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Register a new userAn innovative blazar classification based on radio jet kinematics
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Blazars are usually classified following their synchrotron peak frequency ($ u F( u)$ scale) as high, intermediate, low frequency peaked BL Lacs (HBLs, IBLs, LBLs), and flat spectrum radio quasars (FSRQs), or, according to their radio morphology at large scale, FR~I or FR~II. However, the diversity of blazars is such that these classes seem insufficient to chart the specific properties of each source. We propose to classify a wide sample of blazars following the kinematic features of their radio jets seen in very long baseline interferometry (VLBI). For this purpose we use public data from the MOJAVE collaboration in which we select a sample of blazars with known redshift and sufficient monitoring to constrain apparent velocities. We selected 161 blazars from a sample of 200 sources. We identify three distinct classes of VLBI jets depending on radio knot kinematics: class I with quasi-stationary knots, class II with knots in relativistic motion from the radio core, and class I/II, intermediate, showing quasi-stationary knots at the jet base and relativistic motions downstream. A notable result is the good overlap of this kinematic classification with the usual spectral classification; class I corresponds to HBLs, class II to FSRQs, and class I/II to IBLs/LBLs. We deepen this study by characterizing the physical parameters of jets from VLBI radio data. Hence we focus on the singular case of the class I/II by the study of the blazar BL Lac itself. Finally we show how the interpretation that radio knots are recollimation shocks is fully appropriate to describe the characteristics of these three classes.
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Blazars are among the most studied sources in high-energy astrophysics as they form the largest fraction of extragalactic gamma-ray sources and are considered prime candidates for being the counterparts of high-energy astrophysical neutrinos. Their reliable identification amid the many faint radio sources is a crucial step for multi-messenger counterpart associations. As the astronomical community prepares for the coming of a number of new facilities able to survey the non-thermal sky at unprecedented depths, from radio to gamma-rays, machine learning techniques for fast and reliable source identification are ever more relevant. The purpose of this work was to develop a deep learning architecture to identify blazar within a population of AGN based solely on non-contemporaneous spectral energy distribution information, collected from publicly available multi-frequency catalogues. This study uses an unprecedented amount of data, with SEDs for $approx 14,000$ sources collected with the Open Universe VOU-Blazars tool. It uses a convolutional long-short term memory neural network purposefully built for the problem of SED classification, which we describe in detail and validate. The network was able to distinguish blazars from other types of AGNs to a satisfying degree (achieving a ROC area under curve of $0.98$), even when trained on a reduced subset of the whole sample. This initial study does not attempt to classify blazars among their different sub-classes, or quantify the likelihood of any multi-frequency or multi-messenger association, but is presented as a step towards these more practically-oriented applications.
Blazars are a subclass of radio-loud active galactic nuclei (AGNs), where the jet is aligned close to the line of sight. Blazars emission is dominated by non-thermal processes, where Doppler boosted radiation originates from a relativistic population of charged particles within the jet. From radio to TeV energies, blazars are highly variable on timescales from minutes to several months. There are several mechanisms proposed to explain variability, including changes in the viewing angle of the jet, propagating along the rotation axis of the accretion disc. The misalignment of a supermassive black hole (SMBH) spin and the angular momentum of the accretion disc yields to Lense-Thirring precession of such tilted disc, which leads to the variation of Doppler beaming. Such scenario is supported by radio observations of jet precession observed in some AGNs. The radio-emitting regions, however, are located far from the central engine, and thus the observed time scales in this band can be affected by e.g. a variation of the bulk Lorentz factor along the jet. In this contribution, we derive expected time scales of the jet wobbling using SMBH masses and compare them with the time intervals between flares in long-term (over 15 years) X-ray light curves of bright blazars observed by Swift-XRT. We found that for Mrk 421, Mrk 501 and 3C 273, the derived time scales are consistent with the observational constraints, while for 1ES 1959+650 we are mostly limited by uncertainty in the Doppler beaming factor.
The time evolution of the electromagnetic emission from blazars, in particular high frequency peaked sources (HBLs), displays irregular activity not yet understood. In this work we report a methodology capable of characterizing the time behavior of these variable objects. The Maximum Likelihood Blocks (MLBs) is a model-independent estimator which sub-divides the light curve into time blocks, whose length and amplitude are compatible with states of constant emission rate of the observed source. The MLBs yields the statistical significance in the rate variations and strongly suppresses the noise fluctuations in the light curves. We apply the MLBs for the first time on the long term X-ray light curves (RXTE/ASM) of Mkn~421,Mkn~501, 1ES 1959+650 and 1ES 2155-304, which consist of more than 10 years of observational data (1996-2007). Using the MLBs interpretation of RXTE/ASM data, the integrated time flux distribution is determined for each single source considered. We identify in these distributions the characteristic level as well as the flaring states of the blazars. All the distributions show a significant component at negative flux values, most probably caused by an uncertainty in the background subtraction and by intrinsic fluctuations of RXTE/ASM. This effect interests in particular short time observations. In order to quantify the probability that the intrinsic fluctuations give rise to a false identification of a flare, we study a population of very faint sources and their integrated time flux distribution. We determine duty cycle or fraction of time a source spent in the flaring state of the source Mkn~421, Mkn~501, 1ES 1959+650 and 1ES 2155-304. Moreover, we study the random coincidences between flares and generic sporadic events such as high energy neutrinos or flares in other wavelengths.
We have analyzed the parsec-scale jet kinematics of 447 bright radio-loud AGN, based on 15 GHz VLBA data obtained between 1994 August 31 and 2019 August 4. We present new total intensity and linear polarization maps obtained between 2017 January 1 to 2019 August 4 for 143 of these AGN. We tracked 1923 bright features for five or more epochs in 419 jets. A majority (60%) of the well-sampled jet features show either accelerated or non-radial motion. In 47 jets there is at least one non-accelerating feature with an unusually slow apparent speed. Most of the jets show variations of 10 to 50 deg in their inner jet position angle (PA) over time, although the overall distribution has a continuous tail out to 200 deg. AGN with SEDs peaked at lower frequencies tend to have more variable PAs, with BL Lacs being less variable than quasars. The Fermi LAT gamma-ray associated AGN also tend to have more variable PAs than the non-LAT AGN in our sample. We attribute these trends to smaller viewing angles for the lower spectral peaked and LAT-associated jets. We identified 13 AGN where multiple features emerge over decade-long periods at systematically increasing or decreasing PAs. Since the ejected features do not fill the entire jet cross-section, this behavior is indicative of a precessing flow instability near the jet base. Although some jets show indications of oscillatory PA evolution, we claim no bona fide cases of periodicity since the fitted periods are comparable to the total VLBA time coverage.
Blazars are among the most powerful extragalactic objects, as a sub-class of active galactic nuclei. They launch relativistic jets and their emitted radiation shows strong variability across the entire electro-magnetic spectrum. The mechanisms producing the variability are still controversial and different models have been proposed to explain the observed variations in multi-frequency blazar light curves.We investigate the capabilities of the classical shock-in-jet model to explain and reconstruct the observed evolution of flares in the turnover frequency turnover flux density plane and their frequency-dependent light curve parameters. With a detailed parameter space study we provide the framework for future, detailed comparisons of observed flare signatures with the shock-in-jet scenario. Based on the shock model we compute synthetic single-dish light curves at different radio frequencies (2.6 to 345 GHz) and for different physical conditions in a conical jet (e.g. magnetic field geometry and Doppler factor). From those we extract the slopes of the different energy loss stages within the $ u_mathrm{m}$-$S_mathrm{m}$ plane and deduce the frequency-dependence of different light curve parameters such as flare amplitude, time scale and cross-band delays. The evolution of the Doppler factor along the jet has the largest influence on the evolution of the flare and on the frequency-dependent light curve parameters. The synchrotron stage can be hidden in the Compton or in the adiabatic stage, depending mainly on the evolution of the Doppler factor, which makes it difficult to detect its signature in observations. In addition, we show that the time lags between different frequencies can be used as an efficient tool to better constrain the physical properties of these objects.
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