arXiv subjects

Ioannis Liodakis

Publications and source records attributed to Ioannis Liodakis.

116 records · Page 7Linked to original sources

arXiv2022

Incremental Fermi Large Area Telescope Fourth Source Catalog

We present an incremental version (4FGL-DR3, for Data Release 3) of the fourth Fermi-LAT catalog of gamma-ray sources. Based on the first twelve years of science data in the energy range from 50 MeV to 1 TeV, it contains 6658 sources. The analysis improves on that used for the 4FGL catalog over eight years of data: more sources are fit with curved spectra, we introduce a more robust spectral parameterization for pulsars, and we extend the spectral points to 1 TeV. The spectral parameters, spectral energy distributions, and associations are updated for all sources. Light curves are rebuilt for all sources with 1 yr intervals (not 2 month intervals). Among the 5064 original 4FGL sources, 16 were deleted, 112 are formally below the detection threshold over 12 yr (but are kept in the list), while 74 are newly associated, 10 have an improved association, and seven associations were withdrawn. Pulsars are split explicitly between young and millisecond pulsars. Pulsars and binaries newly detected in LAT sources, as well as more than 100 newly classified blazars, are reported. We add three extended sources and 1607 new point sources, mostly just above the detection threshold, among which eight are considered identified, and 699 have a plausible counterpart at other wavelengths. We discuss degree-scale residuals to the global sky model and clusters of soft unassociated point sources close to the Galactic plane, which are possibly related to limitations of the interstellar emission model and missing extended sources.

astro-ph.HE↗

arXiv2022

Testing High-Energy Emission Models for Blazars with X-ray Polarimetry

Both leptonic and hadronic emission processes may contribute to blazar jet emission; which dominates in blazars's high energy emission component remains an open question. Some intermediate synchrotron peaked blazars transition from their low to high energy emission components in the X-ray band making them excellent laboratories to probe both components simultaneously, and good targets for the newly launched Imaging X-ray Polarimetry Explorer. We characterize the spectral energy distributions for three such blazars: CGRaBS~J0211+1051, TXS~0506+056, and S5~0716+714, predicting their X-ray polarization behavior by fitting a multizone polarized leptonic jet model. We find that a significant detection of electron synchrotron dominated polarization is possible with a 300~ks observation for S5~0716+714 and CGRaBS~J0211+1051 in their flaring states, while even 500~ks observations are unlikely to measure synchrotron self-Compton polarization. Importantly, non-leptonic emission processes like proton synchrotron are marginally detectable for our brightest ISP, S5~0716+714, during a flaring state. Improved {\it IXPE} data reduction methods or next generation telescopes like {\it eXTP} are needed to confidently measure SSC polarization.

astro-ph.HE↗

arXiv2022

Using Multivariate Imputation by Chained Equations to Predict Redshifts of Active Galactic Nuclei

Redshift measurement of active galactic nuclei (AGNs) remains a time-consuming and challenging task, as it requires follow up spectroscopic observations and detailed analysis. Hence, there exists an urgent requirement for alternative redshift estimation techniques. The use of machine learning (ML) for this purpose has been growing over the last few years, primarily due to the availability of large-scale galactic surveys. However, due to observational errors, a significant fraction of these data sets often have missing entries, rendering that fraction unusable for ML regression applications. In this study, we demonstrate the performance of an imputation technique called Multivariate Imputation by Chained Equations (MICE), which rectifies the issue of missing data entries by imputing them using the available information in the catalog. We use the Fermi-LAT Fourth Data Release Catalog (4LAC) and impute 24% of the catalog. Subsequently, we follow the methodology described in Dainotti et al. (2021) and create an ML model for estimating the redshift of 4LAC AGNs. We present results which highlight positive impact of MICE imputation technique on the machine learning models performance and obtained redshift estimation accuracy.

astro-ph.IM↗

arXiv2022

Predicting the redshift of gamma-ray loud AGNs using Supervised Machine Learning: Part 2

Measuring the redshift of active galactic nuclei (AGNs) requires the use of time-consuming and expensive spectroscopic analysis. However, obtaining redshift measurements of AGNs is crucial as it can enable AGN population studies, provide insight into the star formation rate, the luminosity function, and the density rate evolution. Hence, there is a requirement for alternative redshift measurement techniques. In this project, we aim to use the Fermi gamma-ray space telescope's 4LAC Data Release (DR2) catalog to train a machine learning model capable of predicting the redshift reliably. In addition, this project aims at improving and extending with the new 4LAC Catalog the predictive capabilities of the machine learning (ML) methodology published in Dainotti et al. (2021). Furthermore, we implement feature engineering to expand the parameter space and a bias correction technique to our final results. This study uses additional machine learning techniques inside the ensemble method, the SuperLearner, previously used in Dainotti et al.(2021). Additionally, we also test a novel ML model called Sorted L-One Penalized Estimation (SLOPE). Using these methods we provide a catalog of estimated redshift values for those AGNs that do not have a spectroscopic redshift measurement. These estimates can serve as a redshift reference for the community to verify as updated Fermi catalogs are released with more redshift measurements.

astro-ph.HE↗

arXiv2021

Predicting the redshift of gamma-ray loud AGNs using supervised machine learning

AGNs are very powerful galaxies characterized by extremely bright emissions coming out from their central massive black holes. Knowing the redshifts of AGNs provides us with an opportunity to determine their distance to investigate important astrophysical problems such as the evolution of the early stars, their formation along with the structure of early galaxies. The redshift determination is challenging because it requires detailed follow-up of multi-wavelength observations, often involving various astronomical facilities. Here, we employ machine learning algorithms to estimate redshifts from the observed gamma-ray properties and photometric data of gamma-ray loud AGN from the Fourth Fermi-LAT Catalog. The prediction is obtained with the Superlearner algorithm, using LASSO selected set of predictors. We obtain a tight correlation, with a Pearson Correlation Coefficient of 71.3% between the inferred and the observed redshifts, an average Δz_norm = 11.6 x 10^-4. We stress that notwithstanding the small sample of gamma-ray loud AGNs, we obtain a reliable predictive model using Superlearner, which is an ensemble of several machine learning models.

astro-ph.HE↗

arXiv2020

Using variability and VLBI to measure cosmological distances

In this paper, we propose a new approach to determining cosmological distances to active galactic nuclei (AGN) via light travel-time arguments, which can be extended from nearby sources to very high redshift sources. The key assumption is that the variability seen in AGN is constrained by the speed of light and therefore provides an estimate of the linear size of an emitting region. This can then be compared with the angular size measured with very long baseline interferometry (VLBI) in order to derive a distance. We demonstrate this approach on a specific well studied low redshift (z = 0.0178) source 3C84 (NGC 1275), which is the bright radio core of the Perseus Cluster. We derive an angular diameter distance including statistical errors of $D_{A} = 72^{+5}_{-6}$ Mpc for this source, which is consistent with other distance measurements at this redshift. Possible sources of systematic errors and ways to correct for them are discussed.

astro-ph.CO↗

arXiv2019

Demonstration of magnetic field tomography with starlight polarization towards a diffuse sightline of the ISM

The availability of large datasets with stellar distance and polarization information will enable a tomographic reconstruction of the (plane-of-the-sky-projected) interstellar magnetic field in the near future. We demonstrate the feasibility of such a decomposition within a small region of the diffuse ISM. We combine measurements of starlight (R-band) linear polarization obtained using the RoboPol polarimeter with stellar distances from the second Gaia data release. The stellar sample is brighter than 17 mag in the R band and reaches out to several kpc from the Sun. HI emission spectra reveal the existence of two distinct clouds along the line of sight. We decompose the line-of-sight-integrated stellar polarizations to obtain the mean polarization properties of the two clouds. The two clouds exhibit significant differences in terms of column density and polarization properties. Their mean plane-of-the-sky magnetic field orientation differs by 60 degrees. We show how our tomographic decomposition can be used to constrain our estimates of the polarizing efficiency of the clouds as well as the frequency dependence of the polarization angle of polarized dust emission. We also demonstrate a new method to constrain cloud distances based on this decomposition. Our results represent a preview of the wealth of information that can be obtained from a tomographic map of the ISM magnetic field.

astro-ph.GA↗

arXiv2017

Optical polarization variations in the blazar PKS 1749+096

We report on the variation in the optical polarization of the blazar PKS 1749+096 observed in 2008--2015. The degree of polarization (PD) tends to increase in short flares having a time-scale of a few days. The object favors a polarization angle (PA) of $40^\circ$--$50^\circ$ at the flare maxima, which is close to the position angle of the jet ($20^\circ$--$40^\circ$). Three clear polarization rotations were detected in the negative PA direction associated with flares. In addition, a rapid and large decrease in the PA was observed in the other two flares, while another two flares showed no large PA variation. The light curve maxima of the flares possibly tend to lag behind the PD maxima and color-index minima. The PA became $-50^\circ$ to $-20^\circ$ in the decay phase of active states, which is almost perpendicular to the jet position angle. We propose a scenario to explain these observational features, where transverse shocks propagate along curved trajectories. The favored PA at the flare maxima suggests that the observed variations were governed by the variations in the Doppler factor, $δ$. Based on this scenario, the minimum viewing angle of the source, $θ_\mathrm{min}=4.8^\circ$--$6.6^\circ$, and the location of the source, $Δr\gtrsim 0.1$pc, from the central black hole were estimated. In addition, the acceleration of electrons by the shock and synchrotron cooling would have a time-scale similar to that of the change in $δ$. The combined effect of the variation in $δ$ and acceleration/cooling of electrons is probably responsible for the observed diversity of the polarization variations in the flares.

astro-ph.HE↗