General Information
Title of Manuscript: Electro-optic frequency shift of single photons from a quantum dot
Authors: Sanjay Kapoor, Aleksander Rodek, Michał Mikołajczyk, Jerzy Szuniewicz, Filip Sośnicki, Tomasz Kazimierczuk, Piotr Kossacki, Michał Karpiński
Corresponding Author Email: sanjay.kapoor@fuw.edu.pl, michal.karpinski@fuw.edu.pl
Institution: Faculty of Physics, University of Warsaw, Pasteura 5, 02-093 Warszawa, Poland
Manuscript DOI: https://doi.org/10.1515/nanoph-2024-0550
Journal: Nanophotonics, Volume: 14, Issue: 11, Page Range: 1775-1782, Year: 2025
Dataset License: CC-BY 4.0
Description of the Data
The dataset provides the raw experimental data and processing scripts used to demonstrate deterministic frequency shift of single photons from a semiconductor quantum dot (QD) using an electro-optic phase modulator (EOPM). The spectral shifts are achieved using a serrodyne electro-optic phase modulation technique. The data includes: 1. Spectal measurements: Acquired using a single-photon grating spectrometer (Acton SP-2750i and Andor Newton CCD). 2. Time-correlation data: Measured using a time-tagger (HydraHarp 400) for second order correclation measurements and Hong-Ou-Mandel (HOM) indistinguishability experiments.
File Structure and Contents
The dataset is organized into four main directories corresponding to specific figures in the manuscript.
1. Folder: Figure_2_Spectra
Description: Contains five ASCII data files used to generate Figure 2. These files represent the photoluminescence spectrum of a single QD under various electro-optic modulation states.
Parameters: Acquisition time: 20 seconds, Bias voltage: 1.333 V, Excitation wavelength: 930.1 nm, First column: wavelength (nm), Second column: Counts (in 20 seconds)
d001_true_background.asc
The data represents the background spectrum of the experimental evironment when the excitation laser was off. This spectrum is subtracted from all the measured spectra during the post processing of the data.
d001_res_ex_eopm_off_bias_detuned.asc
The data represents spectrum of the QD under resonant excitation when the bias voltage (0.8 Volts) was detuned. It allows measuring the excitation laser leaking from the QD setup. The black data points in Fig. 2.
d001_res_ex_eopm_off_no_shift.asc
The data represents spectrum of the QD under resonant excitation when the EOPM was off. The green data points in Fig. 2.
d001_res_ex_eopm_on_blue_shift.asc
The data represents spectrum of the QD under resonant excitation when the EOPM was driven with a sawtooth waveform with a positive slope resulting in a blue shift of the QD emission. The blue data points in Fig. 2.
d001_res_ex_eopm_on_red_shift.asc
The data represents spectrum of the QD under resonant excitation when the EOPM was driven with a sawtooth waveform with a negative slope resulting in a red shift of the QD emission. The red data points in Fig. 2.
plot_fig2_spectra.py
The Python script used to read the (.asc) spectrum files and post process the data and generate Fig. 2 of the manuscript.
spectra_fit.png
The figure generated using the Python script.
2. Folder: Figure_3_g2(0)
Description: Contains data for Figure 3. These three (.dat) files contain data for the time correlated measurements using a time tagger for second-order correlation measurements of single photons. The first column is the coincidence counts between channel 1 and channel 2 of the time tagger which were connected to the outputs of fiber beam splitter, spliting the single photons from the QD.
Parameters: Bin width: 128 ps, Acquisition time: 15 minutes.
d002_g2_eopm_off_no_shift.dat
Time-correralted histogram measurement when the EOPM was off, the green data points in Fig. 3 of the manuscript.
d002_g2_eopm_on_red_shift.dat
Time-correlated histogram measurement when the EOPM was driven with a sawtooth RF waveform resulting in a red shift, the red data points in Fig. 3 of the manuscript.
d002_g2_eopm_on_blue_shift.dat
Time-correlated histogram measurement when the EOPM was driven with a sawtooth RF waveform resulting in a blue shift, the blue data points in Fig. 3 of the manuscript.
plot_fig3_g2.py
The Python script used to read the above three .dat files and post process the data, and generate the plots for Fig. 3.
g2.png
The figure generated using the Python script.
3. Folder: Figure_4_HOMI
Description: Contains data for Figure 4. These four (.dat) files contain data for the HOM interference measurements in an unbalanced fiber Mach-Zehnder interferometer with a 26 ns delay between the two arms.
Parameters: Bin width = 128 ps
d002_hom_eopm_off_no_shift_orthogonal_pol.dat
Cross-polarized (orthogonal) configuration, when the EOPM was off resulting in maximum distinguishability between the two arms. The orange trace in Fig. 4 (a). The data acquisition time was 19 minutes.
d002_hom_eopm_off_no_shift_parallel_pol.dat
Co-polarized (parallel) configuration, when the EOPM was off resulting in maximum indistinguishability between the two arms. The green trace in Fig. 4 (a). The data acquisition time was 15 minutes.
d002_hom_eopm_on_red_shift_parallel_pol.dat
Co-polarized (parallel) configuration, when the EOPM was driven with a sawtooth RF waveform (4.56 GHz) resulting in a red shift, the red trace in Fig. 4 (b) of the manuscript. The data acquisition time was 15 minutes.
d002_hom_eopm_on_blue_shift_parallel_pol.dat
Co-polarized (parallel) configuration, when the EOPM was driven with a sawtooth RF waveform (4.56 GHz)resulting in a blue shift, the blue trace in Fig. 4 (b) of the manuscript. The data acquisition time was 15 minutes.
plot_fig4_homi.py
The Python script used to read the above four .dat files and post process the data, and generate the plots for Fig. 4.
homi.png
The plot generated using the Python script.
4. Folder: Figure_5a_Tunable_shift
Description: Contains three subfolders containing data for Figure 5 (a). These files represent the spectrum measured for different modulation frequencies, demonstrating the tunablity of the spectral shift.
Subfolder: 2_28GHz, 4_56GHz, 5_32GHz
Each subfolder contains the following .asc files: `no_shift`, `blue_shift`, `red_shift`, and `bias_detuned`.
plot_all_spectra.py
The Python script to aggregate data from all frequencies into a single plot for Fig. 5a.
spectral_shift.png
The plot generated using the Python script.
Packages and Dependencies
Description: All scripts were tested with Python 3.13 on March 2nd, 2026. Required packages:
numpy 2.1.3
matplotlib 3.9.2
scipy 1.16.1
