相关论文: Source finding, parametrization and classification…

We present a method of reliably extracting the flux of individual sources from sky maps in the presence of noise and a source population in which number counts are a steeply falling function of flux. The method is an extension of a standard…

Identifying the electromagnetic counterparts of gravitational wave (GW) sources detected by upcoming networks of advanced ground-based interferometers will be challenging due in part to the large number of unrelated astrophysical transients…

We introduce Flat Hilbert Bayesian Inference (FHBI), an algorithm designed to enhance generalization in Bayesian inference. Our approach involves an iterative two-step procedure with an adversarial functional perturbation step and a…

We present a comprehensive model to predict the rate of spectroscopic confusion in HI surveys, and demonstrate good agreement with the observable confusion in existing surveys. Generically the action of confusion on the HI mass function was…

Remote sensing is a higher technology to produce knowledge for data mining applications. In principle hyperspectral images (HSIs) is a remote sensing tool that provides precise classification of regions. The HSI contains more than a hundred…

Detection of point sources in images is a fundamental operation in astrophysics, and is crucial for constraining population models of the underlying point sources or characterizing the background emission. Standard techniques fall short in…

We have used the Westerbork array to carry out an unbiased wide-field survey for HI emission features, achieving an RMS sensitivity of about 18 mJy/Beam at a velocity resolution of 17 km/s over 1800 deg^2 and between -1000 < V_Hel<+6500…

We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic strong-lens simulations, deep neural network classification, and…

Challenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly…

Active search is the process of identifying high-value data points in a large and often high-dimensional parameter space that can be expensive to evaluate. Traditional active search techniques like Bayesian optimization trade off…

We present the design and implementation of an automated data calibration and reduction pipeline for very-long-baseline interferometric (VLBI) observations taken at millimeter wavelengths. These short radio-wavelengths provide the best…

Simulation-based inference (SBI) has emerged as a powerful tool for extracting cosmological information from galaxy surveys deep into the non-linear regime. Despite its great promise, its application is limited by the computational cost of…

We present the results of completeness simulations for the detection of point sources as well as redshifted elliptical and spiral galaxies in the K'-band images of the Munich Near-Infrared Cluster Survey (MUNICS). The main focus of this…

Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to process and analyze these hyperspectral (HS) products mainly by…

The reconstruction of the unknown acoustic source is studied using the noisy multiple frequency data on a remote closed surface. Assume that the unknown source is coded in a spatial dependent piecewise constant function, whose support set…

Two-sample hypothesis testing for network comparison presents many significant challenges, including: leveraging repeated network observations and known node registration, but without requiring them to operate; relaxing strong structural…

Observations of neutral hydrogen can provide a wealth of information about the distribution and kinematics of galaxies. To detect HI beyond the ionisation edge of galaxy disks, column density sensitivities have to be achieved that probe the…

The paper proposes a new high spatial resolution hyperspectral (HR-HS) image estimation method based on convex optimization. The method assumes a low spatial resolution HS (LR-HS) image and a guide image as observations, where both…

Hyperspectral images (HSI) classification is a high technical remote sensing tool. The main goal is to classify the point of a region. The HIS contains more than a hundred bidirectional measures, called bands (or simply images), of the same…

High-quality astronomical images delivered by modern ground-based and space observatories demand adequate, reliable software for their analysis and accurate extraction of sources, filaments, and other structures, containing massive amounts…