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We measure cosmological parameters using the three-dimensional power spectrum P(k) from over 200,000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with WMAP and other data. Our results are consistent with a ``vanilla'' flat…
Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), one of three core programs in the Sloan Digital Sky Survey-IV (SDSS-IV), is an integral-field spectroscopic (IFS) survey of roughly 10,000 nearby galaxies. It employs dithered…
Hyperspectral optical imaging provides rich spectral information for estimating continuous environmental and material parameters; however, its high dimensionality and strong feature correlation pose significant challenges for machine…
Electron and scanning probe microscopy produce vast amounts of data in the form of images or hyperspectral data, such as EELS or 4D STEM, that contain information on a wide range of structural, physical, and chemical properties of…
Variational autoencoders (VAEs) are a popular class of deep generative models with many variants and a wide range of applications. Improvements upon the standard VAE mostly focus on the modelling of the posterior distribution over the…
Ultrafast multidimensional spectroscopies are powerful tools that can access charge and energy flow in complex materials, shifting chemical kinetics, and even many-body interactions in correlated matter. However, current implementations…
The chemical abundance patterns of near-pristine objects provide important constraints on the properties of the first generations of stars in the Universe. We present the chemical abundances of five very metal-poor ([M/H]<-2.5) sub damped…
In recent times, the use of stochastic geometry has become a popular and important tool for performance analysis of next-generation dense small cell wireless networks. Usually, such networks are modeled using 2 dimensional spatial Poisson…
This paper is the third in a series reporting on a study of carbon abundances in a carefully chosen sample of planetary nebulae representing a large range in progenitor mass and metallicity. We make use of the IUE Final Archive database…
Principal component analysis (PCA) is widely used for feature extraction and dimensionality reduction, with documented merits in diverse tasks involving high-dimensional data. Standard PCA copes with one dataset at a time, but it is…
Extracting the non-Gaussian information of the cosmic large-scale structure (LSS) is vital in unlocking the full potential of the rich datasets from the upcoming stage-IV galaxy surveys. Galaxy skew spectra serve as efficient…
Context. The APOGEE survey has obtained high-resolution infrared spectra of more than 100,000 stars. Deriving chemical abundances patterns of these stars is paramount to piecing together the structure of the Milky Way. While the derived…
Stellar abundance analysis relies on flexible, high-performance spectral synthesis. To meet these needs, we present PySME v1.0, an updated Python implementation of Spectroscopy Made Easy (SME) designed for precise and survey-scale modelling…
We present ELSA, a new modular software package, written in C, to analyze and manage spectroscopic data from emission-line objects. In addition to calculating plasma diagnostics and abundances from nebular emission lines, the software…
The goal of the Open Cluster Chemical Abundances and Mapping (OCCAM) survey is to constrain key Galactic dynamic and chemical evolution parameters by the construction and analysis of a large, comprehensive, uniform data set of infrared…
Several analytical forms of cloud particle size distributions (PSDs) have been used in numerical modeling and remote sensing retrieval studies of clouds and precipitation, including exponential, gamma, lognormal, and Weibull distributions.…
Climate anomalies significantly impact terrestrial carbon cycle dynamics, necessitating robust methods for detecting and analyzing anomalous behavior in plant productivity. This study presents a novel application of variational autoencoders…
Aiming to extract cosmological information from linear scales of the WISE$\times$SuperCOSMOS photometric redshift catalog, we perform a characterization of the systematic effects associated with stellar content, evidencing the presence of…
To understand the expansion dynamics of the universe from galaxy cluster scales, using the angular diameter distance (ADD) data from two different galaxy cluster surveys, we constrain four cosmological models to explore the underlying value…
The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions. The framework uses Atrous Spatial Pyramid Pooling (ASPP) module to enhance feature extraction. At…