C IV BAL disappearance in a large SDSS QSO sample

Broad absorption lines (BALs) in the spectra of quasi-stellar objects (QSOs) originate from outflowing winds along our line of sight; winds are thought to originate from the inner regions of the QSO accretion disk, close to the central supermassive black hole (SMBH). Winds likely play a role in galaxy evolution and aid the accretion mechanism onto the SMBH. BAL equivalent widths can change on typical timescales from months to years; such variability is generally attributed to changes in the covering factor and/or in the ionization level of the gas. We investigate BAL variability, focusing on BAL disappearance. We analyze multi-epoch spectra of more than 1500 QSOs -the largest sample ever used for such a study- observed by different programs from the Sloan Digital Sky Survey-I/II/III (SDSS), and search for disappearing C IV BALs. The spectra rest-frame time baseline ranges from 0.28 to 4.9 yr; the source redshifts range from 1.68 to 4.27. We detect 73 disappearing BALs in the spectra of 67 sources. This corresponds to 3.9% of disappearing BALs, and 5.1% of our BAL QSOs exhibit at least one disappearing BAL. We estimate the average lifetime of a BAL along our line of sight (~ 80-100 yr), which appears consistent with the accretion disk orbital time at distances where winds are thought to originate. We inspect properties of the disappearing BALs and compare them to the properties of our main sample. We also investigate the existence of a correlation in the variability of multiple troughs in the same spectrum, and find it persistent at large velocity offsets between BAL pairs, suggesting that a mechanism extending on a global scale is necessary to explain the phenomenon. We select a more reliable sample of disappearing BALs following Filiz Ak et al. (2012), where a subset of our sample was analyzed, and compare the findings from the two works, obtaining generally consistent results.Comment: 22 pages, 9 figures. Accepted for publication in A&

Poster: Continual Network Learning

We make a case for in-network Continual Learning as a solution for seamless adaptation to evolving network conditions without forgetting past experiences. We propose implementing Active Learning-based selective data filtering in the data plane, allowing for data-efficient continual updates. We explore relevant challenges and propose future research directions

Optically variable active galactic nuclei in the 3 yr VST survey of the COSMOS field

The analysis of the variability of active galactic nuclei (AGNs) at different wavelengths and the study of possible correlations among different spectral windows are nowadays a major field of inquiry. Optical variability has been largely used to identify AGNs in multivisit surveys. The strength of a selection based on optical variability lies in the chance to analyze data from surveys of large sky areas by ground-based telescopes. However the effectiveness of optical variability selection, with respect to other multiwavelength techniques, has been poorly studied down to the depth expected from next generation surveys. Here we present the results of our r-band analysis of a sample of 299 optically variable AGN candidates in the VST survey of the COSMOS field, counting 54 visits spread over three observing seasons spanning > 3 yr. This dataset is > 3 times larger in size than the one presented in our previous analysis (De Cicco et al. 2015), and the observing baseline is ~8 times longer. We push towards deeper magnitudes (r(AB) ~23.5 mag) compared to past studies; we make wide use of ancillary multiwavelength catalogs in order to confirm the nature of our AGN candidates, and constrain the accuracy of the method based on spectroscopic and photometric diagnostics. We also perform tests aimed at assessing the relevance of dense sampling in view of future wide-field surveys. We demonstrate that the method allows the selection of high-purity (> 86%) samples. We take advantage of the longer observing baseline to achieve great improvement in the completeness of our sample with respect to X-ray and spectroscopically confirmed samples of AGNs (59%, vs. ~15% in our previous work), as well as in the completeness of unobscured and obscured AGNs. The effectiveness of the method confirms the importance to develop future, more refined techniques for the automated analysis of larger datasets.Comment: 21 pages, 10 figures; accepted for publication in A&

The VOICE Survey : VST Optical Imaging of the CDFS and ES1 Fields

Indexación: Scopus.We present the VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey, a VST INAF Guaranteed Time program designed to provide optical coverage of two 4 deg2 cosmic windows in the Southern hemisphere. VOICE provides the first, multi-band deep optical imaging of these sky regions, thus complementing and enhancing the rich legacy of longer-wavelength surveys with VISTA, Spitzer, Herschel and ATCA available in these areas and paving the way for upcoming observations with facilities such as the LSST, MeerKAT and the SKA. VOICE exploits VST's OmegaCAM optical imaging capabilities and completes the reduction of WFI data available within the ES1 fields as part of the ESO-Spitzer Imaging Extragalactic Survey (ESIS) program providing ugri and uBVR coverage of 4 and 4 deg2 areas within the CDFS and ES1 field respectively. We present the survey's science rationale and observing strategy, the data reduction and multi-wavelength data fusion pipeline. Survey data products and their future updates will be released at http://www.mattiavaccari.net/voice/ and on CDS/VizieR.https://pos.sissa.it/275/026/pd

SUDARE-VOICE variability-selection of Active Galaxies in the Chandra Deep Field South and the SERVS/SWIRE region

One of the most peculiar characteristics of Active Galactic Nuclei (AGN) is their variability over all wavelengths. This property has been used in the past to select AGN samples and is foreseen to be one of the detection techniques applied in future multi-epoch surveys, complementing photometric and spectroscopic methods. In this paper, we aim to construct and characterise an AGN sample using a multi-epoch dataset in the r band from the SUDARE-VOICE survey. Our work makes use of the VST monitoring program of an area surrounding the Chandra Deep Field South to select variable sources. We use data spanning a six month period over an area of 2 square degrees, to identify AGN based on their photometric variability. The selected sample includes 175 AGN candidates with magnitude r < 23 mag. We distinguish different classes of variable sources through their lightcurves, as well as X-ray, spectroscopic, SED, optical and IR information overlapping with our survey. We find that 12% of the sample (21/175) is represented by SN. Of the remaining sources, 4% (6/154) are stars, while 66% (102/154) are likely AGNs based on the available diagnostics. We estimate an upper limit to the contamination of the variability selected AGN sample of about 34%, but we point out that restricting the analysis to the sources with available multi-wavelength ancillary information, the purity of our sample is close to 80% (102 AGN out of 128 non-SN sources with multi-wavelength diagnostics). Our work thus confirms the efficiency of the variability selection method in agreement with our previous work on the COSMOS field; in addition we show that the variability approach is roughly consistent with the infrared selection.Comment: Published in A & A, 15 pages, 6 figure

Explainable Artificial Intelligence in communication networks: A use case for failure identification in microwave networks

Artificial Intelligence (AI) has demonstrated superhuman capabilities in solving a significant number of tasks, leading to widespread industrial adoption. For in-field network-management application, AI-based solutions, however, have often risen skepticism among practitioners as their internal reasoning is not exposed and their decisions cannot be easily explained, preventing humans from trusting and even understanding them. To address this shortcoming, a new area in AI, called Explainable AI (XAI), is attracting the attention of both academic and industrial researchers. XAI is concerned with explaining and interpreting the internal reasoning and the outcome of AI-based models to achieve more trustable and practical deployment. In this work, we investigate the application of XAI for network management, focusing on the problem of automated failure-cause identification in microwave networks. We first introduce the concept of XAI, highlighting its advantages in the context of network management, and we discuss in detail the concept behind Shapley Additive Explanations (SHAP), the XAI framework considered in our analysis. Then, we propose a framework for a XAI-assisted ML-based automated failure-cause identification in microwave networks, spanning model's development and deployment phases. For the development phase, we show how to exploit SHAP for feature selection and how to leverage SHAP to inspect misclassified instances during model's development process, and how to describe model's global behavior based on SHAP's global explanations. For the deployment phase, we propose a framework based on predictions uncertainty to detect possibly wrong predictions that will be inspected through XAI

Supernova rates from the SUDARE VST-Omegacam search II. Rates in a galaxy sample

This is the second paper of a series in which we present measurements of the Supernova (SN) rates from the SUDARE survey. In this paper, we study the trend of the SN rates with the intrinsic colours, the star formation activity and the mass of the parent galaxies. We have considered a sample of about 130000 galaxies and a SN sample of about 50 events. We found that the SN Ia rate per unit mass is higher by a factor of six in the star-forming galaxies with respect to the passive galaxies. The SN Ia rate per unit mass is also higher in the less massive galaxies that are also younger. These results suggest a distribution of the delay times (DTD) less populated at long delay times than at short delays. The CC SN rate per unit mass is proportional to both the sSFR and the galaxy mass. The trends of the Type Ia and CC SN rates as a function of the sSFR and the galaxy mass that we observed from SUDARE data are in agreement with literature results at different redshifts. The expected number of SNe Ia is in agreement with the observed one for all four DTD models considered both in passive and star-forming galaxies so we can not discriminate between different progenitor scenarios. The expected number of CC SNe is higher than the observed one, suggesting a higher limit for the minimum progenitor mass. We also compare the expected and observed trends of the SN Ia rate with the intrinsic U - J colour of the parent galaxy, assumed as a tracer of the age distribution. While the slope of the relation between the SN Ia rate and the U - J color in star-forming galaxies can be reproduced well by all four DTD models considered, only the steepest of them is able to account for the rates and colour in star-forming and passive galaxies with the same value of the SN Ia production efficiency.Comment: A& A accepte

C IV Broad Absorption Line Variability in QSO Spectra from SDSS Surveys

Broad absorption lines (BALs) in the spectra of quasi-stellar objects (QSOs) are thought to arise from outflowing winds along our line of sight; winds, in turn, are thought to originate from the accretion disk, in the very surroundings of the central supermassive black hole (SMBH), and they likely affect the accretion process onto the SMBH, as well as galaxy evolution.\\ BALs can exhibit variability on timescales typically ranging from months to years. We analyze such variability and, in particular, BAL disappearance, with the aim of investigating QSO physics and structure.\\ We search for disappearing C {\scriptsize{IV}} BALs in the spectra of 1319 QSOs from different programs from the Sloan Digital Sky Survey (SDSS); the analyzed time span covers $0.28-4.9$ yr (rest frame), and the source redshifts are in the range $1.68-4.27$. This is to date the largest sample ever used for such a study.\\ We find 67 sources ($5.1_{-0.6}^{+0.7}$\% of the sample) with 73 disappearing BALs in total ($3.9_{-0.5}^{+0.5}$\% of the total number of C {\scriptsize{IV}} BALs detected; \textbf{some sources have more than one BAL that disappears}). We compare the sample of disappearing BALs to the whole sample of BALs, and investigate the correlation in the variability of multiple troughs in the same spectrum. We also derive estimates of the average lifetime of a BAL trough and of the BAL phase along our line of sight

Role of serum-free light chain assay for defining response and progression in immunoglobulin secretory multiple myeloma

The International Myeloma Working Group (IMWG) guidelines recommend using electrophoresis and immunofixation to define response and progressive disease (PD) in immunoglobulin (Ig) secretory multiple myeloma (Ig-MM), whereas the role of serum-free light chain (sFLC) is controversial. We retrospectively analyzed the value of adding sFLC assays in the definition of response and PD according to IMWG criteria in 339 Ig-MM patients treated with a first-line novel agent-based therapy (median follow-up 54 months). sFLC PD was defined according to conventional criteria plus increased sFLC levels, or sFLC escape (sFLCe); progression/sFLCe-free survival (ePFS) was the time from the start of treatment to the date of first PD or sFLCe, or death; overall survival after PD/sFLCe (OS after Pe) was the time from first PD or sFLCe to the date of death. 148 (44%) patients achieved a complete response and 198 (60%) a normal sFLC ratio (sFLCR). sFLCR normalization was an independent prognostic factor for extended PFS (HR&nbsp;=&nbsp;0.46, p&nbsp;=&nbsp;0.001) and OS (HR&nbsp;=&nbsp;0.47, p&nbsp;=&nbsp;0.006) by multivariable analysis. 175 (52%) patients experienced PD according to the IMWG criteria, whereas 180 (53%) experienced PD or sFLCe. Overall, a sFLCe was observed in 31 (9%) patients. Median PFS and ePFS were both equal to 36 (95% CI&nbsp;=&nbsp;32–42, and 32–40, respectively) months. sFLC PD adversely affected the OS after Pe compared to PD with increasing monoclonal Ig only (HR&nbsp;=&nbsp;0.52, p&nbsp;=&nbsp;0.012). Our results support the inclusion of the sFLC assay for defining response and PD in Ig-MM