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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 {Delta}z_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.
The very existence of more than a dozen of high-redshift (z>4) blazars indicates that a much larger population of misaligned powerful jetted AGN was already in place when the Universe was <1.5 Gyr old. Such parent population proved to be very elusive
We present average R-band optopolarimetric data, as well as variability parameters, from the first and second RoboPol observing season. We investigate whether gamma- ray--loud and gamma-ray--quiet blazars exhibit systematic differences in their optic
Background showers triggered by hadrons represent over 99.9% of all particles arriving at ground-based gamma-ray observatories. An important stage in the data analysis of these observatories, therefore, is the removal of hadron-triggered showers. Cur
Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the Hubble ex