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Magic running and standing wave optical traps for Rydberg atoms - Data and code for analysis

<p>Data, theory calculation and plotting scripts for the publication titled "Magic running and standing wave optical traps for Rydberg atoms" (<a href="https://arxiv.org/abs/2410.20901" target="_blank" rel="noopener">arXiv:2410.20901</a>).</p> <p>&nbsp;</p> <p><strong>File legend</strong></p> <ul> <li>&nbsp;<code>data_FIGx_yyy.mat</code> contains the calculated or measured data used in Figure x</li> <li>&nbsp;<code>calc_FIGx_yyy.py</code> is the script to calculate the theoretical data used in Figure x</li> <li>&nbsp;<code>plot_FIGx_yy.py</code> is the script to create the Figure x of the paper</li> <li>&nbsp;<code>simulation_class.py</code> is a class with theory functions</li> <li>&nbsp;<code>paperstyle.mplstyle</code> is a matplotlib style file</li> <li>&nbsp;<code>requirements.txt</code> lists all the required python packages</li> </ul> <p>&nbsp;</p> <p><strong>Abstract</strong></p> <p>Magic trapping of ground and Rydberg states, which equalizes the AC Stark shifts of these two levels, enables increased ground-to-Rydberg state coherence times. We measure via photon storage and retrieval how the ground-to-Rydberg state coherence depends on trap wavelength for two different traps and find different optimal wavelengths for a 1D optical lattice trap and a running wave optical dipole trap. Comparison to theory reveals that this is caused by the Rydberg electron sampling different potential landscapes. The observed difference increases for higher principal quantum numbers, where the extent of the Rydberg electron wave function becomes larger than the optical lattice period. Our analysis shows that optimal magic trapping conditions depend on the trap geometry, in particular for optical lattices and tweezers.</p> <p>&nbsp;</p> <p><strong>Theory calculation</strong></p> <p>We implemented the potential arising from the Hamiltonians described in the paper. The functions are shared here in the python class <code>simulation_class.py</code>. This class is used in the calculation scripts named <code>calc_FIGx_yyy.py</code> and saves the data as <code>data_FIGx_yyy.mat</code> for the respective Figure x.</p> <p>In case of questions to the code or calculations, please contact Chris Nill or Lukas Ahlheit.</p> <p>&nbsp;</p> <p><strong>Experimental data</strong></p> <p>The experimental data published here are photon storage and retrieval traces of 780 nm probe photons as function of storage duration. We recorded photon traces for different trap laser detunings and Rydberg states.</p> <p>In case of questions to the data, please contact Lukas Ahlheit or Sebastian Hofferberth.</p> <p>&nbsp;</p> <p><strong>Inkscape modification to specific figures</strong></p> <ul> <li>Figure 1: The plotted data is joined in Inkscape with schematic drawings</li> <li>Figure 2: The plot created by the python file is edited in Inkscape for readability</li> <li>Figure 5: We add two schematics into the figure created by the python file</li> </ul>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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