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14 results for “power spectrum”

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zenodo48/100

Data in: Aging power spectrum of membrane protein transport and other subordinated random walks

<p>Datasets generated in the report &quot;Aging power spectrum of membrane protein transport and other subordinated random walks&quot;. Included data are:</p> <p><strong>Numerical simulations&nbsp;</strong><br> RWdata1.mat: 10,000 realizations, subordinated random walk with Hurst exponent, <em>H</em>=0.3&nbsp;and <span class="math-tex">\(\alpha\)</span>=0.4.<br> RWdata3.mat:&nbsp;10,000 realizations, subordinated random walk with Hurst exponent, <em>H</em>=0.7&nbsp;and <span class="math-tex">\(\alpha\)</span>=0.4.<br> RWdata8.mat:&nbsp;5,000 realizations, subordinated random walk with Hurst exponent, <em>H</em>=0.75&nbsp;and <span class="math-tex">\(\alpha\)</span>=0.8.<br> RWdataCTRW.mat:&nbsp;10,000 realizations, continuous time random walk (CTRW),&nbsp;<span class="math-tex">\(\alpha\)</span>=0.7.</p> <p><strong>Spectra of&nbsp;simulations</strong><br> PSDdata1.mat: Power spectral density (PSD) of a subordinated random walk with Hurst exponent, <em>H</em>=0.3&nbsp;and <span class="math-tex">\(\alpha\)</span>=0.4. Five different realization times are used to compute the PDS: 2^8,&nbsp;2^10,&nbsp;2^12,&nbsp;2^14, and 2^16.<br> PSDdata3.mat:&nbsp;PSD of a subordinated random walk with Hurst exponent, <em>H</em>=0.7&nbsp;and <span class="math-tex">\(\alpha\)</span>=0.4. Five different realization times are used to compute the PDS: 2^8,&nbsp;2^10,&nbsp;2^12,&nbsp;2^14, and 2^16.<br> PSDdata8.mat: PSD of a&nbsp;subordinated random walk with Hurst exponent, <em>H</em>=0.75&nbsp;and <span class="math-tex">\(\alpha\)</span>=0.8.&nbsp;Four&nbsp;different realization times are used to compute the PDS: 2^15,&nbsp;2^16,&nbsp;2^17, and 2^18.<br> PSDs_CTRW.mat: PSD of a&nbsp;continuous-time random walk (CTRW),&nbsp;<span class="math-tex">\(\alpha\)</span>=0.7. Five different realization times are used to compute the PDS: 2^8,&nbsp;2^10,&nbsp;2^12,&nbsp;2^14, and 2^16.</p> <p><strong>Experimental data of Nav1.6 channels in the soma of hippocampal neurons</strong><br> NavMSDtimes.csv: ensemble-averaged (EA) MSD and time-averaged (TA) MSD. The TA-MSD is measured&nbsp;for three observation times, 64, 128, and 256 frames (3.2, 6.4, and 12.8 s).<br> NavPSD.csv: Power spectral density (PSD) measured for&nbsp;three observation times, 64, 128, and 256 frames.</p>

opencc-by-4.0Sep 2021View details →
zenodo48/100

Solar and interplanetary magnetic field data analyzed in "Optimal frequency-domain analysis for spacecraft time series: Introducing the missing-data multitaper power spectrum estimator"

<p>This dataset contains simultaneous measurements of the interplanetary magnetic field magnitude &lt;B&gt;&nbsp;and the sun&#39;s radio flux at 10.7 cm &lt;F10.7&gt;. &lt;B&gt; measurements&nbsp;come from a series of spacecraft located at the L1 point, while&nbsp;&lt;F10.7&gt; was measured by the ongoing monitoring program by&nbsp;Canada&#39;s Dominion Radio Astrophysical Observatory. Bartels rotation-averaged data&nbsp;were downloaded from&nbsp;NASA&#39;s OMNIWeb,&nbsp;https://omniweb.gsfc.nasa.gov/html/ow_data.html. The file contains&nbsp;other solar wind plasma parameters that were not used in the analysis.</p>

opencc-by-4.0Jun 2023View details →
zenodo44/100

Supplementary Data for Inhomogeneous Energy Injection in the 21-cm Power Spectrum: Sensitivity to Dark Matter Decay

<p>This dataset contains the interpolation tables for use with the DM21cm code release as part of "Inhomogeneous Energy Injection in the 21-cm Power Spectrum: Sensitivity to Dark Matter Decay." For details on usage, see the public github repository at: https://github.com/yitiansun/DM21cm.&nbsp;</p>

openmit-licenseDec 2023View details →
zenodo40/100

Data used for the Walther et al (2017) Lya forest power spectrum measurement

<p>The Files "PS_dataset_*.hdf5" contain the masked datasets used in the Walther et al (2017) power spectrum analysis with or without metal masking.</p> <p>They also contain MCMC chains for performing the masking corrections.</p> <p>The README file gives basic usage instructions.</p>

opencc-by-4.0Nov 2017View details →
zenodo40/100

Estimates of the Wavenumber Wavelet Power Spectrum of Magnetic Fluctuations during Magnetic Reconnection Figure Data

<p>This is data for the publication, &quot;Estimates of the Wavenumber Wavelet Power Spectrum of Magnetic Fluctuations during Magnetic Reconnection&quot;.</p>

opencc-by-4.0Dec 2022View details →
zenodo36/100

The 44Ti-powered spectrum of SN 1987A

<p>SN 1987A model at 8 years. Distance 50 kpc assumed.</p>

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

Correlation matrix of power spectrum

<p>Correlation matrix obtained from the BAM halo mock catalogs and the SLICS references computed in real and<br> redshift space.</p>

opencc-by-4.0Nov 2022View details →
zenodo36/100

Power spectrum and reduced bispectrum of halo number-count mock catalogs

<p>Power spectrum (left) and reduced bispectrum (right) computed from sets of halo number-count mock catalogs (of 80 realizations each ) obtained from the calibration of&nbsp; BAM using the TkWEB model as described in . First rows show the mean in each case. The second row shows the ratio of to the reference (RTR) and the third row shows the variance in the respective statistics. The shaded area in the second rows denote the $5\%$ deviation with respect to unity.</p>

opencc-by-4.0Nov 2022View details →
zenodo36/100

Halo power spectrum computed in real and redshift space

<p>Halo power spectrum computed from the halo catalogs in-<br> terpolated on a 4003 mesh, in real (P(k)) and redshift space, the lat-<br> ter represented through the monopole P0(k), the quadrupole P2(k)<br> and the hexadecapole P4(k). The main panels show the mean from<br> 80 SLICS realizations (green dashed line) and the mean from the<br> same number of BAM mocks (solid gray lines). The bottom panels<br> show the ratio between the mean spectra from the BAM mocks to<br> the mean from the SLICS. The gray area in the ratios show the 1&sigma;<br> region computed from the means and their respective errors.</p>

opencc-by-4.0Nov 2022View details →
zenodo32/100

Dark Sky Simulations ds14_a redshift=0 Mass Power Spectrum

<p>Dark Sky Simulations ds14_a redshift=0 &nbsp;Mass Power Spectrum</p>

opencc-by-4.0Apr 2014View details →
zenodo32/100

Density power spectrum of three red giant stars observed by Kepler

<p>Density power spectrum of three red giants stars observed by Kepler in the frequency range 50-280 &micro;Hz. Kepler data are publicly available from the Mikulski Archive for Space Telescopes (MAST) portal at <a href="https://archive.stsci.edu">https://archive.stsci.edu</a>. They have been corrected following Garc&iacute;a et al. (2011, MNRAS 414, L6).</p>

opencc-by-4.0Dec 2021View details →
zenodo32/100

Strength, depth, and geometry of magnetic sources in the crust of the Moon from localized power spectrum analysis

<p>This archive contains data files that can be used to reproduce Figures 7-10 in the article</p> <blockquote> <p>Wieczorek, M. A. (2018) Strength, depth, and geometry of magnetic sources in the crust of the Moon from localized power spectrum analysis, J. Geophys. Res. Planets.</p> </blockquote> <p>The data files contain the final inversion results for the model using magnetized sills, where the full magnetic field to spherical-harmonic degree 449 was employed. For each localized analysis, the best 6 orthogonal localization windows were used that maximized their power within a spherical cap with an angular radius of 8 degrees and with a spherical-harmonic bandwidth of 58. The analyses were performed at the vertices of a quasi equal-area grid with a spacing corresponding to five degrees of latitude. For these models, the file names start with &quot;sills_449_8_58_5&quot;. Each file contains the latitude and longitude (in degrees) of the localization analysis, as well as one other value.</p> <p><br> FILE DESCRIPTIONS</p> <p>sills_449_8_58_5_minchi2r.dat</p> <p>This file contains the minimum reduced chi<sup>2</sup> value of the best-fitting model for each analysis. Uncertainties on the inversion parameters were obtained from Monte Carlo simulations that showed 68.2% and 95.4% of the analyses should have reduced chi<sup>2</sup> values less than 2.133 and 4.082, respectively. Where 1-sigma uncertainties could not be calculated (when the best-fitting misfits were above the 1-sigma limits) the limit was set to +/- 999.e99.</p> <p>sills_449_8_58_5_db.dat<br> sills_449_8_58_5_db_1m.dat<br> sills_449_8_58_5_db_1p.dat</p> <p>The best-fitting depths to the bottom of the magnetized region and their +/- 1-sigma limits (1p/1m).</p> <p>sills_449_8_58_5_dt.dat<br> sills_449_8_58_5_dt_1m.dat<br> sills_449_8_58_5_dt_1p.dat</p> <p>The best-fitting depths to the top of the magnetized region and their +/- 1-sigma limits.</p> <p>sills_449_8_58_5_rdisk.dat<br> sills_449_8_58_5_rdisk_1m.dat<br> sills_449_8_58_5_rdisk_1p.dat</p> <p>The best-fitting angular radii (in km) of the magnetized sills and their +/- 1-sigma limits.</p> <p>sills_449_8_58_5_rkm2v2.dat<br> sills_449_8_58_5_rkm2v2_1m.dat<br> sills_449_8_58_5_rkm2v2_1p.dat</p> <p>The best-fitting (N M^2 V^2)^(1/2) values in A m^2 of the magnetized sills and their +/- 1-sigma limits.<br> &nbsp;</p>

opencc-by-4.0Nov 2017View details →
ClinicalTrials.gov32/100

Evaluation of EEG Power Spectrum in Patients With Traumatic Coma

ClinicalTrials.gov study NCT06321146. IPD Sharing: YES. Countries: 1. Publications: 8.

controlledIPD-YESFeb 2026View details →
zenodo28/100

Emission spectrum of the plasma source at different powers (gas flow:3 L/min) (a)280nm-420nm (b)720nm-860nm.

Open the record for dataset details and reuse information.

opencc-by-4.0Aug 2024View details →

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