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3 results for “quantum random numbers”
Hardware-biased quantum random numbers
<p>Bitstring from a hardware-biased quantum random number generator. The data is used in the numerical experiments for the publication "On the effects of biased quantum random numbers on the initialization of artificial neural networks" (<a href="http://arxiv.org/abs/2108.13329">arXiv:2108.13329</a>).</p> <p> </p>
Mbit/s-range alkali vapour spin noise quantum random number generators - DATASETS
<p>Two example datasets. Each dataset consists of 2 files; one, where spin noise is present in the spectrum (noise_on.npy) and one, where spin noise is absent (noise_off.npy). The former is used generate random numbers, while the latter is used to 1. find a baseline threshold \Sigma, as described in the paper, and 2. to find the spin noise spectrum. </p> <p>The spin noise spectrum can be found by subtracting the spectra of the first and second file, as it is only present in the first file. Every dataset should be filtered around the Larmor frequency prior to any bit generation. The width of the band-pass filter should be such that the entirety of the spin noise spectrum is contained.</p> <p>Bit generation is to be done by protocols described in the paper "Mbit/s-range alkali vapour spin noise quantum random number generators". All bitrates are calculated at \Sigma = 5 \sigma, where \sigma is the standard deviation of noise_off.npy for the given experiment.</p> <p>Cs12: Sample rate 50 MHz. Measured at a temperature of approximately 140 degrees C. The Larmor frequency is approximately 670 kHz. There is a large induced gradient present in the system, so the spin noise spectrum is not a Lorentzian shape, but is spread with a full-width half max of 500 kHz . Protocol 1 raw bitrates are approximately 40 kb/s, whereas protocol 2 raw bitrates are approximately 2.40 Mb/s.</p> <p>Cs14: Sample rate 100 MHz. Spin noise measurement (noise_on.npy) has 1G samples (16 bit signed). Background measurement (noise_off.npy) has 10M samples (16 bit signed). Measured at a temperature of approximately 140 degrees C. The Larmor frequency is approximately 440kHz ,T2 is approximately 2e-6 s. This is the dataset presented in the paper. Protocol 1 raw bitrates are approximately 40 kb/s, protocol 2 raw bitrates are approximately 1.97 Mb/s.</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>
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