Related papers: The ZTF Source Classification Project: III. A Cata…

The XMM identification (XID) programme is accumulating Optical/IR data to identify thousands of XMM sources at both high ($bII > 20^{\circ}$) and low galactic latitude. X-ray sources are divided into samples on the basis of their X-ray flux…

Simulating the long-term dynamics of multi-scale and multi-physics systems poses a significant challenge in understanding complex phenomena across science and engineering. The complexity arises from the intricate interactions between scales…

We have investigated a number of factors that can have significant impacts on the classification performance of $\gamma$-ray sources detected by Fermi Large Area Telescope (LAT) with machine learning techniques. We show that a framework of…

There is a growing concern about an impact of low-Earth-orbit (LEO) satellite constellations on ground-based astronomical observations, in particular, on wide-field surveys in the optical and infrared. The Zwicky Transient Facility (ZTF),…

The Kilodegree Extremely Little Telescope (KELT) has been surveying more than $70\%$ of the celestial sphere for nearly a decade. While the primary science goal of the survey is the discovery of transiting, large-radii planets around bright…

Source-Free Object Detection (SFOD) aims to adapt a source-pretrained object detector to a target domain without access to source data. However, existing SFOD methods predominantly rely on internal knowledge from the source model, which…

The Zwicky Catalog of galaxies (ZC), with m_Zw<=15.5mag, has been the basis for the Center for Astrophysics (CfA) redshift surveys. To date, analyses of the ZC and redshift surveys based on it have relied on heterogeneous sets of galaxy…

Follow-up of gravitational-wave events by wide-field surveys is a crucial tool for the discovery of electromagnetic counterparts to gravitational wave sources, such as kilonovae. Machine learning tools can play an important role in aiding…

Generation of science-ready data from processed data products is one of the major challenges in next-generation radio continuum surveys with the Square Kilometre Array (SKA) and its precursors, due to the expected data volume and the need…

The Z Transform is a mathematical operation in signal processing, which gives a tractable way to solve linear, constant-coefficient difference equations. Based on the classical Z transform and inspired by the thought of sliding DFT, a new…

We introduce an efficient method for learning linear models from uncertain data, where uncertainty is represented as a set of possible variations in the data, leading to predictive multiplicity. Our approach leverages abstract…

We present a catalog of 150 variable stars, including 13 stars with exoplanet candidates. 37 stars were identified as variables for the first time. As a result of a 2.5-year photometric survey of exoplanets, we have obtained and analyzed…

This study presents a bidirectional Long Short-Term Memory (LSTM) neural network for classifying transient astronomical object light curves from the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC) dataset. The…

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SV) and burst-like (BL) transients, using multi-band image-differencing time-series…

Upcoming synoptic surveys are set to generate an unprecedented amount of data. This requires an automatic framework that can quickly and efficiently provide classification labels for several new object classification challenges. Using data…

Zigbee is widely used in smart home environments due to its low power consumption and support for mesh networking, making it a relevant target for traffic-based IoT forensic analysis. However, existing studies often rely on limited datasets…

We aim to construct an exceptionally deep (V ~< 27) catalog of variable objects in selected Galactic and extragalactic fields visited multiple times by the Hubble Space Telescope (HST). While HST observations of some of these fields were…

Digital tracking detects faint solar system bodies by stacking many images along hypothesized orbits, revealing objects that are undetectable in every individual exposure. Previous searches have been restricted to small areas and short time…

We present the first results of our dedicated programme of automatised classification of galaxies, stars and quasars in the mid-infrared all-sky data from the WISE survey. We employ the Support Vector Machines (SVM) algorithm, which defines…

The modulation transfer function (MTF) is widely used to characterise the performance of optical systems. Measuring it is costly and it is thus rarely available for a given lens specimen. Instead, MTFs based on simulations or, at best, MTFs…