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18 results for “optical trapping”
Dataset 1 for Publication: Separation-dependent near-field effects in Mie scattering spectra of two optically trapped aerosol droplets
<p>Dataset for Publication: ASCII files of Mie spectra for each experimentally analysed run, calibrated wavelength files, and brightfield images at each interdroplet separation.</p>
Prospects for single photon sideband cooling of optically trapped neutral atoms
<p>Data used for figures in paper: Berto et al., Prospects for single photon sideband cooling of optically trapped neutral atoms, 2021.</p> <p>Data is organized in single files fig1.csv, fig2.csv, ..., etc, each containing columns of <x> and <y> used to create the curves in the given figure.</p> <p> </p> <p>Abstract: We propose a novel cooling scheme for realising single photon sideband cooling on particles trapped in a state-dependent optical potential. We develop a master rate equation from an ab-initio model and find that in experimentally feasible conditions it is possible to drastically reduce the average occupation number of the vibrational levels by applying a frequency sweep on the cooling laser that sequentially cools all the motional states. Notably, this cooling scheme works also when a particle experiences a deeper trap in its internal ground state than in its excited state, a condition for which conventional single photon sideband cooling does not work. In our analysis, we consider two cases: a two-level particle confined in an optical tweezer and Li atoms confined in an optical lattice, and find conditions for efficient cooling in both cases. The results from the model are confirmed by a full quantum Monte Carlo simulation of the system Hamiltonian. Our findings provide an alternative cooling scheme that can be applied in principle to any particle, e.g. atoms, molecules or ions, confined in a state-dependent optical potential.</p>
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> </p> <p><strong>File legend</strong></p> <ul> <li> <code>data_FIGx_yyy.mat</code> contains the calculated or measured data used in Figure x</li> <li> <code>calc_FIGx_yyy.py</code> is the script to calculate the theoretical data used in Figure x</li> <li> <code>plot_FIGx_yy.py</code> is the script to create the Figure x of the paper</li> <li> <code>simulation_class.py</code> is a class with theory functions</li> <li> <code>paperstyle.mplstyle</code> is a matplotlib style file</li> <li> <code>requirements.txt</code> lists all the required python packages</li> </ul> <p> </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> </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> </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> </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>
Hybrid electro-optical trap for experiments with levitated particles in vacuum
<p>Data for the paper "Hybrid electro-optical trap for experiments with levitated particles in vacuum"</p>
Data presented in "Characteristics of a magneto-optical trap of molecules"
<p>Data presented in the figures of our paper "Characteristics of a magneto-optical trap of molecules". The data is provided for figures 4a, 4b, 5a, 5b, 6a, 6b, 6c, 6d, 8a, 8b, 8c, 8d, 10a, 10b, 10c, 10d, 11a, 11b, 11c, 11d, 12b, 12c, 13a, 13b, 14a, 14b, 14c, 15, 16a and 16b.</p>
Data presented in "Blue-detuned magneto-optical trap"
<p>Data presented in figures 1, 2, 3, 4 and 5 of our paper "Blue-detuned magneto-optical trap"</p>
Dataset for the Manuscript: Surfactants Control Optical Trapping Near a Glass Wall
<p>This repository includes datasets supporting our manuscript that will be transferred to <em>the Journal of Physical Chemistry C</em>. This Version 2 includes extensive new results conducted during the revision process. </p> <ul> <li><strong>'Videos.zip'</strong>: Recordings of trapped particles, estimated trajectories, and calculated MSDs<strong>.</strong></li> <li><strong>'Dynamic Light Scattering.zip'</strong>: Measurement data using dynamic light scattering (DLS). It includes the conductivity, zeta potentials, and hydrodynamic size measurements.</li> <li><strong>'Raw data manual.html'</strong>: A data manual explaining the data details and visualizing the results.</li> </ul> <p>Notes:</p> <p>For finding particle trajectories, we used a Python package, <a href="http://soft-matter.github.io/trackpy/v0.4.2/index.html">Trackpy</a>, developed by Allan et al. We simply followed <a href="http://soft-matter.github.io/trackpy/v0.4.2/tutorial/walkthrough.html">their walkthrough</a> to find particle locations in a video recording and link them to a particle trajectory. The details of our trajectory outputs (_traj.csv files) can be found in <a href="http://soft-matter.github.io/trackpy/v0.4.2/generated/trackpy.locate.html#trackpy.locate">their API reference</a>. </p>
Data presented in "Laser cooling and magneto-optical trapping of molecules analyzed using optical Bloch equations and the Fokker-Planck-Kramers equation"
<p>Results of simulations presented in our paper "Laser cooling and magneto-optical trapping of molecules analyzed using optical Bloch equations and the Fokker-Planck-Kramers equation"</p>
Optical trapping of micro-particles and bacterial cells in single channel and flow-focusing microfluidic devices
<p><strong>Video 1</strong> - The video shows the flow-focusing and trapping of 1.84 μm bacteria-sized particles flowing at a sample flow rate of 0.1 μL/min. The horizontal sheath flow rate 1 μL/min and the vertical sheath flow rate is 0.5 μL/min. Trapping is achieved using a maximum laser power of 250mW. </p> <p><strong>Video 2</strong> - The video shows the flow and fluorescence trapping of 1.84 μm bacteria-sized particles flowing at a flow rate of 0.013 μL/min. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p> <p><strong>Video 3</strong> - The video shows the flow and trapping of 1.84 μm bacteria-sized particles flowing at a flow rate of 1 μL/min. Increased flow rate results in continuous transient trapping of the cells is achieved at a trapping power of 250mW. The microchannel surface is not treated with pluronic F-127, therefore lot of particles stick to the channel surface. </p> <p><strong>Video 4</strong> - The video shows the flow and trapping of 1.84 μm bacteria-sized particles flowing at a flow rate of 0.013 μL/min. Trapping is achieved at a laser power of 250mW. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p> <p><strong>Video 5</strong> - The video shows the flow and trapping of <em>E. coli</em> MG1655 flowing at a flow rate of 0.013 μL/min. Trapping is achieved at a laser power of 250mW. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p> <p><strong>Video 6</strong> - The video shows the flow and trapping of <em>S. aureus</em> 6538 flowing at a flow rate of 0.013 μL/min. Trapping is achieved at a laser power of 250mW. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p>
Optical Trapping Data for the manuscript "Myosin with hypertrophic cardiomyopathy mutation R712L has a reduced working stroke which is rescued by omecamtiv mecarbil"
<p>Optical Trapping Data for the manuscript "Myosin with hypertrophic cardiomyopathy mutation R712L has a reduced working stroke which is rescued by omecamtiv mecarbil"</p>
Floquet dynamics of ultracold atoms in optical lattices with a parametrically modulated trapping potential
<p>This dataset includes the data on which the figures of the preprint "Floquet dynamics of ultracold atoms in optical lattices with a parametrically modulated trapping potential" by Usman Ali, Martin Holthaus, Torsten Meier ( https://arxiv.org/abs/2405.02125v1 ) are based and the relevant codes that were used to generate the data.</p> <p>U.A. gratefully acknowledges support from Deutscher Akademischer Austauschdienst (DAAD, German Academic Exchange Service) through a doctoral research grant and we thank the PC2 (Paderborn Center for Parallel Computing) for providing computing time. M.H. has been supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through Project No. 397122187.</p>
Data presented in "Characteristics of unconventional Rb magneto-optical traps"
<p>Data presented in "Characteristics of unconventional Rb magneto-optical traps"</p>
Probing surface charge densities on optical fibers with a trapped ion
<p>We describe a novel method to measure the surface charge densities on optical fibers placed in the vicinity of a trapped ion, where the ion itself acts as the probe. Surface charges distort the trapping potential, and when the fibers are displaced, the ion’s equilibrium position and secular motional frequencies are altered. We measure the latter quantities for different positions of the fibers and compare these measurements to simulations in which unknown charge densities on the fibers are adjustable parameters. Values ranging from −10 to +50 e/µm2 were determined. Our results will benefit the design and simulation of miniaturized experimental systems combining ion traps and integrated optics, for example, in the fields of quantum computation, communication and metrology. Furthermore, our method can be applied to any setup in which a dielectric element can be displaced relative to a trapped charge-sensitive particle.</p>
Dataset for the manuscript: Probing surfactant bilayer interactions by tracking optically trapped single nanoparticles
<p><strong>Publication information</strong></p> <p>Kim, J., Martin, O. J. F., Probing Surfactant Bilayer Interactions by Tracking Optically Trapped Single Nanoparticles. <em>Adv. Mater. Interfaces</em> 2023, 10, 2201793. <a href="https://doi.org/10.1002/admi.202201793">https://doi.org/10.1002/admi.202201793</a></p> <ul> <li><strong>'Data manual.html'</strong>: This notebook explains the data structure and how to visualize the data using Python 3.</li> <li><strong>'rawdata.zip'</strong>: The dataset containing all the video recordings and trajectories.</li> <li>'<strong>single-particle_trajectory.zip'</strong>: It contains a specific particle trajectory used in Figures 2 and 4. It includes two consecutive video recordings of the same particle, the corresponding trajectories, and the mean squared displacements calculated from two segmented trajectories as explained in the manuscript.</li> </ul> <p>This new version also includes the original Jupyter notebook file (<strong>'Data manual.ipynb'</strong>).</p>
Data for figures: Coherently forming a single molecule in an optical trap
<p>This repository contains all experimentally data presented in the paper "Coherently forming a single molecule in an optical trap".</p>
Direct production of fermionic superfluids in a cavity-enhanced optical dipole trap
<p>Data corresponding to the article "Direct production of fermionic superfluids in a cavity-enhanced optical dipole trap".</p>
Optical Sediment Trap Calibration on the New England coast
Measurements from the Opt_Sed_Trap_Cal (Optical Sediment Trap Calibration) project off the New England coast.
Hybrid dielectrophoretic-optical trap for microparticles in aqueous suspension
<div> <p>Dataset of the manuscript "Hybrid dielectrophoretic-optical trap for microparticles in aqueous suspension".</p> <p> </p> </div>
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OpenNeuro
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