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During a tracking mode observation, every telescope with an alt-azimuthal mount shows a rotation in the field of view (FoV) due to the diurnal motion of the Earth. The angular extension of the rotation depends mainly on the time length of…
Fast moving celestial objects are characterized by velocities across the celestial sphere that significantly differ from the motions of background stars. In observational images, these objects exhibit distinct shapes, contrasting with the…
We present a new algorithm designed to improve the signal to noise ratio (SNR) of point and extended source detections in direct imaging data. The novel part of our method is that it finds the linear combination of the science images that…
In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…
In this paper we apply ideas from information theory to create a method for the design of optimal filters for photometric redshift estimation. We show the method applied to a series of simple example filters in order to motivate an…
Achieving a balance between accuracy and efficiency is a critical challenge in facial landmark detection (FLD). This paper introduces Parallel Optimal Position Search (POPoS), a high-precision encoding-decoding framework designed to address…
While conventional imaging in VLBI provides information only about the relative position between different features of a given source, phase-referenced observations can provide precise positional information with respect to an external…
We present the DONUTS autoguiding algorithm, designed to fix stellar positions at the sub-pixel level for high-cadence time-series photometry, which is also capable of autoguiding on defocused stars. DONUTS was designed to calculate guide…
Most current astronomical adaptive optics (AO) systems rely on the availability of a bright star to measure the distortion of the incoming wavefront. Replacing the guide star with an artificial laser beacon alleviates this dependency on…
Obtaining accurate photometric redshift estimations is an important aspect of cosmology, remaining a prerequisite of many analyses. In creating novel methods to produce redshift estimations, there has been a shift towards using machine…
We propose an object detection algorithm which is efficient and fast enough to be used in (almost) real time with the limited computer capacities onboard satellites. For stars below the saturation limit of the CCD detectors it is based on a…
Scoring rules are aimed at evaluation of the quality of predictions, but can also be used for estimation of parameters in statistical models. We propose estimating parameters of multivariate spatial models by maximising the average…
We present an algorithmic method for efficiently planning a long-term, large-scale multi-object spectroscopy program. The Sloan Digital Sky Survey V (SDSS-V) Focal Plane System performs multi-object spectroscopy using 500 robotic…
Most current high contrast imaging point spread function (PSF) subtraction algorithms use some form of a least-squares noise minimization to find exoplanets that are, before post-processing, often hidden below the instrumental speckle…
The next generation of spectroscopic surveys will have a wealth of photometric data available for use in target selection. Selecting the best targets is likely to be one of the most important hurdles in making these spectroscopic campaigns…
We apply a combination of a Genetic Algorithms (GA) and Support Vector Machines (SVM) machine learning algorithm to solve two important problems faced by the astronomical community: star/galaxy separation, and photometric redshift…
Aims. The purpose of this paper is to describe a new post-processing algorithm dedicated to the reconstruction of the spatial distribution of light received from off-axis sources, in particular from circumstellar disks. Methods. Built on…
Among the many challenges posed by the huge data volumes produced by the new generation of astronomical instruments there is also the search for rare and peculiar objects. Unsupervised outlier detection algorithms may provide a viable…
A consensus-based optimization (CBO) algorithm, which enables derivative and mesh-free optimization, is presented to localize a bioluminescent source. The light propagation is modeled by the radiative transfer equation approximated by…
With the growth of the scale, depth, and resolution of astronomical imaging surveys, there is an increased need for highly accurate automated detection and extraction of astronomical sources from images. This also means there is a need for…