Radio and γ\gamma-ray variability in the BL Lac PKS 0219 -164: Detection of quasi-periodic oscillations in the radio light curve

In this work, we explore the long-term variability properties of the blazar PKS 0219-164 in the radio and the $\gamma$-ray regime, utilizing the OVRO 15 GHz and the \fermi/LAT observations from the period 2008--2017. We found that $\gamma$-ray emission is more variable than the radio emission implying that $\gamma$ ray emission possibly originated in more compact regions while the radio emission represented continuum emission from the large scale jets. Also, in $\gamma$-ray the source exhibited spectral variability characterized by the \emph{ softer-when-brighter} trend, a less frequently observed feature in the high energy emission by BL Lacs. In radio, using Lomb-Scargle periodogram and weighted wavelet z-transform, we detected a strong signal of quasi-periodic oscillation (QPO) with a periodicity of 270 $\pm$ 26 days with possible harmonics of 550 $\pm$ 42 and 1150 $\pm$ 157 days periods. At a time when the issue of the detection of QPOs in blazars is still under debate, the observed QPO with high statistical significance ( $\sim$ 97\% -- 99\% global significance over underlying red-noise processes) and persistent over nearly 10 oscillations could make one of the strongest cases for the detection of QPOs in blazar light curves. We discuss various blazar models that might lead to the $\gamma$-ray and radio variability, QPO, and the achromatic behavior seen in the high energy emission from the source.Comment: ApJ, in press. 9 pages and 5 figure

Microvariability in BL Lacertae : "zooming'' into the innermost blazar regions

In this work, we present the results of our multi-band microvariability study of the famous blazar BL Lac. We performed microvariablity observations of the source in the optical VRI bands for four nights in 2016. We studied the intranight flux and spectral variability of the source in detail with an objective to characterize microvariability in the blazars, a frequently observed phenomenon in blazars. The results show that the source often displays a fast flux variability with an amplitude as large as ~0.2 magnitude within a few hours, and that the color variability in the similar time scales can be characterized as “bluer-when-brighter” trend. We also observed markedly curved optical spectrum during one of the nights. Furthermore, the correlation between multi-band emission shows that in general the emission in all the bands are highly correlated; and in one of the nights V band emission was found to lead the I band emission by ~13 min. The search for characteristic timescale using z-transformed auto-correlation function and the structure function analyses reveals characteristic timescale of ~50 min in one of the R band observations. We try to explain the observed results in the context of the passage of shock waves through the relativistic outflows in blazars

Blazar Mrk 501 shows rhythmic oscillations in its γ\gamma-ray emission

Quasi-periodic oscillations (QPO) originating from innermost regions of blazars can provide unique perspective of some of the burning issues in blazar studies including disk-jet connection, launch of relativistic jets from the central engine, and other extreme conditions near the fast rotating supermassive black holes. However, a number of hurdles associated with searching QPOs in blazars e.g., red-noise dominance, modest significance of the detection and periodic modulation lasting for only a couple of cycles, make it difficult to estimate the true significance of the detection. In this work, we report a $\sim$ 330-day QPO in the Fermi/LAT observations of the blazar Mrk 501 spanning nearly a decade. To establish consistency of the result, we adopted multiple approaches to the time series analysis and employed four widely known methods. Among these, Lomb-Scargle periodogram and weighted wavelet z-transform represent frequency domain based methods whereas epoch folding and z-transformed discrete auto-correlation function are time-domain based analysis. Power spectrum response method was followed to properly account for the red-noise, largely inherent in blazar light curves. Both local and global significance of the signal were found to be above 99\% over possible spurious detection. In the context where not many $\gamma$-ray QPOs have been reported to last more than 5 cycles, this might be one of the few instances where we witness a sub-year timescale $\gamma$-ray QPO persisting nearly 7 cycles. A number of possible scenarios linked with binary supermassive black hole, relativistic jets, and accretion disks can be invoked to explain the transient QPO.Comment: 9 pages and 6 figures, MNRAS accepte

Study of optical and gamma-ray long-term variability in blazars

Blazars, a subset of powerful active galactic nuclei, feature relativistic jets that shine in a broadband electromagnetic radiation, e. g. from radio to TeV emission. Here I present the results of the studies that explore gamma-ray and optical variability properties of a sample of gamma-ray bright sources Several methods of time-series analyses are performed on the decade-long optical and Fermi/LAT observations. The main results are as follows: The sources are found highly variable in both the bands, and the gamma-ray power spectral density is found to be consistent with flicker noise suggesting long-memory processes at work. While comparing two emission, not only the overall optical and the $\gamma$-ray emission are highly correlated but also both the observation distributions exhibit heavy tailed log-normal distribution and linear RMS-flux relation. In addition, in some of the sources indications of quasi-periodic oscillation were revealed with similar characteristic timescales in both the bands. We discuss the results in light of current blazar models with relativistic shocks propagating down the jet viewed close to the line of sight.Comment: 8 pages, submitted to Acta Physica Polonica

Hard X-ray properties of NuSTAR blazars

Context. Investigation of the hard X-ray emission properties of blazars is key to the understanding of the central engine of the sources and associated jet process. In particular, simultaneous spectral and timing analyses of the intra-day hard X-ray observations provide us a means to peer into the compact innermost blazar regions, not accessible to our current instruments. Aims. The primary objective of the work is to associate the observed hard X-ray variability properties in the blazars to their flux and spectral states, thereby, based on the correlation among them, extract the details about the emission regions and the processes occurring near the central engine. Methods. We carried out timing, spectral and cross-correlation analysis of 31 NuSTAR observations of 13 blazars. We investigated the spectral shapes of the sources using single power-law, broken power-law and log-parabola models. We also studies the co-relation between the soft and the hard emission using z-transformed discrete correlation function. Results. We found that for most of the sources the hard X-ray emission can be well represented by log-parabola model; and that the spectral slopes for different blazar sub-classes are consistent with so called blazar sequence. We noted a close connection between the flux and spectral slope within the source sub-class in the sense that high flux and/or flux states tend to be harder in spectra. In BL Lacertae objects, assuming particle acceleration by diffusive shocks and synchrotron cooling as the dominant processes governing the observed flux variability, we constrain the magnetic field of the emission region to be a few gauss; whereas in flat-spectrum radio quasars, using external Compton models, we estimate the energy of the lower end of the injected electrons to be a few Lorentz factors.Comment: 12 figures, 21 pages, A&A accepte

Detection of periodic radio signal from the Blazar J1043+2408

The search for periodic signals from blazars has become a widely discussed topic in recent years. In the scenario that such periodic changes originate from the innermost regions of blazars, the signals bear imprints of the processes occurring near the central engine, which are mostly inaccessible to our direct view. Such signals provide insights into various aspect of blazar studies, including disk-jet connection, magnetic-field configuration and, more importantly, strong gravity near the supermassive black holes and release of gravitational waves from binary supermassive-black-hole systems. In this work, we report the detection of a periodic signal in the radio light curve of blazar J1043+2408 spanning ∼10.5 years. We performed multiple methods of time-series analysis, namely, epoch folding, Lomb⁻Scargle periodogram, and discrete autocorrelation function. All three methods consistently revealed a repeating signal with a periodicity of ∼560 days. To robustly account for the red-noise processes usually dominant in the blazar variability and other possible artefacts, a large number of Monte Carlo simulations were performed. This allowed us to estimate high significance (99.9% local and 99.4% global) against possible spurious detection. As possible explanations, we discuss a number of scenarios, including binary supermassive-black-hole systems, Lense⁻Thirring precession, and jet precession

Estimation of redshift and associated uncertainty of Fermi/LAT extra-galactic sources with Deep Learning

With the advancement of technology, machine learning-based analytical methods have pervaded nearly every discipline in modern studies. Particularly, a number of methods have been employed to estimate the redshift of gamma-ray loud active galactic nuclei (AGN), which are a class of supermassive black hole systems known for their intense multi-wavelength emissions and violent variability. Determining the redshifts of AGNs is essential for understanding their distances, which, in turn, sheds light on our current understanding of the structure of the nearby universe. However, the task involves a number of challenges such as the need for meticulous follow-up observations across multiple wavelengths and astronomical facilities. In this study, we employ a simple yet effective deep learning model with a single hidden layer having $64$ neurons and a dropout of 0.25 in the hidden layer, on a sample of AGNs with known redshifts from the latest AGN catalog, 4LAC-DR3, obtained from Fermi-LAT. We utilized their spectral, spatial, and temporal properties to robustly predict the redshifts of AGNs as well quantify their associated uncertainties, by modifying the model using two different variational inference methods. We achieve a correlation coefficient of 0.784 on the test set from the frequentist model and 0.777 and 0.778 from both the variants of variational inference, and, when used to make predictions on the samples with unknown redshifts, we achieve mean predictions of 0.421, 0.415 and 0.393, with standard deviations of 0.258, 0.246 and 0.207 from the models, respectively.Comment: In-Review: MNRAS Comments are appreciate