Related papers: RASSINE: Interactive tool for normalising stellar …

*Context: The optimisation of new multiplex spectrographs (resolution, wavelength range,...), their associated surveys (choice of setup), or their parameterisation pipelines require methods that estimate which wavelengths contain useful…

I present a fast Python tool, SpectRes, for carrying out the resampling of spectral flux densities and their associated uncertainties onto different wavelength grids. The function works with any grid of wavelength values, including…

This work investigates the spectrum parameterization problem using deep neural networks (DNNs). The proposed scheme consists of the following procedures: first, the configuration of a DNN is initialized using a series of autoencoder neural…

We propose an efficient algorithm for reconstructing one-dimensional wide-band line spectra from their Fourier data in a bounded interval $[-\Omega,\Omega]$. While traditional subspace methods such as MUSIC achieve super-resolution for…

We introduce a new 1D stellar spectral synthesis Python code called stardis. stardis is a modular, open-source radiative transfer code that is capable of spectral synthesis from near-UV to IR for FGK stars. We describe the structure,…

Wavelength calibration is a routine and critical part of any spectral work-flow, but many astronomers still resort to matching detected peaks and emission lines by hand. We present RASCAL (RANSAC Assisted Spectral CALibration), a python…

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) is the most sensitive ground-based, single-dish radio telescope on Earth. However, the original HI spectra produced by FAST are affected by standing waves. To maximize the…

Hyperspectral remote sensing images (HSIs) are characterized by having a low spatial resolution and a high spectral resolution, whereas multispectral images (MSIs) are characterized by low spectral and high spatial resolutions. These…

Optimal extraction is a key step in processing the raw images of spectra as registered by two-dimensional detector arrays to a one-dimensional format. Previously reported algorithms reconstruct models for a mean one-dimensional spatial…

Natural images tend to mostly consist of smooth regions with individual pixels having highly correlated spectra. This information can be exploited to recover hyperspectral images of natural scenes from their incomplete and noisy…

We applied machine learning to the entire data history of ESO's High Accuracy Radial Velocity Planet Searcher (HARPS) instrument. Our primary goal was to recover the physical properties of the observed objects, with a secondary emphasis on…

The fitting of spectral lines is a common step in the analysis of line observations and simulations. However, the observational noise, the presence of multiple velocity components, and potentially large data sets make it a non-trivial task.…

We developed a Python based framework for astronomical image processing and analysis. Astronomical image loading, normalizing, stacking, and filtering processes represent visible range images from grayscale. Besides, the blending process…

Aims. We provide an easy-to-use full-spectrum fitting package and explore its applications to (i) the determination of the stellar atmospheric parameters and (ii) the study of the history of stellar populations. Methods. We developed ULySS,…

Aims. We study the 2D spectral line profile of HARPS (High Accuracy Radial Velocity Planet Searcher), measuring its variation with position across the detector and with changing line intensity. The characterization of the line profile and…

Well-calibrated spectropolarimetry studies at resolutions of $R>$10,000 with signal-to-noise ratios (SNRs) better than 0.01\% across individual line profiles, are becoming common with larger aperture telescopes. Spectropolarimetric studies…

A pilot project has been proceeded to map 1 deg$^2$ on the Galactic plane for radio recombination lines (RRLs) using the Five hundred meter Aperture Spherical Telescope (FAST). The motivation is to verify the techniques and reliabilities…

Remote sensing image restoration aims to reconstruct missing or corrupted areas within images. To date, low-rank based models have garnered significant interest in this field. This paper proposes a novel low-rank regularization term, named…

We introduce a new pipeline for analyzing and mitigating radio frequency interference (RFI), which we call Sky-Subtracted Incoherent Noise Spectra (SSINS). SSINS is designed to identify and remove faint RFI below the single baseline thermal…

The use of 3D hydrodynamical simulations of stellar surface convection for model atmospheres is computationally expensive. Although these models have been available for quite some time, their use is limited because of the lack of extensive…