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Accurate photometric redshifts are among the key requirements for precision weak lensing measurements. Both the large size of the Sloan Digital Sky Survey (SDSS) and the existence of large spectroscopic redshift samples that are…
We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC…
Broad-band measurements of flux for galaxies at different redshifts measure different regions of the rest-frame galaxy spectrum. Certain astronomical questions, such as the evolution of the luminosity function of galaxies, require…
This paper attempts to undertake the study of Restored Gaussian Blurred Images. by using four types of techniques of deblurring image as Wiener filter, Regularized filter, Lucy Richardson deconvlutin algorithm and Blind deconvlution…
A technique for the construction of axisymmetric distribution functions for individual galaxies is presented. It starts from the observed surface bright- ness distribution, which is deprojected to gain the axisymmetric luminosity density,…
In this paper, we address common error sources for 3D Gaussian Splatting (3DGS) including blur, imperfect camera poses, and color inconsistencies, with the goal of improving its robustness for practical applications like reconstructions…
We present a novel approach to photometric redshifts, one that merges the advantages of both the template fitting and empirical fitting algorithms, without any of their disadvantages. This technique derives a set of templates, describing…
The accurate determination of the true redshift distributions in tomographic bins is critical for cosmological constraints from photometric surveys. The proposed redshift self-calibration method, which utilizes the photometric galaxy…
A speedy pixon algorithm for image reconstruction is described. Two applications of the method to simulated astronomical data sets are also reported. In one case, galaxy clusters are extracted from multiwavelength microwave sky maps using…
We extend the real-space mapping method developed in Shi et at. (2016) so that it can be applied to flux-limited galaxy samples. We use an ensemble of mock catalogs to demonstrate the reliability of this extension, showing that it allows…
We developed a Deep Convolutional Neural Network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies in the Main Galaxy Sample of the Sloan Digital Sky Survey…
This paper presents the development of a new algorithm for Gaussian based color image enhancement system. The algorithm has been designed into architecture suitable for FPGA/ASIC implementation. The color image enhancement is achieved by…
Improving distance measurements in large imaging surveys is a major challenge to better reveal the distribution of galaxies on a large scale and to link galaxy properties with their environments. Photometric redshifts can be efficiently…
We present a simple and accurate method to constrain galaxy bias based on the distribution of counts in cells. The most unique feature of our technique is that it is applicable to non-linear scales, where both dark matter statistics and the…
Targeted color-dots with varying shapes and sizes in images are first exhaustively identified, and then their multiscale 2D geometric patterns are extracted for testing spatial uniformness in a progressive fashion. Based on color theory in…
I employ the Lucy rectification algorithm to recover the inclination-corrected distribution of local disk galaxies in the plane of absolute magnitude ($M_i$) and HI velocity width ($W_{20}$). By considering the inclination angle as a random…
The development of fast and accurate methods of photometric redshift estimation is a vital step towards being able to fully utilize the data of next-generation surveys within precision cosmology. In this paper we apply a specific approach…
Accurate estimation of photometric redshifts (photo-$z$) is crucial in studies of both galaxy evolution and cosmology using current and future large sky surveys. In this study, we employ Random Forest (RF), a machine learning algorithm, to…
We describe a method for constructing mock galaxy catalogues which are well suited for use in conjunction with large photometric surveys. We use the semi-analytic galaxy formation model of Bower et al. implemented in the Millennium…
Reconstructions of potential in Schrodinger equation with data in the diffusion frequency domain have been successfully obtained within Lippmann-Schwinger-Lanczos (LSL) approach, however limited resolution away from the sensor positions…