RADIO PHYSICS AND RADIO ASTRONOMY

PACS numbers: 95.75.Wx, 95.85.Bh 

Purpose: Study of the variability of flux density of extragalactic radio sources (3C 273, 3C 120, 3C 345, 3C 446, 3C 454.3, OJ 287, OT 081, BL Lac, DA 55, CTA 102) according to a long-term (1965–2011) monitoring at 14.5, 8, 4.8 GHz made with a 26-m telescope of the University of Michigan. Making up a catalog of quasi-periods values and their properties, as well as using this latter to predict the flux changes after 2011 at 14.5 GHz.

Design/methodology/approach: Using wavelet analysis, bandpass filtering and singular spectrum analysis (Caterpillar-SSA) the information is obtained on the values and properties of quasiperiods of radio flux density change, separately for the longterm and short-term variability components. Using these values, for the first time the forecasting with the two methods – harmonic and autoregressive linear prediction, has been made.

Findings: The catalog of quasi-periodic components of flux density variability is compiled for 10 radio sources, forming dynamics of their activity. The variability of extragalactic radio sources is shown to be formed by adding the quasi-periodic components on different time scales. The results of forecasts showed good compliance with real observations from MOJAVE database. Autoregression method is preferred for a short-term forecasting of flux density changes for radio sources with complex processes of variability.

Conclusions: Presented values and properties of quasi-periods are designed to build theoretical models of short-term and longterm variabilities of extragalactic radio sources. The ability to predict changes in flux density of extragalactic radio sources using their variability data enables efficient planning of observation programs.

Manuscript submitted 12.06.2016

Radio phys. radio astron. 2016, 21(3): 161-188

REFERENCES

1. WENGER, M., OCHSENBEIN, F., EGRE, D., DUBOIS, P., BONNAREL, F., BORDE, S., GENOVA, F., JASNIEWICZ, G., LALOË, S., LESTEVEN, S. and MONIER, R., 2000. The SIMBAD astronomical database. The CDS reference database for astronomical objects. Astron. Astrophys. Suppl. vol. 143, pp. 9–22. DOI: https://doi.org/10.1051/aas:2000332

2. KOMBERG, B. V. and REPIN, S. V., 2014. Universe star islands with relativistic "geysers" in the centers (Galaxy on "desktop"). Moscow: Yanus-K Publ. (in Russian).

3. RIEGER F. M., 2005. Periodic variability and binary black hole systems in blazars. AIP Conf. Proc. vol. 745, pp. 487–492. DOI: https://doi.org/10.1063/1.1878450

4. DE VRIES, W. H., BECKER, R. H., WHITE R. L. and LOOMIS, C., 2005. Structure Function Analysis of Long-Term Quasar Variability. Astron. J. vol. 129, no. 2, pp. 615–629. DOI: https://doi.org/10.1086/427393

5. COWPERTHWAITE, P. S. and REYNOLDS, C. S., 2012. The Central Engine Structure of 3C120: Evidence for a Retrograde Black Hole or a Refilling Accretion Disk. Astrophys. J. Lett. vol. 752, no. 2, id. L21. DOI: https://doi.org/10.1088/2041-8205/752/2/L21

6. MARSCHER, A. P., 2006. Relativistic Jets in Active Galactic Nuclei. AIP Conf. Proc. vol. 856, pp. 1–22. DOI: https://doi.org/10.1063/1.2356381

7. MIZUNO, Y., LYUBARSKY, Yu., NISHIKAWA, K.-I. and HARDEE, P. E., 2012. Three-Dimensional Relativistic Magnetohydrodynamic Simulations of Current-Driven Instability. III. Rotating Relativistic Jets. Astrophys. J. vol. 757, no. 1, id. 16. DOI: https://doi.org/10.1088/0004-637X/757/1/16

8. KING, A. R., PRINGLE, J. E., WEST, R. G. and LIVIO, M., 2004. Variability in black hole accretion discs. Mon. Not. R. Astron. Soc. vol. 348, is. 1, pp. 111–122. DOI: https://doi.org/10.1111/j.1365-2966.2004.07322.x

9. MATSUMOTO, R., KATO, S., and HONMA, F., 1989. Chapter 16. Nonlinear Pulsation in the Transonic Region of Geometrically Thin Accretion Disks. In: F. MEYER,W. J. DUSCHL, J. FRANK, and E. MEYER-HOFMEISTER, eds. Theory of Accretion Disks. Netherlands: Springer, pp. 167–172. DOI: https://doi.org/10.1007/978-94-009-1037-9_16

10. FAN, J. H., LIU, Y., YUAN, Y. H., WANG, H. G., WANG, Y. X., GUPTA, A. C., YANG, J. H., LI, J., ZHOU, J. L., XU, S. X., CHEN, J. L., LIU, F. and LI, Y. Z., 2006. Radio variability properties of a sample of 168 radio sources: Periodicity analysis. Chin. J. Astron. Astrophys. vol. 6, suppl. 2, pp. 333–336. DOI: https://doi.org/10.1088/1009-9271/6/S2/62

11. HOVATTA, T., LEHTO, H. J. and TORNIKOSKI, M., 2008. Wavelet analysis of a large sample of AGN at high radio frequencies. Astron. Astrophys. vol. 488, no. 3, pp. 897–903. DOI: https://doi.org/10.1051/0004-6361:200810200

12. HUGHES, P. A., ALLER, H. D. and ALLER, M. F., 1992. The University of Michigan radio astronomy data base. I - Structure function analysis and the relation between BLLacertae objects and quasi-stellar objects. Astrophys. J. vol. 396, No. 2, pp. 469–486. DOI: https://doi.org/10.1086/171734

13. ALLER, H. D., ALLER, M. F., LATIMER, G. E. and HODGE, P. E., 1985. Spectra and Linear Polarizations of Extragalactic Variable Sources at Centimeter Wavelengths. Astrophys. J. Suppl. Ser. vol. 59, pp. 513–768. DOI: https://doi.org/10.1086/191083

14. GAYDYSHEV, I., 2001. Data processing and analysis: Special handbook. St. Petersburg: Piter Publ. (in Russian).

15. DAVYDOV, A. V., 2007-2010. Digital Signal Processing:Thematic lectures. Yekaterinburg: Ural State Mining University, Department of Geoinformatics (in Russian).

16. SMOLENTSEV, N. K., 2008. Wavelet Theory Fundamentals. Wavelets in Matlab. Moscow: DMK Press Publ. (in Russian).

17. BOZHOKIN, S. V., 2012. Continuous wavelet transform and exactly solvable model of nonstationary signals. Tech. Phys. vol. 57, is. 7, pp. 900–906.

18. MALLAT, S. A., 1998. Wavelet Tour of Signal Processing. San Diego, CA: Academic Press.

19. TORRENCE, C. and COMPO, G. P., 1998. A practical guide to wavelet analysis. Bul. Amer. Met. Soc. vol. 79, no. 1, pp. 61–78. DOI: 10.1175/1520-0477(1998)07960;0061:apgtwa62;2.0.co;2

20. ASTAFIEVA, N. M., 1996. Wavelet analysis: basic theory and some applications. Uspekhi Fizicheskikh Nauk. vol. 166, no. 11, pp. 1145–1170 (in Russian). DOI: https://doi.org/10.3367/UFNr.0166.199611a.1145

21. ALEXANDROV, F. I. and GOLYANDINA, N. E., 2004.The automatic extraction of time series trend and periodical components with the help of the "Caterpillar"-SSA approach. Exponenta Pro. Mathematics in applications. no. 3–4, pp. 54–61 (in Russian).

22. GOLYANDINA, N. E., 2004. The"Caterpillar"-SSA method: time series analysis (User manual). St. Petersburg: St. Petersburg University Publ. (in Russian).

23. CHISTYAKOVA, A. A. and SHAMSHA, B. V., 2011. Identification of the structure of nonstationary time series with the singular spectrum analysis method. Radіoelektronіc and computer systems. vol. 4 (52), pp. 105–111. (in Russian).

24. SHIMANOV, S. N., TSYMBAL, V. A., PRASOLOV, V. A. and FRANKOV, S. V., 2015. Adaptive digital filtering of signals against white Gaussian noise based on singular expansion in linear manifolds. In: Izvestija Tulskogo gosudarstvennogo universiteta. Tekhnicheskie nauki. Tula, Russia: Publishing house of TULGU. vol. 11, pp. 128–136 (in Russian).

25. ABRAHAM, Z. and ROMERO, G. E., 1999. Beaming and precession in the inner jet of 3C 273. Astron. Astrophys. vol. 344, no. 1, pp. 61–67.

26. BI XIONGWEI, HE WANQUAN, TIAN JIAJIN, ZHANG QINGYOU and CAI QUN,2012. Analysis of Multi-Wavelength Variation Periods of the Quasar 3C 273. Astron. Res. Technol. vol. 9, no. 4, pp. 339–347.

27. MAO LI-SHENG, 2007. A Possible Periodicity in the Radio Light Curves of 3C 120. Astron. Res. Technol. vol. 4, no. 4, pp. 307–312.

28. BELOKON', E. T., 1987. 3C 120: Connection between the optical variability and superluminal components of the millisecond radio structure. Astrophysics. vol. 27, no. 3, pp. 588–598. DOI: https://doi.org/10.1007/BF01012448

29. VOL'VACH, A. E., KUTKIN, A. M., VOL'VACH, L. N., LARIONOV, M. G., LAKHTEENMAKI, A., TORNIKOSKI, M., NIEPPOLA, E., TAMMI, J., SAVOLAINEN, P., LEON-TAVARES, J., ALLER, M. F. and ALLER, H. D., 2013. Results of long-term monitoring of 3C 273 over a wide range of wavelengths. Astron. Rep. vol. 57, no. 1, pp. 34–45. DOI: https://doi.org/10.1134/S1063772912050083

30. DONG FUTONG, ZHANG ZUOJING, MAO LISHENG, ZHANG XIONG, ZHENG YONGGANG and TANG LING, 2010. Wavelet Analysis of the Variability Periodicity Data of Quasar 3C 345. Acta Astronomica Sinica. vol. 51, no. 2, pp. 117–126.

31. QIAN SHAN-JIE, WITZEL, A., ZENSUS, J. A., KRICHBAUM, T. P., BRITZEN, S. and ZHANG XI-ZHEN, 2009. Periodicity of the ejection of superluminal components in 3C 345. Res. Astron. Astrophys. vol. 9, is. 2, pp. 137–150. DOI: https://doi.org/10.1088/1674-4527/9/2/003

32. KLARE, J., ZENSUS, J. A., LOBANOV, A. P., ROS, E.,KRICHBAUM, T. P. and WITZEL, A., 2005. Quasi-PeriodicChanges in the Parsec-Scale Jet of 3C 345. In: J. ROMNEY and M. REID, eds. Future Directions in High Resolution Astronomy: The 10th Anniversary of the VLBA,ASP: Conf. Proc. San Francisco, USA: Astronomical Societyof the Pacific. vol. 340. pp. 40.

33. BABADZHANYANTS, M. K. and BELOKON', E. T., 1984. Properties of optical variability of the quasar 3C 345. Astrophysics. vol. 21, is. 2, pp. 461–469. DOI: https://doi.org/10.1007/BF01813647

34. VOLVACH, A. E., VOLVACH, L. N., LARIONOV, M. G., ALLER, H. D., ALLER, M. F., YUROVSKIY, Yu. Yu. and RYABOV, M. I., 2006. Flux density evolution of the sources 3C 273, 3C 279 and 3C 454.3 at the frequencies102 MHz – 36.8 GHz. Astron. Astrophys. Trans. vol. 25, no. 5–6, pp. 385–391. DOI: https://doi.org/10.1080/10556790601135059

35. QIAN SHAN-JIE, KUDRYAVTSEVA, N. A., BRITZEN, S., KRICHBAUM, T. P., GAO LONG, WITZEL, A., ZENSUS,J. A., ALLER, M. F., ALLER H. D. and ZHANGXI-ZHEN, 2006. A Possible Periodicity in the Radio Light Curves of 3C 454.3. Chinese J. Astron. Astrophys. vol. 7, no. 3, pp. 364–374. DOI: https://doi.org/10.1088/1009-9271/7/3/05

36. KELLY, B. C., HUGHES, P. A., ALLER, H. D. and ALLER,M. F., 2003. The Cross-Wavelet Transform and Analysis of Quasi-periodic Behavior in the Pearson-Readhead VLBI Survey Sources. Astrophys. J. vol. 591, no. 2,pp. 695–714. DOI: https://doi.org/10.1086/375511

37. WEIZHAO SHI, XIANG LIU and HUAGANG SONG,2007. A new model for the periodic outbursts of the BL Lac object OJ287. Astrophys. Space Sci. vol. 310, is. 1, pp. 59–63. DOI: https://doi.org/10.1007/s10509-007-9413-z

38. HUGHES, P. A., ALLER, H. D. and ALLER, M. F., 1998. Extraordinary Activity in the BL Lacertae Object OJ 287. Astrophys. J. vol. 503, no. 2, pp. 662– 673. DOI: https://doi.org/10.1086/306014

39. ISHIDA, T., FUJISAWA, K., KINO, M. and NIINUMA, K., 2012. A short-term flare on a time scale of 20 days in the BL Lac object OT 081. In: 11th European VLBI NetworkSymposium & Users Meeting, Bordeaux, France, October 9-12: Symp. Proc. id. 101.

40. HUMRICKHOUSE, C. and WEBB, J. R., 2008. Wavelet Analysis of Microvariability in Blazars 0716+714, ON231 and BL Lac. Journal of the Southeastern Association for Research in Astronomy. vol. 2, pp. 23–29.

41. GUO, Y. C., HU, S. M., XU, C., LIU, C. Y., CHEN, X., GUO, D. F., MENG, F. Y., XU, M. T. and XU, J. Q., 2015. Long-term optical and radio variability of BL Lacertae. New Astron. vol. 36, pp. 9–18. DOI: https://doi.org/10.1016/j.newast.2014.09.011

42. KUDRYAVTSEVA, N. A. and PYATUNINA, T. B., 2006. A search for periodicity in the light curves of selected blazars. Astron. Rep. vol. 50, is. 1, pp. 1–11. DOI: https://doi.org/10.1134/S106377290601001X

43. BARBIERI, C., VIO, R., CAPPELLARO, E. and TURRANO, M., 1990. The optical variability of the quasar 3C 446. Astrophys. J. vol. 359. pp. 63–66. DOI: https://doi.org/10.1086/169033

44. LOMB, N. R., 1976. Least-squares frequency analysis of unequally spaced data. Astrophys. Space Sci. vol. 39, is. 2, pp. 447–462. DOI: https://doi.org/10.1007/BF00648343

45. SCARGLE, J. D., 1982. Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis ofunevenly spaced data. Astrophys. J. vol. 263, pp. 835–853.DOI: https://doi.org/10.1086/160554

46. HAO JING ZHANG, GANG ZHAO and XIONG ZHANG, 2010. The periodicity of 3C 273's radio light curve at 15 GHz found by the wavelet method. Science China Physics, Mechanics and Astronomy. vol. 53, is. 1, pp. 252–255.

47. HUAI-ZHEN LI, GUANG-ZHONG XIE, SHU-BAIZHOU, HONG-TAO LIU, GUANG-WEI CHA, LI MAand LI-SHENG MAO, 2006. Periodicity Analysis of the Light Curve of 3C 454.3. Chin. J. Astron. Astrophys. vol. 6, no. 4, pp. 421–430. DOI: https://doi.org/10.1088/1009-9271/6/4/04

48. XU YUN-BING, ZHANG HAO-JING and WANG LIHENG,2010. A Study of the Light Curve Period of BL Lac OJ 287. Journal of Yunnan Normal University (Natural Sciences Edition). vol. 4, pp. 1–4.

49. ZHANG, X., XIE, G. Z. and BAI, J. M., 1998. A historical light curve of 3C 345 and its periodic analysis. Astron. Astrophys. vol. 330, pp. 469–473.

50. ZHANG HAO-JING and ZHANG XIONG, 2007. A study of the light curve periodic behavior of BL Lac object S5 0716+714. Acta Physica Sinica. vol. 56, is. 7, pp. 4305–4311.

51. MORDVINOV, A. V., 1986. Prediction of monthly indices of solar activity F10.7 on the basis of a multiplicative autoregression model. Byulletin Solnechnye Dannye Akademii Nauk USSR. no. 1985/12, pp. 67–73.

52. LIU SI-QING, ZHONG QIU-ZHEN, WEN JING and DOU XIAN-KANG, 2010. Modeling Research of the 27-day Forecast of 10.7 cm Solar Radio Flux (I). Chin. Astron. Astrophys. vol. 34, is. 3, pp. 305–315. DOI: https://doi.org/10.1016/j.chinastron.2010.07.006

53. KANE, R. P. and TRIVEDI, N. B., 1985. Periodicitiesin sunspot numbers. J. Geomagn. Geoelectricity. vol. 37, no. 12, pp. 1071–1085. DOI: https://doi.org/10.5636/jgg.37.1071

54. VASEGHI SAEED, V., 2006. Advanced digital signal processing and noise reduction. Chichester, England: JohnWiley & Sons Ltd.

55. MARPLE, S. L., 1987. Digital spectral analysis with applications. Englewood Cliffs, N.J.: Prentice-Hall, Inc.

56. MAKHOUL, J., 1975. Linear prediction: A tutorial review. Proc. IEEE. vol. 63, is. 4, pp. 561–580. DOI: https://doi.org/10.1109/PROC.1975.9792

57. SHAKHTARIN, B. I. and KOVRIGIN, V. A. 2005. Methods of spectral estimation of random processes. Moscow: Gelios ARV. (in Russian).

58. KAY, S. M., 1988. Modern spectral estimation: Theoryand application. Englewood Cliffs, N. J. : Prentice-Hall, Inc.

59. RISSANEN, J., 1983. A Universal Prior for Integers and Estimation by Minimum Description Length. Ann. Statist. vol. 11, no. 2, pp. 416–431. DOI: https://doi.org/10.1214/aos/1176346150

60. ULRYCH, T. J. and CLAYTON, R. W., 1976. Time series modelling and maximum entropy. Phys. Earth Planet. Inter. vol. 12, iss. 2–3, pp. 188–200. DOI: https://doi.org/10.1016/0031-9201(76)90047-9

61. TUFTS, D. and KUMARESAN, R., 1982. Singular value decomposition and improved frequency estimation using linear prediction. IEEE Trans. Acoust. Speech Signal Process. vol. 30, is. 4, pp. 671–675. DOI: https://doi.org/10.1109/TASSP.1982.1163927

62. UIKE, M., UCHIYAMA, T. and MINAMITANI, H., 1992. Comparison of linear prediction methods based on singular value decomposition. J. Magn. Reson. vol. 99, is. 2, pp. 363–371. DOI: https://doi.org/10.1016/0022-2364(92)90188-D

63. LISTER, M. L., COHEN, M. H., HOMAN, D. C., KADLER, M., KELLERMANN, K. I., KOVALEV, Y. Y., ROS, E., SAVOLAINEN, T. and ZENSUS, J. A., 2009. MOJAVE: Monitoring of Jets in Active Galactic Nuclei with VLBA Experiments. VI. Kinematics Analysis of a Complete Sample of Blazar Jets. Astron. J. vol. 138, is. 6, pp. 1874–1892. DOI: https://doi.org/10.1088/0004-6256/138/6/1874

64. SUKHAREV, A. L., RYABOV, M. I. and DONSKIKH, G. I., 2016. Predicting Changes in the Radio Emission Fluxesof Extragalactic Sources. Astrophysics. vol. 59, no. 2, pp. 213–226. DOI: https://doi.org/10.1007/s10511-016-9428-7

65. DONSKYKH, G. I., RYABOV, M. I., SUKHAREV, A. L. and ALLER, M., M., 2014. Using the methods of wavelet analysis and singular spectrum analysis in the study of radio source BL Lac. Odessa Astronomical Publications. vol. 27, is. 1, pp. 69–70.