{"id":2165,"date":"2025-05-13T11:30:54","date_gmt":"2025-05-13T10:30:54","guid":{"rendered":"http:\/\/newskbncran.ru\/?page_id=2165"},"modified":"2026-06-04T13:38:50","modified_gmt":"2026-06-04T12:38:50","slug":"26-5-4-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/26-5-4-en\/","title":{"rendered":"26.5.4 en"},"content":{"rendered":"\n

Modeling artificial whistlers in Py\u0421harm<\/strong><\/h2>\n\n\n\n

L.S. Marchenko, R.I. Parovik<\/strong><\/strong><\/strong><\/p>\n\n\n\n

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Abstract.<\/em><\/strong> The work proposed an algorithm for modeling an artificial whistler signal in Python in the PyCharm environment. The algorithm is based on physical and mathematical models of whistler propagation. The proposed algorithm can be used to model signal characteristics, duration, maximum and minimum frequency, and sampling frequency. The algorithm implements the ability to construct the amplitude characteristic of the signal, as well as construct its spectrogram. The model of the artificial whistler signal can be used to solve the problem of whistler recognition in real time.<\/p>\n\n\n\n

Keywords:<\/em><\/strong> whistler, mathematical model, dispersion coefficient, frequency, signal model, spectrogram, Python, PyCharm<\/p>\n\n\n\n

For citation<\/strong>. Marchenko L.S., Parovik R.I.Modeling artificial whistlers in PyCharm. News of the Kabardino-Balkarian Scientific Center of RAS.<\/em>2024. Vol. 26. No. 5. Pp. 53\u201363. DOI: 10.35330\/<\/strong>1991-6639-2024-26-5-53-63<\/p>\n\n\n\n

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References<\/strong><\/summary>\n
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  1. Storey L.R.O. An investigation of whistling atmospherics. Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences<\/em>. 1953. Vol. 246. No. 908. Pp. 113\u2013141.<\/li>\n\n\n\n
  2. Gershman B.N., Korobkov Yu.S. On the theory of propagation of whistling atmospherics. Izvestiya Vuzov. Radiofizika<\/em>. 1958. Vol. 1. No. 2. Pp. 51\u201358. (In Russian)<\/li>\n\n\n\n
  3. Gershman B.N., Ugarov V.A. Propagation and generation of low-frequency electromagnetic waves in the upper atmosphere. Uspekhi Fizicheskikh Nauk<\/em>. 1960. Vol. 72. No. 2. Pp. 235\u2013271. (In Russian)<\/li>\n\n\n\n
  4. Lichtenberger J., Ferencz C., Bodn\u00e1r L. et al. Automatic whistler detector and analyzer system: Automatic whistler detector. Geophys<\/em>. Res. 2008. Vol. 113.<\/li>\n\n\n\n
  5. Koronczay D., Lichtenberger J., Clilverd M.A. et al. The source regions of whistlers. Journal of Geophysical Research: Space-Physics<\/em>, 2019. Vol. 124. Pp. 5082\u20135096.<\/li>\n\n\n\n
  6. Li W., Shen X.-C., Menietti J.D. et al. Global distribution of whistler mode waves in Jovian inner magnetosphere. Geophysical Research Letters<\/em>. 2020. Vol. 47. No. 15. DOI: 10.1029\/2020GL088198<\/li>\n\n\n\n
  7. Morris P.J., Bohdan A., Weidl M.S. et al. Pre-acceleration in the electron foreshock. II. oblique whistler waves. The Astrophysical Journal<\/em>. 2023. Vol. 944. No. 1. Id 13. 12 p. DOI: 10.3847\/1538-4357\/acaec8<\/li>\n\n\n\n
  8. Sonwalkar V.S., Reddy A. Specularly reflected whistler: A low-latitude channel to couple lightning energy to the magnetosphere. Science Advances<\/em>. 2024. Vol. 10. No. 33.eado2657. DOI: 10.1126\/sciadv.ado2657<\/li>\n\n\n\n
  9. Cherneva N.V., Vodinchar G.M., Sivokon V.P. et al. Correlation analysis of fluxes of whistling atmospherics and lightning discharges. Vestnik KRAUNC<\/em>. Fiziko-Matemati\u0441eskie Nauki. Vol. 7. No. 2. Pp. 59\u201367. DOI: 10.18454\/2079-6641-2013-7-2-59-67. (In Russian)<\/li>\n\n\n\n
  10. Sivokon V.P., Bogdanov V.V., Druzhin G.I. et al. Whistler modulation. Geomagnetizm i Aeronomiya. <\/em>2014. Vol. 54. No. 6. Pp. 851\u2013851. DOI: 10.7868\/S0016794014060182. (In Russian)<\/li>\n\n\n\n
  11. Malysh E.A. Algorithm for automatic recognition of whistling atmospherics in real time. Vestnik KRAUNC. Fiziko-Matemati\u0441eskie Nauki. 2015. No. 2(11). Pp. 82\u201387. DOI: 10.18454\/
    2079-6641-2015-11-2-82-87. (In Russian)<\/li>\n\n\n\n
  12. Kichigin G.N. Structure of nonlinear whistlers moving through plasma at an angle to the magnetic field. Solar-Terrestrial Physics. 2018. Vol. 4. No. 1. Pp. 28\u201332. DOI: 10.12737\/szf-41201803. (In Russian)<\/li>\n\n\n\n
  13. Malkin E.I., Kazakov E.A., Sannikov D.V. et al. Statistical relationship between whistlers and sprites according to AWDANET and WWLLN. Vestnik KRAUNC. Fiziko-Matemati\u0441eskie
    Nauki. 2022. Vol. 41. No. 4. Pp. 178\u2013190. (In Russian)<\/li>\n\n\n\n
  14. Aksenov A.P. Differential equations in 2 parts. I part. Moscow: Yurait, 2021. 241 p. (In Russian)<\/li>\n\n\n\n
  15. Bruce M. Van Horn II, Nguyen Q. Hands-on application development with PyCharm: Build applications like a Pro with the ultimate Python development tool. Packt Publishing Ltd.:
    Birmingham. UK, 2023.<\/li>\n\n\n\n
  16. Shaw Z.A. Learn Python the hard way. Addison-Wesley Professional, 2024. 352 p.<\/li>\n<\/ol>\n\n\n\n

    <\/p>\n<\/details>\n\n\n\n

    Information about the authors<\/strong>
     <\/strong><\/summary>\n

    Lyudmila S. Marchenko<\/strong>, Leading Specialist of the Scientific Secretariat, Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences;
    684034, Russia, Kamchatka, Elizovsky District, Paratunka, 7 Mirnaya street;
    Postgraduate Student, Scientific Research Geotechnological Centre Far Eastern Branch of the Russian Academy of Sciences;
    683002, Russia, Petropavlovsk-Kamchatsky, 30 Severo-Vostochnoye highway;
    marchenko@ikir.ru, ORCID: https:\/\/orcid.org\/0000-0003-3634-2443, SPIN-\u043a\u043e\u0434: 8988-7994
    Roman I. Parovik<\/strong>, Doctor of Physical and Mathematical Sciences, Associate Professor, Professor of the Far Eastern Branch of the Russian Academy of Sciences, Leading Researcher, Laboratory of Modeling of Physical Processes, Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences;
    684034, Russia, Kamchatka, Elizovsky District, Paratunka village, 7 Mirnaya street;
    parovik@ikir.ru, ORCID: https:\/\/orcid.org\/0000-0002-1576-1860, SPIN-code: 4295-6894<\/p>\n\n\n\n

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    Modeling artificial whistlers in Py\u0421harm L.S. Marchenko, R.I. Parovik Abstract. The work proposed an algorithm for modeling an artificial whistler signal in Python in the PyCharm environment. The algorithm is based on physical and mathematical models of whistler propagation. The proposed algorithm can be used to model signal characteristics, duration, maximum and minimum frequency, and […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2165","page","type-page","status-publish","hentry"],"yoast_head":"\n26.5.4 en - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/izvestiyakbncran.ru\/index.php\/en\/26-5-4-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"26.5.4 en - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb\" \/>\n<meta property=\"og:description\" content=\"Modeling artificial whistlers in Py\u0421harm L.S. Marchenko, R.I. Parovik Abstract. The work proposed an algorithm for modeling an artificial whistler signal in Python in the PyCharm environment. The algorithm is based on physical and mathematical models of whistler propagation. 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