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67 results for “dipole”
Raw data for 'Increasing the Modulation Depth of Gd(III)-based Pulsed Dipolar EPR Spectroscopy (PDS) with Porphyrin-GdIII Laser Induced Magnetic Dipole Spectroscopy'
<p>Raw data for 'Increasing the Modulation Depth of Gd(III)-based Pulsed Dipolar EPR Spectroscopy (PDS) with Porphyrin-GdIII Laser Induced Magnetic Dipole Spectroscopy'</p>
Combining Dipole and Loop Coil Elements for 7 T Magnetic Resonance Studies of the Human Calf Muscle - Dataset
<p>Data necessray to reprodice and to verify the results of the publication "Combining Dipoles and Loops for High SNR and Parallel Imaging Performance in Human Calf Muscle Studies at 7 T".</p>
Evolution of plasma properties in 2D particle-in-cell simulations of pulsar polar caps as function of dipole inclination angle
<p>The video shows the evolution of plasma properties in polar cap region of neutron stars from initial simulation conditions to the quasi-periodic pair creation. Three inclination angles of magnetic dipole axis to the star rotation axis are investigate \iota = 0°, 45°, and 90°.</p> <p>The presented quantities are (in rows): Parallel current density, parallel electric field, parallel and perpendicular Poynting flux, electron and positron plasma density, and electron and positron plasma bulk momenta.</p> <p> </p>
Dipole-dipole interaction data for all three regular polytopes
<p>One can find here the raw data employed for discussing the minimum energy for dipoles placed on the vertices of the three families of regular polytopes in any dimension d (up to d=7)</p>
Equatorial dipole: the ghost derailing the Ediacaran geomagnetic field
<p>These documents are all paleomagnetic data for a manuscript submitted to Geophysical Research Letters entitled "Equatorial dipole: the ghost derailing the Ediacaran geomagnetic field" by Zhong et al.</p>
Data presented in "Laser cooled YbF molecules for measuring the electron's electric dipole moment"
<p>Data underlying figure 2, 3 and 4 of the paper</p>
Nanoscale dipole dynamics of protein membranes studied by broadband dielectric microscopy
<p>Original data in support of our publication: Nanoscale dipole dynamics of protein membranes studied by broadband dielectric microscopy</p>
Dataset for: Dynamics of a pair of magnetic dipoles with nonreciprocal interactions due to a moving conductor
<p>Includes data and code for the corresponding article. The code is written in Python with a corresponding list of packages included in the archive. The README.txt file includes more detail on the different folders and files.</p>
Highly Accurate Potential Energy Surface and Dipole Moment Surface for Nitrous Oxide and Ames-296K Infrared Line Lists for 14N216O and Minor Isotopologues
<p>First generation data product and IR line lists for Nitrous Oxide (N<sub>2</sub>O), including an isotopologue-independent <em>ab initio</em> PES of Nitrous Oxide refined with selected HITRAN energy levels below 7000 cm<sup>-1</sup> and experimental <em>G</em><sub>V</sub> at higher energies, an <em>ab initio </em>DMS fitted with CCSD(T)/aug-cc-pV(T,Q,5)Z dipoles computed up to 20,000 cm<sup>-1</sup> above potential minimum and extrapolated to one-electron basis set limit, room temperature IR line lists for 12 N<sub>2</sub>O isotopologues of <sup>14/15</sup>N and <sup>16/17/18</sup>O, and a combination "natural" list with terrestrial abundances. This project is funded by NASA Grant 18-APRA18-0013 through NASA/SETI Institute Co-operative Agreement 80NSSC20K1358. See https://huang.seti.org/N2O/n2o.html for data format and abundance information.</p> <ol> <li>Ames-0 and Ames-1 PES subroutine & coefficient files, and PES refinement related files including reference energy level list and refinement output.</li> <li><em>J</em>=0-150 energy level lists of <sup>14</sup>N<sub>2</sub><sup>16</sup>O and 11 minor isotopologues, computed on the Ames-1 PES. The .zip file contains 12 compressed .tgz files.</li> <li> Ames-1 DMS subroutine & coefficient files, and <em>ab initio</em> data;</li> <li> Ames-296K IR line lists for <sup>14</sup>N<sub>2</sub><sup>16</sup>O and 11 minor isotopologues, each with 100% abundance. Computed using Ames-1 DMS and rovibrational wavefunctions for those energy levels acquired on Ames-1 PES; 12 .tgz files combined into one .zip file</li> <li> A "natural" Ames-296K IR line list for N<sub>2</sub>O, including transitions from all 12 isotopologues with their 296K intensities scaled by terrestrial abundances. Computed on the Ames-1 PES and DMS. </li> <li>ORIGIN project file for related analysis and figures. Use Origin Viewer to open on PC and MAC, <a href="https://www.originlab.com/viewer/dl.aspx">https://www.originlab.com/viewer/dl.aspx</a> </li> </ol> <p>Line List Data Format: (N<sub>2</sub>O is the 4<sup>th</sup> molecules in HITRAN, we use 40+iso#, e.g., 41 - 446; 42 - 456; 43 - 546; 44 - 448; 45 - 447; ...)</p> <pre>iso wavenumber S(Ames-2021) A21(Ames-2021) E"(Ames-1) vtet_qn' vtet_qn" JPS' #root' JPS" #root" J' J" wang_symmetry 43 2540.050758 2.696686E-31 2.829145E+00 4329.863425 0 0 3 1 0 0 50 2 2 109 49 1 2 24 50 49 e e </pre> <p><strong>Table 1</strong>. Abundances and number of IR lines of 12 N<sub>2</sub>O isotopologues in the Ames-296K <em>natural</em> IR line list for N<sub>2</sub>O up to 15,000 cm<sup>-1</sup> and intensity down to 10<sup>-31</sup> cm/molecule. Their wavenumber range <em>f</em><sub>max</sub> (in cm<sup>-1</sup>), intensity max <em>S</em><sub>296K</sub><sup>max</sup>, and intensity sum are also included for each isotopologue. Intensities are scaled by corresponding abundances, in cm<sup>-1</sup>/molecule.cm<sup>-2</sup>.</p> <table align="center"> <tbody> <tr> <td> <p>#</p> </td> <td> <p>Iso</p> </td> <td> <p>Abundance</p> </td> <td> <p><em>#lines</em></p> </td> <td> <p><em>f</em><sub>max</sub> (cm<sup>-1</sup>)</p> </td> <td> <p><em>S</em><sub>296K</sub><sup>max</sup></p> </td> <td> <p>Intensity Sum</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>446</p> </td> <td> <p>0.990333</p> </td> <td> <p>1387178</p> </td> <td> <p>15000</p> </td> <td> <p>1.0217E-18</p> </td> <td> <p>7.2848E-17</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>456</p> </td> <td> <p>3.64093E-3</p> </td> <td> <p>375607</p> </td> <td> <p>14896</p> </td> <td> <p>3.5696E-21</p> </td> <td> <p>2.5816E-19</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>546</p> </td> <td> <p>3.64093E-3</p> </td> <td> <p>411253</p> </td> <td> <p>14970</p> </td> <td> <p>3.7098E-21</p> </td> <td> <p>2.6639E-19</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>448</p> </td> <td> <p>1.98582E-3</p> </td> <td> <p>377008</p> </td> <td> <p>14875</p> </td> <td> <p>1.8990E-21</p> </td> <td> <p>1.4206E-19</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>447</p> </td> <td> <p>3.69280E-4</p> </td> <td> <p>238697</p> </td> <td> <p>13964</p> </td> <td> <p>3.6668E-22</p> </td> <td> <p>2.6767E-20</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>556</p> </td> <td> <p>1.33858E-5</p> </td> <td> <p>93754</p> </td> <td> <p>11640</p> </td> <td> <p>1.2867E-23</p> </td> <td> <p>9.3609E-22</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>548<sup>*</sup></p> </td> <td> <p>7.30080E-6</p> </td> <td> <p>93609</p> </td> <td> <p>10681</p> </td> <td> <p>6.8881E-24</p> </td> <td> <p>5.1939E-22</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>458<sup>*</sup></p> </td> <td> <p>7.30080E-6</p> </td> <td> <p>86397</p> </td> <td> <p>10578</p> </td> <td> <p>6.5998E-24</p> </td> <td> <p>4.9864E-22</p> </td> </tr> <tr> <td> <p>9</p> </td> <td> <p>547<sup>*</sup></p> </td> <td> <p>1.35765E-6</p> </td> <td> <p>55324</p> </td> <td> <p>9065</p> </td> <td> <p>1.3299E-24</p> </td> <td> <p>9.7874E-23</p> </td> </tr> <tr> <td> <p>10</p> </td> <td> <p>457<sup>*</sup></p> </td> <td> <p>1.35765E-6</p> </td> <td> <p>50539</p> </td> <td> <p>8804</p> </td> <td> <p>1.2718E-24</p> </td> <td> <p>9.4017E-23</p> </td> </tr> <tr> <td> <p>11</p> </td> <td> <p>558<sup>*</sup></p> </td> <td> <p>2.68412E-8</p> </td> <td> <p>15761</p> </td> <td> <p>6373</p> </td> <td> <p>2.3969E-26</p> </td> <td> <p>1.8219E-24</p> </td> </tr> <tr> <td> <p>12</p> </td> <td> <p>557<sup>*</sup></p> </td> <td> <p>4.99134E-9</p> </td> <td> <p>8498</p> </td> <td> <p>4964</p> </td> <td> <p>4.6171E-27</p> </td> <td> <p>3.4327E-25</p> </td> </tr> </tbody> </table>
A case study for measuring the relativistic dipole of a galaxy cross-correlation with the Dark Energy Spectroscopic Instrument: Data Repository
<p>This repository contains the synthetic catalogue for the DESI Bright Galaxy Survey produced wit the N-body code <em>gevolution</em>, which is analysed in the manuscript "<a href="https://arxiv.org/abs/2306.04213">A case study for measuring the relativistic dipole of a galaxy cross-correlation with the Dark Energy Spectroscopic Instrument</a>", as well as the raw data of the analysis results. The catalogue "catalogue.csv.bz2" is in the CSV format and can be directly read using the pandas library of python, for example. The columns in the catalogue contain the following information:</p> <p>0. Column index<br> 1. Comoving coordinate x (in units of Mpc/h)<br> 2. Comoving coordinate y (in units of Mpc/h)<br> 3. Comoving coordinate z (in units of Mpc/h)<br> 4. Observed redshift<br> 5. Cosine of the observed polar angle measured with respect to the axis pointing in the direction (1,1,1) along the box diagonal (the original comoving coordinate system has been rotated with an intrinsic z-y-z Euler rotation, first rotating along the z-axis with <span class="math-tex">\(\phi_1 = \pi/4\)</span>, then rotating along the new y axis with <span class="math-tex">\(\theta_2 = \mathrm{arccos}(1/\sqrt{3})\)</span> and setting the final rotation angle to zero, <span class="math-tex">\(\phi_3 = 0\)</span>; hence to get the unperturbed mu and phi coordinates, one needs to rotate the comoving x, y and z coordinates with the corresponding inverse Euler rotation matrix)<br> 6. Observed azimuthal angle phi measured with respect to axis pointing in the direction (1,1,1) along the box diagonal (the original comoving coordinate system has been rotated with an intrinsic z-y-z Euler rotation, first rotating along the z-axis with <span class="math-tex">\(\phi_1 = \pi/4\)</span>, then rotating along the new y axis with <span class="math-tex">\(\theta_2 = \mathrm{arccos}(1/\sqrt{3})\)</span> and setting the final rotation angle to zero, <span class="math-tex">\(\phi_3 = 0\)</span>; hence to get the unperturbed mu and phi coordinates, one needs to rotate the comoving x, y and z coordinates with the corresponding inverse Euler rotation matrix)<br> 7. Logarithm of the luminosity in units of solar luminosity <span class="math-tex">\(L_\odot\)</span><br> 8. Observed flux (in units of <span class="math-tex">\(L_\odot/\mathrm{Mpc}^2\)</span>)<br> 9. Number of particles in each object, plus a uniform noise between 0 and 1. This quantity is the proxy of the mass that was used to assign luminosity to the objects.<br> 10. Flag that identifies the selected objects within each redshift bin. The Flag is 0 for objects not included in the catalogue, and equal to the mean redshift of the bins <span class="math-tex">\(\bar{z} = 0.25, 0.35, 0.45\)</span> for the selected objects. <br> 11. Flag that identifies the bright and faint objects for case 1 (50% bright, 50% faint, no flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 12. Flag that identifies the bright and faint objects for case 2 (90% bright, 10% faint, no flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 13. Flag that identifies the bright and faint objects for case 3 (50% bright, 50% faint, with flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.<br> 14. Flag that identifies the bright and faint objects for case 4 (90% bright, 10% faint, with flux limit). Flag = 0 for non-selected objects, Flag = 1 for bright objects, Flag = 2 for faint objects.</p> <p>The example script "example-script.ipynb" demonstrates how to query the catalogue to extract e.g. the redshift distribution of the objects for the different cases considered in Table 4 of the manuscript.</p> <p>Additionally, the measured dipole data vectors with the jackknife covariance matrices (<span class="math-tex">\(\mathrm{cov}^\mathrm{JK}_{ij}\)</span>), as well as the theoretical data vectors with the theoretical measurement covariance (<span class="math-tex">\(\mathrm{cov}^\mathrm{th}_{ij}\)</span>) and the theoretical prediction covariance (<span class="math-tex">\(\mathrm{cov}^\mathrm{pred}_{ij}\)</span>) are provided within this repository:</p> <ul> <li>In the measurements.tar.gz archive, the measured data for the flux-limited case can be found in the /flux-limit subdirectory, while the data for the case without flux-limit is in /no-flux-limit. The data vectors are named "dipole_<redshift bin>_<% of bright galaxies>.txt. The first column in each of those files is the separation bin <span class="math-tex">\(d\)</span> in <span class="math-tex">\(\mathrm{Mpc}/h\)</span>, the second column is the mean two-point correlation function dipole of the 100 jackknife subsamples, and the third column is the square root of the diagonal part of the jackknife covariance matrix (<span class="math-tex">\(\mathrm{cov}^\mathrm{JK}_{ij}\)</span>). The corresponding jackknife covariance matrices are named "cov_<redshift bin>_<% of bright galaxies>.txt.</li> <li>In the theory.tar.gz archive, the theoretical predictions are found in /flux-limit for the case with flux limit and in /no-flux-limit for the case without flux limit. The theoretical data vectors are named "dipole_<% of bright galaxies>B_z<redshift bin>_gevol.dat". The first column in each of those files is the separation bin <span class="math-tex">\(d\)</span> in <span class="math-tex">\(\mathrm{Mpc}/h\)</span>, the second column the theoretical two-point correlation function dipole and the third column is the square root of the diagonal part of the theoretical prediction covariance matrix (<span class="math-tex">\(\mathrm{cov}^\mathrm{pred}_{ij}\)</span>) . The theoretical measurement covariance matrices are named "covariance_Lp6_<% of bright galaxies>B_z<redshift bin>_gevol.dat", and the theoretical prediction covariance matrices are named "covtheo_<% of bright galaxies>B_z<redshift bin>_gevol.dat". </li> </ul> <p>The example script also demonstrates how to use these data files to reproduce plots of the dipole measurement vs the theoretical prediction like in Figures 6, 7, C1 and C2. The archives need to be unpacked before using the example script to access the data.</p>
Improved Indian Ocean dipole seasonal prediction in the new generation of CMA prediction system
<p>Hindcast experiment Data for Liu et al. (2023), titled "Improved Indian Ocean dipole seasonal prediction in the new generation of CMA prediction system".</p>
Utilizing Novel Dipole Density Capabilities to Objectively Visualize the Etiology of Rhythms in Atrial Fibrillation
ClinicalTrials.gov study NCT02825992. IPD Sharing: NO. Countries: 6. Publications: 1.
Dipole Density Mapping in Supraventricular Tachycardia
ClinicalTrials.gov study NCT02469623. IPD Sharing: UNDECIDED. Countries: 6. Publications: 1.
Data from: Dipoles affect conformational equilibrium
Open the record for dataset details and reuse information.
Persistent Influence of Non-Dipole Geomagnetic Field on East Asia over the Past 4,000 Years
<p>A ~4000-year high-resolution full vector (including inc, dec and rpi) paleomagnetic record derived from the Bohai Sea, China.</p>
The isotopic composition of the French Illimani ice core in the Bolivian Andes supports the east-west South American precipitation dipole from the last deglaciation to the mid-Holocene
<p>Isotopic composition (deuterium and deuterium excess) of the French Illimani ice core drilled in 1999 with a revised dating detailed in the following manuscript:</p> <p>Françoise Vimeux and Amaëlle Landais, 2025. The isotopic composition of the French Illimani ice core in the Bolivian Andes supports the east-west South American precipitation dipole from the last deglaciation to the mid-Holocene. Quaternary Science Reviews 347, https://doi.org/10.1016/j.quascirev.2024.109098.</p>
Optical polarimetric observations of black hole binary Cyg X-1 with DIPol-2
<p>The dataset contains raw polarimetric FITS images of black hole X-ray binary <a href="https://en.wikipedia.org/wiki/Cygnus_X-1">Cyg X-1</a> (and surrounding field), obtained with the DIPol-2 optical CCD polarimeter in three (<em>BVR</em>) filters while mounted on the remotely operated Tohoku 60 cm (T60) telescope at the Haleakala Observatory, Hawaii. The data were collected over 5 observing nights during the week 2022 May 15–21 for about 4 hours each night. During each observing night, a set of calibration images were also obtained. These typically include 7 dark and 7 bias images per filter per night. Bias and dark FITS files have `bias` or `dark` labels in their names.</p>
Dataset for "Particle-in-cell simulations of the fast magnetosonic mode in a dipole magnetic field: 1D along the radial direction"
<p>Dataset used to produce figures in the paper "Particle-in-cell simulations of the fast magnetosonic mode in a dipole magnetic field: 1D along the radial direction"</p>
Orbit-induced rainfall dipole pattern in South Asia over the past 425 ka
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Complementary files for Stability of classical planar dipole matter on regular and aperiodic lattices manuscript
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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.
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.
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.
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.
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.