Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

11

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

11 results for “Wave optics”

Learn how ShareScore rates datasets ↗
zenodo40/100

Dataset: Use of bioresorbable fibers for short-wave infrared spectroscopy using time-domain diffuse optics

Open the record for dataset details and reuse information.

opencc-by-4.0Aug 2024View details →
zenodo36/100

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>

opencc-by-4.0Oct 2024View details →
zenodo36/100

Optical parametric amplification seeded by four-wave mixing in photonic crystal fibres

<p>Open access dataset for figures in &#39;Optical parametric amplification seeded by four-wave mixing in photonic crystal fibres&#39;, accepted for publication in&nbsp;Nonlinear Frequency Generation and Conversion: Materials and Devices XXI, paper 11985-4, SPIE LASE Photonics West, 2022.</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Optically measured torsional waves on cello string bowed at varying bow force

<p>Transverse and torsional vibrations of a cello&nbsp;G string made of steel, product name &quot;Pirastro Chromcor medium&quot;. Find string properties below. String mounted on a&nbsp;monochord and tuned to approximately&nbsp;98 Hz.</p> <p>Measurements by a high speed camera at 7000 frames per second,&nbsp;on axis with the bowed&nbsp;string (displacement &lt; 20&deg;).</p> <p>Transverse:&nbsp;optical marker on the string (transverse), 70 mm away from the bridge,&nbsp;10 mm away from the bow contact point.</p> <p>Torsional: optical marker at each end of&nbsp;two needles (top, and bottom, each 4mm long, total weight including marker 0.002 g), 70 mm away from the bridge,&nbsp;10 mm away from the bow contact point.</p> <p>Manual bowing by experienced player, bowing at the target contact point 80 mm away from bridge, while each individual&nbsp;stroke represents a certain&nbsp;level of&nbsp;bow pressure. Only&nbsp;regular Helmholtz motion is excited&nbsp;on the string. For each level (high, medium, low) the player adjusted bow velocity reasonably.</p> <p>* Raw data: movies</p> <p>Torsion3.avi :&nbsp;medium bow force<br> Torsion5.avi :&nbsp;low bow force<br> Torsion6.avi :&nbsp;high bow force<br> &nbsp;</p> <p>* Data, 1st level of&nbsp;abstraction: extracted traces using subpixel tracking</p> <p>Tables in *.mqa format hold pixel row and column of extracted optical marker (top,transverse, botteom) for respective bow force (3=medium, 5=low,6=high).</p> <p>&nbsp;</p> <p>* Data, 2nd level of abstraction:&nbsp;angle of torsional displacement as derived from optical markers and geometry, versus bow force</p> <p>torsion_angle_vs_3_force_levels (eps, and MATLAB fig).</p> <p>&nbsp;</p> <p>* String properties</p> <p>mass per unit length &nbsp; &nbsp;g/m &nbsp; &nbsp;6.15</p> <p>diameter &nbsp; &nbsp;mm &nbsp; &nbsp;1.19</p> <p>nominal tension &nbsp; &nbsp;N &nbsp; &nbsp;121</p> <p>transverse wave speed <em>v<sub>tra</sub></em>&nbsp;&nbsp; &nbsp;m/s &nbsp; &nbsp;133</p> <p>transverse wave impedance <em>Z<sub>0</sub></em>&nbsp;&nbsp; &nbsp;kg/s &nbsp; &nbsp;0.93</p> <p>torsional fundamental frequency &nbsp; &nbsp;Hz &nbsp; &nbsp;543</p> <p>torsional wave speed <em>v<sub>tor &nbsp; &nbsp;</sub></em>m/s &nbsp; &nbsp;738</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2018View details →
zenodo36/100

Data and Code for "Topological atom-optics and beyond with knotted quantum wave functions"

<p>This folder contains data files and Mathematica 12 Student Edition files for processing the data files and generating figures for the paper &ldquo;<em>Topological atom optics and beyond with knotted quantum wavefunctions</em>&rdquo;, authored by M. Jayaseelan, J. D. Murphree, J. T. Schultz, J. Ruostekoski, and N. P. Bigelow.</p> <p>&nbsp;</p> <ol> <li>Folder &ldquo;Data_Only&rdquo; contains *.csv and *.SPE files for each of the following magnetic phases: <ul> <li> <ol> <li>Polar</li> <li>Cyclic</li> <li>Biaxial Nematic</li> </ol> </li> </ul> </li> <li>Folder Fig2_Polar_code contains&nbsp; <ul> <li> <ol> <li>Data for the Polar magnetic phase (duplicated from Data_Only folder): etau.SPE and e.csv</li> <li>e_imGData, e_imGDataC, e_imLGData, e_imLGDataC: *.csv files that are output as intermediate data processing steps.</li> <li>Fig2_KnotsAtomsPolar_v2.nb: Mathematica file that produces the figures for Fig. 2</li> </ol> </li> </ul> </li> <li>Folder Fig3_Cyclic_code contains&nbsp; <ul> <li> <ol> <li>Data for the Cyclic magnetic phase (duplicated from Data_Only folder): lor_atau.SPE and lor_a_tau.csv</li> <li>lor_a_imGData, lor_a_imG0Data, lor_a_imLGData: *.csv files that are output as intermediate data processing steps.</li> <li>Fig3_KnotsAtomsCyclic_v2.nb: Mathematica file that produces the figures for Fig. 3</li> </ol> </li> </ul> </li> <li>Folder Fig4_Cyclic_code contains&nbsp; <ul> <li> <ol> <li>Fig4_KnotsAtomsCyclic_v2.nb: Mathematica file that produces the figures for Fig. 4</li> </ol> </li> </ul> </li> <li>Folder Fig5_BN_code contains&nbsp; <ul> <li> <ol> <li>Data for the BN magnetic phase (duplicated from Data_Only folder): sk_ltau.SPE and sk_l.csv</li> <li>sk_l_imGData, sk_l_imLGData: *.csv files that are output as intermediate data processing steps.</li> <li>Fig5_KnotsAtomsBN_v2.nb: Mathematica file that produces the figures for Fig. 5</li> </ol> </li> </ul> </li> <li>Folder Fig6_Fig7_BN_code contains&nbsp; <ul> <li> <ol> <li>Fig6_Fig7_KnotsAtomsBN_v2.nb: Mathematica file that produces the figures for Fig. 6 and Fig.7</li> </ol> </li> </ul> </li> </ol>

opencc-by-4.0Mar 2023View details →
zenodo32/100

Insights from GRBs for optical follow-up of gravitational-wave counterparts

<p>Public data release for the paper "Insights from GRBs for optical follow-up of gravitational-wave counterparts". Includes afterglow lightcurves, skymaps from GW simulations, and scripts for using the scheduler and making figures.</p>

opencc-by-4.0Mar 2024View details →
zenodo32/100

Data in "The uncertainties in the laboratory-measured short-wave refractive indices of mineral dust aerosols and the derived optical properties: A theoretical assessment"

<p>This is the data for publication "The uncertainties in the laboratory-measured short-wave refractive indices of mineral dust aerosols and the derived optical properties: A theoretical assessment"</p> <p>Version 1: data</p> <p>Version 2: rename the data files and add a readme file</p>

opencc-by-4.0Apr 2024View details →
ClinicalTrials.gov32/100

5Fr Bipolar Electrode vs. Conical Optical 5Fr Fibers for Dual Wave-length Diode Laser for Hysteroscopic Polypectomy

ClinicalTrials.gov study NCT06526962. IPD Sharing: UNDECIDED. Countries: 1. Publications: 15.

restrictedIPD-UNDECIDEDFeb 2026View details →
zenodo28/100

Spin wave optics for gravitational waves

<p>This is supplementary material<span>&nbsp;for paper </span><a href="https://arxiv.org/abs/2408.03289">arXiv:2408.03289</a><span>.</span></p>

opencc-by-4.0Aug 2024View details →
ClinicalTrials.gov28/100

Validation of Optical Device for Aortic Pulse Wave Velocity Measurement

ClinicalTrials.gov study NCT05400421. IPD Sharing: NO. Countries: 0. Publications: 10.

closedIPD-NOFeb 2026View details →
zenodo20/100

Semi-automatic segmentation of optic radiations and LGN, and their relationship to EEG alpha waves

<p>Spreadsheet containing structural and functional data</p>

opencc-zeroMay 2016View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record