Multi-frequency study on markarian 421 during the first two years of operation of the MAGIC stereo telescopes

Markarian 421 (Mrk~421) is one of the classical blazars at X-ray and very high energies (VHE; $>$100 GeV). Its spectral energy distribution (SED) can be accurately characterized by current instruments because of its close proximity, which makes Mrk~421 one of the best sources to study the nature of blazars. The goal of this PhD thesis is to better understand the mechanisms responsible for the broadband emission and the temporal evolution of Mrk~421. The results might be applied to other blazars which cannot be studied with this level of detail because their emissions are weaker, or they are located further away. This thesis reports results from $\sim$70 hours of observations with MAGIC in 2010 and 2011 (the first two years of the operation of the MAGIC stereo telescopes), as well as the results from the multi-wavelength (MW) observation campaigns in 2010 and 2011, where more than 20 instruments participated, covering energies from radio to VHE. The MW data from the 2010 and 2011 campaigns show that, for both years, the fractional variability $F_{\rm var}$ increases with the energy for both the low-energy and the high-energy bumps in the SED of Mrk~421. Furthermore, $F_{\rm var}(\text{optical})$ was similar to F_{\rm var}(\text{HE-\gamma$-ray;$>100 MeV}), and $F_{\rm var}(\text{X-ray})$ was similar to F_{\rm var}(\text{VHE-\gamma-ray}). This observed characteristic is expected from the strong correlation between the synchrotron photons and the up-scattered photons by inverse-Compton effect within the synchrotron self-Compton (SSC) emission model, thus allowing for the first time of the consistency test on this widely used theoretical model. During the MW campaign in 2010, we measured the decay of a flaring activity during 13 days in March. We could perform MW observations every day, which enables an unprecedented characterization of the time-evolution of the radio to $\gamma$-ray emission of Mrk~421. The broadband SEDs during this flaring episode, resolved on timescales of one day, were characterized with two leptonic scenarios: a one-zone SSC model, and a two-zone SSC model where one zone is responsible for the quiescent emission while the other (smaller) zone, which is spatially separated from the former one, contributes to the daily-variable emission occurring mostly at X-rays and VHE $\gamma$ rays. Both the one-zone SSC and the two-zone SSC models can describe the daily SEDs. However, the two-zone SSC model provides a better agreement to the observed SED at the narrow peaks of the low- and high-energy bumps during the highest activity. The proposed two-zone scenario would naturally lead to the correlated variability in the X-ray and VHE bands without variability in the optical/UV band, as well as to shorter timescales for the variability in the X-ray and VHE bands with respect to the variability in the other bands. This concept of a second small emission region containing a narrow electron spectrum in order to explain the short timescale flaring activity in the X-ray and VHE bands could be generalized to other blazars. The results from the 2010 March flaring activity of Mrk~421 are reported in Sections~\ref{LightCurves} -- \ref{Discussion}, and they are the main scientific achievement of this PhD thesis. Preliminary results were reported (as an oral contribution) in the 33rd International Cosmic Ray Conference (Rio de Janeiro, July 2013), one of the most prestigious conferences in the field of the VHE astronomy and astro-particle physics in general. The final results (reviewed and approved within the \Fermic, MAGIC, and VERITAS Collaborations) have been submitted for publication in the Astronomy and Astrophysics journal in 2014 June. During the MW campaign in 2011, Mrk~421 had an atypically high activity in the optical band, together with a very low state in the X-ray/VHE band. Typically, blazar emission models for Mrk~421 focus on the explanation of the variability in the X-ray and $\gamma$-ray bands. This data set is suitable for examining emission models and estimate if they can describe the evolution of the whole broadband SEDs including the variabilities in optical, X-ray, and $\gamma$-ray bands. We found that the one-zone SSC model can describe the relatively slow variation of the 2011 broadband SEDs. The modeling of these SEDs shows that the main factor dominating the spectral evolution could be the electron energy distribution (EED), instead of the environmental parameters like the blob size and the Doppler factor. To explain the featured high optical state together with the low X-ray/VHE state, several changes were needed in comparison to the typical state from 2009: a harder power-law index in the first segment in the EED, a lower first break in the EED, and a softer power-law index in the second segment in the EED. Besides, these optical high states had synchrotron peak frequencies 10 times lower than the typical state, while their synchrotron peak energy-fluxes were similar to those of the typical state. On the contrary, the 2010~March flaring activity showed that a high peak energy-flux was accompanied by a high peak frequency in comparison to the typical state, which has also been observed on several other blazars. This contrast showed that the broadband variability in the emission of Mrk~421 during 2011 had a different \emph{flavor} with respect to the typical blazar broadband flaring activity. This PhD thesis shows that most variations in the SED of Mrk~421 can be produced through changes in the EED, which could shed light into how particles get accelerated in the vicinity of super-massive black holes, or within the relativistic jets of the active galactic nuclei. However, the results also show a large complexity in the evolution of the broadband (radio to VHE $\gamma$-rays) SED. Thus longer and deeper observations are needed to understand what characteristics get repeated over time and hence typical, what characteristics are atypical, and ultimately, whether the lessons learned with Mrk~421 can be extended to high-synchrotron-peaked blazars in general

Predicting the hosts of prokaryotic viruses using GCN-based semi-supervised learning

Background: Prokaryotic viruses, which infect bacteria and archaea, are the most abundant and diverse biological entities in the biosphere. To understand their regulatory roles in various ecosystems and to harness the potential of bacteriophages for use in therapy, more knowledge of viral-host relationships is required. High-throughput sequencing and its application to the microbiome have offered new opportunities for computational approaches for predicting which hosts particular viruses can infect. However, there are two main challenges for computational host prediction. First, the empirically known virus-host relationships are very limited. Second, although sequence similarity between viruses and their prokaryote hosts have been used as a major feature for host prediction, the alignment is either missing or ambiguous in many cases. Thus, there is still a need to improve the accuracy of host prediction. Results: In this work, we present a semi-supervised learning model, named HostG, to conduct host prediction for novel viruses. We construct a knowledge graph by utilizing both virus-virus protein similarity and virus-host DNA sequence similarity. Then graph convolutional network (GCN) is adopted to exploit viruses with or without known hosts in training to enhance the learning ability. During the GCN training, we minimize the expected calibrated error (ECE) to ensure the confidence of the predictions. We tested HostG on both simulated and real sequencing data and compared its performance with other state-of-the-art methods specifcally designed for virus host classification (VHM-net, WIsH, PHP, HoPhage, RaFAH, vHULK, and VPF-Class). Conclusion: HostG outperforms other popular methods, demonstrating the efficacy of using a GCN-based semi-supervised learning approach. A particular advantage of HostG is its ability to predict hosts from new taxa.Comment: 16 pages, 14 figure

VIGAN: Missing View Imputation with Generative Adversarial Networks

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.Comment: 10 pages, 8 figures, conferenc