Related papers: Evaluating the optical classification of Fermi BCU…
We present the results of the \textit{Fermi}-LAT 10-years-long light curves (LCs) modeling of selected blazars: six flat spectrum radio quasars (FSRQs) and five BL Lacertae (BL Lacs), examined in 7-, 10-, and 14-day binning. The LCs and…
The future Rubin Legacy Survey of Space and Time (LSST) is expected to deliver its first data release in the current of 2025. The upcoming survey will provide us with images of galaxy clusters in the optical to the near-infrared, with…
Using public \fermi LAT and \swift BAT observations, we constructed the first sample of blazars selected at both hard X-rays and gamma-rays. Studying its spectral properties, we find a luminosity dependence of the spectral slopes at both…
We describe an image-based method that uses two radio criteria, compactness and spectral index, to identify promising pulsar candidates among Fermi Large Area Telescope (LAT) unassociated sources. These criteria are applied to those radio…
A new maximum approximate likelihood (ML) estimation algorithm for the mixture of Kent distribution is proposed. The new algorithm is constructed via the BSLM (block successive lower-bound maximization) framework and incorporates manifold…
The amount of data for machine learning (ML) applications is constantly growing. Not only the number of observations, especially the number of measured variables (features) increases with ongoing digitization. Selecting the most appropriate…
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…
Brightest cluster galaxies (BCGs) lie deep within the largest gravitationally bound structures in existence. Though some cluster finding techniques identify the position of the BCG and use it as the cluster center, other techniques may not…
We describe a catalogue of gamma-ray source candidates, selected using the Minimum Spanning Tree (MST) algorithm on the 9-years Fermi-LAT sky (Pass 8) at energies higher than 10 GeV. The extragalactic sky at absolute Galactic latitudes…
We present the results of an identification campaign of unassociated sources from the Fermi Large Area Telescope 3FHL catalog. Out of 200 unidentified sources, we selected 110 sources for which archival Swift-XRT observations were…
The third catalog of active galactic nuclei (AGNs) detected by the Fermi Large Area Telescope (3LAC) is presented. It is based on the third catalog (3FGL,\cite{3FGL}) of sources detected with a test statistic greater than 25, using the…
Flat Spectrum Radio Quasars (FSRQs) and BL Lac objects detected in the first three months of the Fermi survey neatly separate in the gamma-ray spectral index vs gamma-ray luminosity plane. BL Lac objects are less luminous and have harder…
We collect a sample of 78 Fermi detected blazars with broad line region (BLR) data and the quasi-simultaneous multi-wave band data. By analyzing the sample, we find: (1) For whole blazar sample, there exist significant correlations between…
Galaxy cluster-scale strong gravitational lensing systems are rare yet valuable tools for investigating the properties of dark matter and dark energy, as well as providing the opportunity to study the distant universe at flux levels and…
Recent advances in foundation models present new opportunities for interpretable visual recognition -- one can first query Large Language Models (LLMs) to obtain a set of attributes that describe each class, then apply vision-language…
We present a machine learning (ML) pipeline to identify star clusters in the multi{color images of nearby galaxies, from observations obtained with the Hubble Space Telescope as part of the Treasury Project LEGUS (Legacy ExtraGalactic…
This work proposes a multiple machine learning method (MMLM) aiming to improve the accuracy and robustness in the analysis of star clusters. The MMLM performance is evaluated by applying it to the reanalysis of the old binary cluster…
In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised…
Following our work presented in Dai et al. (2016), we report our detailed data analysis for another 38 Fermi gamma-ray un-associated sources. These sources are selected from the Fermi Large Area Telescope (LAT) third source catalog on the…
We examine the constraints on the luminosity-dependent density evolution model for the evolution of blazars given the observed spectrum of the diffuse gamma-ray background (DGRB), blazar source-count distribution, and the blazar spectral…