Hostname: page-component-669899f699-tpknm Total loading time: 0 Render date: 2025-05-01T14:18:51.587Z Has data issue: false hasContentIssue false

Long term multi-wavelength spectral variations of blazar S5 0716+714

Published online by Cambridge University Press:  13 December 2024

C. Baheeja*
Affiliation:
Department of Physics, University of Calicut, Malappuram, Kerala, India
Aminabi Thekkoth
Affiliation:
Department of Physics, University of Calicut, Malappuram, Kerala, India
Sunder Sahayanathan
Affiliation:
Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai, India Homi Bhabha National Institute, Mumbai, India
C. D. Ravikumar
Affiliation:
Department of Physics, University of Calicut, Malappuram, Kerala, India
Nilay Bhatt
Affiliation:
Astrophysical Sciences Division, Bhabha Atomic Research Centre, Mumbai, India
*
Corresponding author: C. Baheeja; Email: [email protected]

Abstract

We present a comprehensive analysis of simultaneous, long-term observations of blazar S5 0716+714, covering optical/UV, X-ray, and $\gamma$-ray wavelengths. All available observations of the source by Swift-UVOT/XRT and Fermi-LAT till January 2023 were used, and the spectra were fitted using power-law/log-parabola functions. A detailed correlation study between the best-fit parameters were performed, and our results suggest that the spectral changes observed during high flux states could be associated with the spectral energy distribution shifting towards the blue end. The flux distribution predominantly shows a log-normal/double log-normal behaviour, whereas the index distribution indicates a Gaussian or double Gaussian nature. As a Gaussian variation in the index of a power-law spectrum will result in a log-normal variation in the flux, the observed log-normal variability in blazars may be associated with Gaussian variation in the spectral indices. The observed normal/log-normal variations in indices/fluxes can again be interpreted through bluer when brighter behaviour of the source. Furthermore, the broadband SED during two distinct flux states can be successfully fitted by considering synchrotron, synchrotron self-Compton, and external Compton emission processes. The flux enhancement of the source is predominantly associated with an increase in the bulk Lorentz factor. Additionally, we find that the model curves corresponding to variations in the Lorentz factor have the potential to explain the observed correlations between the spectral parameters. Our study thereby concludes that the spectral variations of blazar S5 0716+714 are primarily associated with changes in the bulk Lorentz factor of the jet.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Astronomical Society of Australia

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Abdo, A. A., et al. 2009, ApJ, 700, 597Google Scholar
Abdo, A. A., et al. 2010, ApJ, 716, 30Google Scholar
Ackermann, M., et al. 2011, ApJ, 743, 171Google Scholar
Aharonian, F. 2000, NewAs, 5, 377CrossRefGoogle Scholar
Anderhub, H., et al. 2009, ApJ, 704, L129Google Scholar
Baheeja, C., Sahayanathan, S., Rieger, F. M., Jagan, S. K., & Ravikumar, C. D. 2022, MNRAS, 514, 3074CrossRefGoogle Scholar
Bartoli, B., et al. 2012, ApJ, 758, 2Google Scholar
Begelman, M. C., & Sikora, M. 1987, ApJ, 322, 650Google Scholar
Błażejowski, M., Sikora, M., Moderski, R., & Madejski, G. M. 2000, ApJ, 545, 107CrossRefGoogle Scholar
Blumenthal, G. R., & Gould, R. J. 1970, RvMPh, 42, 237CrossRefGoogle Scholar
Buson, S., et al. 2023, arXiv e-prints, p. arXiv:2305.11263Google Scholar
Chandra, S., Zhang, H., Kushwaha, P., Singh, K. P., Bottcher, M., Kaur, N., & Baliyan, K. S. 2015, ApJ, 809, 130CrossRefGoogle Scholar
Chen, A. W., et al. 2008, A&A, 489, L37Google Scholar
Costamante, L., Cutini, S., Tosti, G., Antolini, E., & Tramacere, A. 2018, MNRAS, 477, 4749CrossRefGoogle Scholar
D’arcangelo, F. D., et al. 2009, ApJ, 697, 985Google Scholar
Dermer, C. D., & Menon, G. 2009, High Energy Radiation from Black Holes: Gamma Rays, Cosmic Rays, and NeutrinosGoogle Scholar
Dermer, C. D., & Schlickeiser, R. 1993, ApJ, 416, 458CrossRefGoogle Scholar
Dermer, C. D., Schlickeiser, R., & Mastichiadis, A. 1992, A&A, 256, L27Google Scholar
Evans, P. A., et al. 2009, MNRAS, 397, 1177Google Scholar
Fan, J. H., et al. 2016, ApJSS, 226, 20Google Scholar
Ferrero, E., Wagner, S. J., Emmanoulopoulos, D., & Ostorero, L. 2006, A&A, 457, 133CrossRefGoogle Scholar
Finke, J. D. 2016, ApJ, 830, 94CrossRefGoogle Scholar
Foschini, L., et al. 2006, A&A, 455, 871Google Scholar
Geng, X., et al. 2020, ApJ, 904, 67Google Scholar
Ghisellini, G., & Tavecchio, F. 2009, MNRAS, 397, 985CrossRefGoogle Scholar
Ghisellini, G., et al. 1997, A&A, 327, 61Google Scholar
Ghisellini, G., Tavecchio, F., Foschini, L., & Ghirlanda, G. 2011, MNRAS, 414, 2674CrossRefGoogle Scholar
Giommi, P., et al. 1999, A&A, 351, 59Google Scholar
Gorbachev, M. A., Butuzova, M. S., Sergeev, S. G., Nazarov, S. V., & Zhovtan, A. V. 2022, ApJ, 928, 86CrossRefGoogle Scholar
Gupta, A. C., et al. 2012, MNRAS, 425, 1357Google Scholar
Harrison, F. A., et al. 2013, ApJ, 770, 103Google Scholar
IceCube Collaboration, et al. 2018, Sci, 361, eaat1378Google Scholar
Jagan, S. K., Sahayanathan, S., Rieger, F. M., & Ravikumar, C. D. 2021, MNRAS, 506, 39964006CrossRefGoogle Scholar
Jones, F. C. 1968, PhRv, 167, 1159CrossRefGoogle Scholar
Jorstad, S. G., et al. 2017, ApJ, 846, 98CrossRefGoogle Scholar
Kalberla, P. M. W., Burton, W. B., Hartmann, D., Arnal, E. M., Bajaja, E., Morras, R., & Pöppel, W. G. L. 2005, A&A, 440, 775782CrossRefGoogle Scholar
Kardashev, N. S. 1962, SvA, 6, 317Google Scholar
Khatoon, R., Shah, Z., Misra, R., & Gogoi, R. 2020, MNRAS, 491, 1934CrossRefGoogle Scholar
Kuehr, H., Witzel, A., Pauliny-Toth, I. I. K., & Nauber, U. 1981, A&AS, 45, 367Google Scholar
Kun, E., Britzen, S., Frey, S., Gabányi, K. É., & Gergely, L. Á. 2023, MNRAS, 526, 4698CrossRefGoogle Scholar
Larionov, V. M., et al. 2013, ApJ, 768, 40CrossRefGoogle Scholar
Liao, N. H., Bai, J. M., Liu, H. T., Weng, S. S., Chen, L., & Li, F. 2014, ApJ, 783, 83Google Scholar
Lin, Y. C., et al. 1995, ApJ, 442, 96Google Scholar
MAGIC Collaboration, 2018, A&A, 619, A45Google Scholar
Malik, Z., Shah, Z., Sahayanathan, S., Iqbal, N., & Manzoor, A. 2022, MNRAS, 514, 4259CrossRefGoogle Scholar
Mannheim, K. 1993, A&A, 269, 67Google Scholar
Maraschi, L., Ghisellini, G., & Celotti, A. 1992, ApJ, 397, L5Google Scholar
Marscher, A. P., & Gear, W. K. 1985, ApJ, 298, 114CrossRefGoogle Scholar
Mücke, A., Protheroe, R. J., Engel, R., Rachen, J. P., & Stanev, T. 2003, APh, 18, 593Google Scholar
Narayan, R., & Piran, T. 2012, MNRAS, 420, 604CrossRefGoogle Scholar
Nilsson, K., Pursimo, T., Sillanpää, A., Takalo, L. O., & Lindfors, E. 2008, A&A, 487, L29Google Scholar
Plavin, A. V., Burenin, R. A., Kovalev, Y. Y., Lutovinov, A. A., Starobinsky, A. A., Troitsky, S. V., & Zakharov, E. I. 2024, JCAP, 2024, 133CrossRefGoogle Scholar
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. 1992, Numerical recipes in FORTRAN. The art of scientific computingGoogle Scholar
Prince, R., Das, S., Gupta, N., Majumdar, P., & Czerny, B. 2024, MNRAS, 527, 8746Google Scholar
Raiteri, C. M., et al. 2003, A&A, 402, 151Google Scholar
Rani, B., et al. 2010a, MNRAS, 404, 1992Google Scholar
Rani, B., Gupta, A. C., Joshi, U. C., Ganesh, S., & Wiita, P. J. 2010b, ApJ, 719, L153CrossRefGoogle Scholar
Rani, B., Gupta, A. C., Joshi, U. C., Ganesh, S., & Wiita, P. J. 2010c, ApJL, 719, L153CrossRefGoogle Scholar
Rani, B., Krichbaum, T. P., Lott, B., Fuhrmann, L., & Zensus, J. A. 2013a, ASR, 51, 2358CrossRefGoogle Scholar
Rani, B., et al. 2013b, A&A, 552, A11Google Scholar
Rani, B., Krichbaum, T. P., Marscher, A. P., Hodgson, J. A., Fuhrmann, L., Angelakis, E., Britzen, S., & Zensus, J. A. 2015, A&A, 578, A123Google Scholar
Rieger, F. M. 2019, Galaxies, 7, 28Google Scholar
Romoli, C., Chakraborty, N., Dorner, D., Taylor, A. M., & Blank, M. 2018, Galaxies, 6, 135Google Scholar
Rybicki, G. B., & Lightman, A. P. 1986, RPAGoogle Scholar
Sahayanathan, S., Sinha, A., & Misra, R. 2018, RAA, 18, 035CrossRefGoogle Scholar
Schlafly, E. F., & Finkbeiner, D. P. 2011, ApJ, 737, 103CrossRefGoogle Scholar
Sinha, A., Khatoon, R., Misra, R., Sahayanathan, S., Mandal, S., Gogoi, R., & Bhatt, N. 2018, MNRAS, 480, L116CrossRefGoogle Scholar
Tagliaferri, G., et al. 2003, A&A, 400, 477CrossRefGoogle Scholar
Thekkoth, A., Sahayanathan, S., Shah, Z., Paliya, V. S., & Ravikumar, C. D. 2023, MNRAS, 526, 6364CrossRefGoogle Scholar
Tripathi, T., et al. 2024, MNRAS, 527, 5220Google Scholar
Urry, C. M., & Padovani, P. 1995, PASP, 107, 803CrossRefGoogle Scholar
Vaughan, S., Edelson, R., Warwick, R. S., & Uttley, P. 2003, MNRAS, 345, 1271CrossRefGoogle Scholar
Wagner, S. J., et al. 1996, AJ, 111, 2187Google Scholar
Wierzcholska, A., & Siejkowski, H. 2015, MNRAS, 452, L11Google Scholar
Wierzcholska, A., & Siejkowski, H. 2016, MNRAS, 458, 2350CrossRefGoogle Scholar
Zhang, Y. H. 2010, ApJ, 713, 180Google Scholar
Supplementary material: File

Baheeja et al. supplementary material

Baheeja et al. supplementary material
Download Baheeja et al. supplementary material(File)
File 97.2 KB