content: Two-dimensional matrix with raw, three-fold coincidence events between (1) pulsed pump trigger, (2) signal and (3) idler down-converted photons as a function of trigger-signal delay and trigger-idler delay in picoseconds:







Delays: first row and first column (ps).

Three-folds: all other elements.





Example import data in Matlab:






% Load directory

S = dir(fullfile('Main\JSI Data\','*.txt'));










% Choose file and extrapolate data

file_index = 1;

F = fullfile('Main\JSI Data\',S(file_index).name);




S(file_index).data = readtable(F);

tau_1 = table2array(S(file_index).data(1,2:end));




tau_2 = table2array(S(file_index).data(2:end,1));




Coinc_table = table2array(S(file_index).data(2:end,2:end));

Coinc_table = flip(table2array(S(file_index).data(2:end,2:end)),1);







HOM Measurement between independent sources without spectral filtering



"IndependentHOM_NoFilters.csv": Hong-Ou-Mandel interference visibility in heralded two-photon interference measurements without spectral filtering.






Measurement procedure: The relative delay between interfering photons is scanned with a translation stage, and single and coincidence events are recorded with a time-tagging system. Ten iterations of the measurement are performed.

Content:



               - First row: Position of the translation stage that sets the relative delay between interfering photons in millimetres.

               - Second row: Total four-fold coincidences, for each position, in the heralded two-photon interference.

               - Third to sixth row: Total single counts, for each position, recorded by each channel's detector.

               - Seventh to sixteenth row: Four-fold coincidences, for each position, at each iteration of the measurement.


Pulse Shaping Data

"Shaping_Data.mat": MATLAB data file containing the struct "shaping_configuration". The struct has 18 fields related to the experimental parameters and results obtained by optimising the voltage mask applied to a Spatial Light Modulator (SLM) placed at the Fourier plane of a 4f pulse shaper. The optimisation is based on an iterative procedure where the voltage applied to each pixel of the SLM is adjusted to minimise the error with respect to a target Gaussian function.





 Format: MATLAB .mat file







  Variables: 


                - "wavelengths": 1x1024 array containing the wavelength corresponding to each pixel of the spectrometer camera.                - "spectra": 41x1024 array containing the 41 spectra measured during the iterative optimisation of the SLM voltage mask (unshaped spectrum = first column).                - "errors": 1x40 array containing the error with respect to the target spectrum (the first is excluded as it is the unshaped spectrum).                - "voltage_masks": 40x128 array containing the optimised voltages (mV) applied to each of the 128 pixels of the SLM.                - "best_voltage_mask": 1x128 array corresponding to the optimised voltage mask.                - Additional fields refer to the spectrometer setting and to the amplitude and wavelength calibration of the SLM (not required in the analysis).




Example import data in Matlab:



% Read data

wl_vec = shaping_configuration.wavelengths';





best_index = find(shaping_configuration.errors==min(shaping_configuration.errors));




Amp_vec = shaping_configuration.spectra(best_index+1, :)';









 % Analysis data





ft = fittype('a*exp(-(x-b)^2/(2*c^2)) + d');




fo = fitoptions('StartPoint', [max(Amp_vec), wl_vec(Amp_vec==max(Amp_vec)), 1, 0], 'Method', 'NonlinearLeastSquares');



[data_fit, gof] = fit(wl_vec, Amp_vec, ft, fo);

etc...







Supplementary Data (`Supplementary/`)


Filter Characterisation (`Supplementary/Semrock 1550-3/`)

Spectral characterisation data for the optical filters. Five measurements are taken for each filter to obtain an average transmission.





"Semrock 1550-3 #1.csv" and "Semrock 1550-3 #2.csv": Transmission spectra for the two filters

Content: CSV with wavelength, average transmission, and standard deviation data.

The "*.dsp" files are the original files obtained from the measuring device for each of the five iterations.


Filtered HOM Measurements

"IndependentHOM_Filters.csv": Hong-Ou-Mandel interference measurements with spectral filtering applied. The data structure is identical to the unfiltered case.


Polarisation Analysis

"Polarisation_InterferenceFringes.csv": Polarisation-dependent interference fringe measurements to estimate the visibility reduction from polarisation mismatch of the interfering photons.





Content: CSV with sample # and intensity measurements at the outputs of the polarisation-maintaining fibre beam splitter used to interfere the down-converted photons.



Related Publications

To be published.


Contact Information

For questions regarding this dataset, please contact: Tommaso.Faleo@uibk.ac.at


Funding

This research was funded in part by the Austrian Science Fund (FWF) projects 10.55776/FG5, 10.55776/F71, 10.55776/W1259, 10.55776/COE1, 10.55776/TAI556 and infrastructure funding from FFG (grant no. FO999896024). We also acknowledge support by the UK Engineering and Physical Sciences Research Council (grant nos, EP/T001011/1, EP/Z533208/1).