Environment and properties of emitting electrons in blazar jets: Mrk 421 as a laboratory

arXiv:1111.0265v1 [astro-ph.HE] 1 Nov 2011 2011 Fermi Symposium, Roma., May. 9-12 1 Environment and properties of emitting electrons in blazar jets: Mrk 421 as a laboratory Nijil Mankuzhiyil INFN Trieste and Universit`a di Udine, via delle Scienze 208, I-33100 Udine, ITALY Stefano Ansoldi International Center for Relativistic Astrophysics (ICRA), Rome and Universit`a di Udine, via delle Scienze 208, I-33100 Udine, ITALY Massimo Persic INAF-Trieste, via G. B. Tiepolo 11, I-34143 Trieste, ITALY Fabrizio Tavecchio INAF-Brera, via E. Bianchi 46, I-23807 Merate, ITALY Here we report our recent study on the spectral energy distribution (SED) of the high frequency BL Lac object Mrk 421 in different luminosity states. We used a full-fledged χ2-minimization procedure instead of more commonly used ”eyeball” fit to model the observed flux of the source (from optical to very high energy), with a Synchrotron-Self-Compton (SSC) emission mechanism. Our study shows that the synchrotron power and peak frequency remain constant with varying source activity, and the magnetic field (B) decreases with the source activity while the break energy of electron spectrum (γbr) and the Doppler factor (δ) increase. Since a lower magnetic field and higher density of electrons result in increased electron-photon scattering efficiency, the Compton power increases, so does the total emission. 1. Introduction Active galactic nuclei (AGN) involve the most pow- erful, steady sources of luminosity in the Universe. It is believed that the center core of AGN consist of super massive black hole (SMBH) surrounded by an accre- tion disk. In some cases powerful collimated jets are found in AGN, perpendicular to the plane of accretion disk. The origin of jets are still unclear. AGNs whose jets are viewed at a small angle to its axis are called blazars. The overall (radio to γ-ray) spectral energy distri- bution (SED) of blazars shows two broad non-thermal continuum peaks. The low-energy peak is thought to arise from electron synchrotron emission. The lep- tonic model suggests that the second peak forms due to inverse Compton emission. This can be due to upscattering, by the same non-thermal population of electrons responsible for the synchrotron radiation, and synchrotron photons (Synchrotron Self Compton: SSC) Maraschi et al. [1992]. Blazars often show violent flux variability, that may or may not appear correlated in the different energy bands. Simultaneous observation are then crucial to understand the physics behind variability. 2. χ2-minimized SED fitting In this section we discuss the code that we have used to obtain an estimation of the characteristic pa- rameters of the SSC model. The SSC model assumes a spectrum for the accelerated electron density k, which is a broken power law with exponents n1 and n2. The minimum, maximum and break Lorentz factors for the DEF: SSC parameters initial values set-up calculate initial χ2 value, change parameters LOOP : calculate χ2 for modified parameters if χ2 has increased: we are moving away from a minimum ⇒change parameters, increase weight of steepest descent method and reset negligible decrease amount counter if χ2 has decreased: we are moving toward a minimum ⇒change parameters and increase weight of inverse Hessian method UNTIL: χ2 decreases by a negligible amount for the fourth time Table I The χ2 minimization algorithm. electrons are usually called γmin., γmax. and γbreak re- spectively. The emitting region is considered to be a blob of radius R moving with Doppler factor δ with respect to the observer in a magnetic field of inten- sity B. The model is thus characterized by nine free parameters. In the present work we have kept γmin. fixed and equal to unit, which is a satisfactory approximation already used in the literature. The determination of the remaining eight parameters has been performed by finding their best values and uncertainties from a χ2 minimization in which multi-frequency experi- eConf C110509 2 2011 Fermi Symposium, Roma., May. 9-12 mental points have been fitted to the SSC spectrum modelled as in Tavecchio et al. [1998]. Minimization has been performed using the Levenberg-Marquardt method Press et al. [1994], which is an efficient stan- dard for non-linear least-squares minimization that smoothly interpolates between two different minimiza- tion approaches, namely the inverse Hessian method and the steepest descent method. For completeness, we briefly present the pseudo-code for the algorithm in table I. A crucial point in our implementation is that from Tavecchio et al. [1998] we can only obtain a numeri- cal approximation to the SSC spectrum, in the form of a sampled SED. On the other hand, from table I, we understand that at each step the calculation of the χ2 requires the evaluation of the SED for all the ob- served frequencies. Although an observed point will likely not be one of the sampled points coming from Tavecchio et al. [1998], it will fall between two sam- pled points, so that interpol

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