Bursts of extensive air showers: chaos vs. stochasticity

Bursts of the count rate of extensive air showers (EAS) lead to the appearance of clusters in time series that represent EAS arrival times. We apply methods of nonlinear time series analysis to twenty EAS cluster events found in the data set obtained with the EAS-1000 prototype array. In particular, we use the Grassberger-Procaccia algorithm to compute the correlation dimension of the time series in the vicinity of the clusters. We find that four cluster events produce signs of chaos in the corresponding time series. By applying a number of supplementary methods we assess that the nature of the observed behaviour of the correlation dimension is likely to be deterministic. We suggest a simple qualitative model that might explain an origin of clusters in general and "possibly chaotic" clusters in particular. Finally, we compare our conclusions with the results of similar investigations performed by the EAS-TOP and LAAS groups.Comment: An extended version of the paper to be submitted to Astroparticle Physics. Version 2: 22 pages, discussion extended, the main part shortened, accepted for publication. Version 1 is still valid (up to a number of typos

Measurement of RudsR_{\text{uds}} and RR between 3.12 and 3.72 GeV at the KEDR detector

Using the KEDR detector at the VEPP-4M $e^+e^-$ collider, we have measured the values of $R_{\text{uds}}$ and $R$ at seven points of the center-of-mass energy between 3.12 and 3.72 GeV. The total achieved accuracy is about or better than $3.3\%$ at most of energy points with a systematic uncertainty of about $2.1\%$. At the moment it is the most accurate measurement of $R(s)$ in this energy range

New precise determination of the \tau lepton mass at KEDR detector

The status of the experiment on the precise $\tau$ lepton mass measurement running at the VEPP-4M collider with the KEDR detector is reported. The mass value is evaluated from the $\tau^+\tau^-$ cross section behaviour around the production threshold. The preliminary result based on 6.7 pb$^{-1}$ of data is $m_{\tau}=1776.80^{+0.25}_{-0.23} \pm 0.15$ MeV. Using 0.8 pb$^{-1}$ of data collected at the $\psi'$ peak the preliminary result is also obtained: $\Gamma_{ee}B_{\tau\tau}(\psi') = 7.2 \pm 2.1$ eV.Comment: 6 pages, 8 figures; The 9th International Workshop on Tau-Lepton Physics, Tau0

Measurement of \Gamma_{ee}(J/\psi)*Br(J/\psi->e^+e^-) and \Gamma_{ee}(J/\psi)*Br(J/\psi->\mu^+\mu^-)

The products of the electron width of the J/\psi meson and the branching fraction of its decays to the lepton pairs were measured using data from the KEDR experiment at the VEPP-4M electron-positron collider. The results are \Gamma_{ee}(J/\psi)*Br(J/\psi->e^+e^-)=(0.3323\pm0.0064\pm0.0048) keV, \Gamma_{ee}(J/\psi)*Br(J/\psi->\mu^+\mu^-)=(0.3318\pm0.0052\pm0.0063) keV. Their combinations \Gamma_{ee}\times(\Gamma_{ee}+\Gamma_{\mu\mu})/\Gamma=(0.6641\pm0.0082\pm0.0100) keV, \Gamma_{ee}/\Gamma_{\mu\mu}=1.002\pm0.021\pm0.013 can be used to improve theaccuracy of the leptonic and full widths and test leptonic universality. Assuming e\mu universality and using the world average value of the lepton branching fraction, we also determine the leptonic \Gamma_{ll}=5.59\pm0.12 keV and total \Gamma=94.1\pm2.7 keV widths of the J/\psi meson.Comment: 7 pages, 6 figure

Search for narrow resonances in e+ e- annihilation between 1.85 and 3.1 GeV with the KEDR Detector

We report results of a search for narrow resonances in e+ e- annihilation at center-of-mass energies between 1.85 and 3.1 GeV performed with the KEDR detector at the VEPP-4M e+ e- collider. The upper limit on the leptonic width of a narrow resonance Gamma(R -> ee) Br(R -> hadr) < 120 eV has been obtained (at 90 % C.L.)

Measurement of main parameters of the \psi(2S) resonance

A high-precision determination of the main parameters of the \psi(2S) resonance has been performed with the KEDR detector at the VEPP-4M e^{+}e^{-} collider in three scans of the \psi(2S) -- \psi(3770) energy range. Fitting the energy dependence of the multihadron cross section in the vicinity of the \psi(2S) we obtained the mass value M = 3686.114 +- 0.007 +- 0.011 ^{+0.002}_{-0.012} MeV and the product of the electron partial width by the branching fraction into hadrons \Gamma_{ee}*B_{h} = 2.233 +- 0.015 +- 0.037 +- 0.020 keV. The third error quoted is an estimate of the model dependence of the result due to assumptions on the interference effects in the cross section of the single-photon e^{+}e^{-} annihilation to hadrons explicitly considered in this work. Implicitly, the same assumptions were employed to obtain the charmonium leptonic width and the absolute branching fractions in many experiments. Using the result presented and the world average values of the electron and hadron branching fractions, one obtains the electron partial width and the total width of the \psi(2S): \Gamma_{ee} =2.282 +- 0.015 +- 0.038 +- 0.021 keV, \Gamma = 296 +- 2 +- 8 +- 3 keV. These results are consistent with and more than two times more precise than any of the previous experiments

Comparative analysis of statistical methods of scientific publications classification in medicine [Сравнительный анализ статистических методов классификации научных публикаций в области медицины]

In this paper the various methods of machine classification of scientific texts by thematic sections on the example of publications in specialized medical journals published by Springer are compared. The corpus of texts was studied in five sections: pharmacology/toxicology, cardiology, immunology, neurology and oncology. We considered both classification methods based on the analysis of annotations and keywords, and classification methods based on the processing of actual texts. Methods of Bayesian classification, reference vectors, and reference letter combinations were applied. It is shown that the method of classification with the best accuracy is based on creating a library of standards of letter trigrams that correspond to texts of a certain subject. It is turned out that for this corpus the Bayesian method gives an error of about 20%, the support vector machine has error of order 10%, and the proximity of the distribution of three-letter text to the standard theme gives an error of about 5%, which allows to rank these methods to the use of artificial intelligence in the task of text classification by industry specialties. It is important that the support vector method provides the same accuracy when analyzing annotations as when analyzing full texts, which is important for reducing the number of operations for large text corpus. © 2020 Institute of Computer Science. All rights reserved