In 2012 Markarian 421 underwent the largest flare ever observed in this blazar at radio frequencies. In the present study, we start exploring this unique event and compare it to a less extreme event in 2013. We use 15 GHz radio data obtained with the
Owens Valley Radio Observatory 40-m telescope, 95 GHz millimeter data from the Combined Array for Research in Millimeter-Wave Astronomy, and GeV gamma-ray data from the Fermi Gamma-ray Space Telescope. The radio light curves during the flaring periods in 2012 and 2013 have very different appearances, both in shape and peak flux density. Assuming that the radio and gamma-ray flares are physically connected, we attempt to model the most prominent sub-flares of the 2012 and 2013 activity periods by using the simplest possible theoretical framework. We first fit a one-zone synchrotron self-Compton (SSC) model to the less extreme 2013 flare and estimate parameters describing the emission region. We then model the major gamma-ray and radio flares of 2012 using the same framework. The 2012 gamma-ray flare shows two distinct spikes of similar amplitude, so we examine scenarios associating the radio flare with each spike in turn. In the first scenario, we cannot explain the sharp radio flare with a simple SSC model, but we can accommodate this by adding plausible time variations to the Doppler beaming factor. In the second scenario, a varying Doppler factor is not needed, but the SSC model parameters require fine tuning. Both alternatives indicate that the sharp radio flare, if physically connected to the preceding gamma-ray flares, can be reproduced only for a very specific choice of parameters.
Several narrow-line Seyfert 1 galaxies (NLS1s) have now been detected in gamma rays, providing firm evidence that at least some of this class of active galactic nuclei (AGN) produce relativistic jets. The presence of jets in NLS1s is surprising, as t
hese sources are typified by comparatively small black hole masses and near- or super-Eddington accretion rates. This challenges the current understanding of the conditions necessary for jet production. Comparing the properties of the jets in NLS1s with those in more familiar jetted systems is thus essential to improve jet production models. We present early results from our campaign to monitor the kinematics and polarization of the parsec-scale jets in a sample of 15 NLS1s through multifrequency observations with the Very Long Baseline Array. These observations are complemented by fast-cadence 15 GHz monitoring with the Owens Valley Radio Observatory 40m telescope and optical spectroscopic monitoring with with the 2m class telescope at the Guillermo Haro Astrophysics Observatory in Cananea, Mexico.
Since mid-2007 we have carried out a dedicated long-term monitoring programme at 15 GHz using the Owens Valley Radio Observatory 40 meter telescope. One of the main goals of this programme is to study the relation between the radio and gamma-ray emis
sion in blazars and to use it as a tool to locate the site of high energy emission. Using this large sample of objects we are able to characterize the radio variability, and study the significance of correlations between the radio and gamma-ray bands. We find that the radio variability of many sources can be described using a simple power law power spectral density, and that when taking into account the red-noise characteristics of the light curves, cases with significant correlation are rare. We note that while significant correlations are found in few individual objects, radio variations are most often delayed with respect to the gamma-ray variations. This suggests that the gamma-ray emission originates upstream of the radio emission. Because strong flares in most known gamma-ray-loud blazars are infrequent, longer light curves are required to settle the issue of the strength of radio-gamma cross-correlations and establish confidently possible delays between the two. For this reason continuous multiwavelength monitoring over a longer time period is essential for statistical tests of jet emission models.
Blazars are powerful, variable emitters from radio to gamma-ray wavelengths. Even though the general picture of synchrotron emission at low energies and inverse Compton at the high energy end is well established, many important aspects of these remar
kable objects are still not well understood. For example, even the location of the gamma-ray emission region is still not clearly established, with some theories locating it close to the black hole/accretion disk while others place it at parsec scales in the radio jet. Since mid-2007 we have carried out a large scale monitoring program at 15 GHz using the OVRO 40 m telescope. We are currently observing about 1700 blazars twice per week. The sample includes all the Fermi-LAT detected blazars north of declination -20 degrees. Here, we study the existence of correlated variability between these two bands for 86 sources bright enough to be detected weekly by LAT. The existence of correlated variability can be interpreted as an indication of a related spatial locations for the radio and gamma-ray emission, making the evaluation of its statistical significance a key goal of our program. A study of the statistical significance of these cross-correlations is presented along with a discussion of the Monte Carlo simulations used to evaluate them. More information about the conditions on the radio emission zone can be obtained through polarization monitoring which tells us about the configuration of the magnetic fields in this region. To study radio polarization variability we are building KuPol, a radio polarization receiver for the 12 to 18 GHz band that will replace the current total power receiver at the OVRO 40 meter telescope.
Whether a correlation exists between the radio and gamma-ray flux densities of blazars is a long-standing question, and one that is difficult to answer confidently because of various observational biases which may either dilute or apparently enhance
any intrinsic correlation between radio and gamma-ray luminosities. We introduce a novel method of data randomization to evaluate quantitatively the effect of these biases and to assess the intrinsic significance of an apparent correlation between radio and gamma-ray flux densities of blazars. The novelty of the method lies in a combination of data randomization in luminosity space (to ensure that the randomized data are intrinsically, and not just apparently, uncorrelated) and significance assessment in flux space (to explicitly avoid Malmquist bias and automatically account for the limited dynamical range in both frequencies). The method is applicable even to small samples that are not selected with strict statistical criteria. For larger samples we describe a variation of the method in which the sample is split in redshift bins, and the randomization is applied in each bin individually; this variation is designed to yield the equivalent to luminosity-function sampling of the underlying population in the limit of very large, statistically complete samples. We show that for a smaller number of redshift bins, the method yields a worse significance, and in this way it is conservative in that it does not assign a stronger, artificially enhanced significance. We demonstrate how our test performs as a function of number of sources, strength of correlation, and number of redshift bins used, and we show that while our test is robust against common-distance biases and associated false positives for uncorrelated data, it retains the power of other methods in rejecting the null hypothesis of no correlation for correlated data.
We present results from the first two years of our fast-cadence 15 GHz gamma-ray blazar monitoring program, part of the F-GAMMA radio monitoring project. Our sample includes the 1158 blazars north of -20 degrees declination from the Candidate Gamma-R
ay Blazar Survey (CGRaBS), which encompasses a significant fraction of the extragalactic sources detected by the Fermi Gamma-ray Space Telescope. We introduce a novel likelihood analysis for computing a time series variability amplitude statistic that separates intrinsic variability from measurement noise and produces a quantitative error estimate. We use this method to characterize our radio light curves. We also present results indicating a statistically significant correlation between simultaneous average 15 GHz radio flux density and gamma-ray photon flux.
