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26 results for “random numbers”
Electron number density and DM density along random lines of sight from the EAGLE simulation
<p>Here we present the electron number density and the dark matter (DM) density along random lines of sight (LOS) extracted from the EAGLE simulation. The data sets contain two types of LOS - with the cross sections <span class="math-tex">\(25\times20\text{ ckpc}^2\)</span> and <span class="math-tex">\(250\times25\text{ ckpc}^2\)</span>(ckpc is comoving kpc). The datasets contain snapshots of the electron number density at <span class="math-tex">\(23\)</span> different redshift points <span class="math-tex">\(z_i\)</span>, <span class="math-tex">\(0\le z_i \le 6\)</span> and <span class="math-tex">\(37\)</span> snapshots of the DM density for <span class="math-tex">\(0\le z_i\le125\)</span>. At each <span class="math-tex">\(z_i\)</span> there are data for <span class="math-tex">\(100\)</span> random LOS (of each type), having comoving length <span class="math-tex">\(100\text{ cMpc}\)</span> and containing <span class="math-tex">\(5000\)</span> data points each.</p> <p>In addition to the raw data we provide a Wolfram Mathematica notebook <strong>LOS.nb</strong>, that gives examples of usage, namely:</p> <ul> <li>Construction the continuous lines of sight for electron number density or DM density;</li> <li>Calculation the resonant conversion probability between dark photon and usual photon along the LOS;</li> <li>Production of the signal in the model where DM decays into dark photons that are later converted into usual photons.</li> </ul> <p>The details of extraction procedure and LOS properties, as well as physical result in the example models are discussed in the paper <a href="https://arxiv.org/abs/2003.10465">[2003.10465]</a>. Please cite this paper if you use data published here.</p> <p><em>To get started download all files in one folder and run the Mathematica notebook.</em></p> <p>Changes in v2: Bug with names of data files was corrected. Minor changes in LOS.nb</p>
Searching for evidence of algorithmic randomness and incomputability in the output of quantum random number generators
<p>This upload contains the data and code used in the following paper:</p> <p>J. T. Kavulich, B. P. Van Deren, and M. Schlosshauer, “Searching for evidence of algorithmic randomness and incomputability in the output of quantum random number generators,” <em>Phys. Lett. A</em> 388, 127032 (2021), <a href="https://doi.org/10.1016/j.physleta.2020.127032">doi.org/10.1016/j.physleta.2020.127032</a></p> <p>The contents of the data set are as follows:</p> <p>1) Random strings for two QRNGs and four PRNGs. For each RNG, a zip archive provides 100 strings containing 25 x 2<sup>26</sup> = 1,677,721,600 bits each.</p> <p>2) C++ code for the Chaitin–Schwartz–Solovay–Strassen (CSSS) and Borel-normality tests (code.zip, 13 KB).</p> <p>The bulk of this code is not ours, but was written and made publicly available at <a href="https://www.cs.auckland.ac.nz/research/groups/CDMTCS/export/80_random_seqs">this link</a> by the authors of the following paper:</p> <p>A. A. Abbott, C. S. Calude, M. J. Dinneen, and N. Huang, <em>Phys. Scri.</em> 94 (2019) 045103, <a href="https://doi.org/10.1088/1402-4896/aaf36a">doi:10.1088/1402-4896/aaf36a</a></p> <p>We have made just a few small modifications to their original code:</p> <ul> <li>For the CSSS tests, a text file containing the Carmichael numbers (for tests 1–3) and odd composites up to 100 (for test 4) is read in and used to perform the tests. (Note: The set of Carmichael numbers used in the tests was generously provided to us by R. G. E. Pinch. Reference: R. G. E. Pinch, The Carmichael numbers up to 10<sup>21</sup>, in: A.-M. Ernvall-Hytönen (Ed.), Proceedings of Conference on Algorithmic Number Theory, Vol. 46, Turku Centre for Computer Science, Turku, Finland, 2007, pp. 129–131.)</li> <li>We combined the first and second CSSS tests into a single program.</li> <li>We reformatted the display of the output, and included a VERBOSE flag for additional status output.</li> </ul> <p>3) Results from CSSS and Borel-normality tests in Python format (results.zip, 22 KB). This archive also contains a Python script (analyze.py) that reads the result files, carries out the statistical analysis, and displays the plots.</p>
Randomized Trial for Optimal Number of Passes Required for Molecular Profiling During EUS-FNB of Pancreatic Cancer
ClinicalTrials.gov study NCT05043532. IPD Sharing: NO. Countries: 1. Publications: 0.
Randomized Trial Of Platelet Transfusion Policies After Blood Stem Cells Transplantation In Young Children: Reduction Of Number Of Single Platelet Concentrate Donors Per Child
ClinicalTrials.gov study NCT00180986. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Hospital vs. Cell Phone Number Follow-Up Randomization Study
ClinicalTrials.gov study NCT01620827. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparing Number of Injection Sites of In-office Intravesical Onabotulinumtoxin A Treatments for Overactive Bladder: A Randomized Controlled Trial
ClinicalTrials.gov study NCT05157295. IPD Sharing: NO. Countries: 0. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.