Related papers: ZAP -- Enhanced PCA Sky Subtraction for Integral F…

We present the data reduction pipeline for CHARIS, a high-contrast integral-field spectrograph for the Subaru Telescope. The pipeline constructs a ramp from the raw reads using the measured nonlinear pixel response, and reconstructs the…

In this paper we present a combined strategy for the retrieval of atmospheric profiles from infrared sounders. The approach considers the spatial information and a noise-dependent dimensionality reduction approach. The extracted features…

Machine learning (ML) methods have proved to be a very successful tool in physical sciences, especially when applied to experimental data analysis. Artificial intelligence is particularly good at recognizing patterns in high dimensional…

We prepare real-life Cosmic Microwave Background (CMB) lensing extraction with the forthcoming Planck satellite data, by studying two systematic effects related to the foregrounds contamination: the impact of foreground residuals after a…

ZEBRA, the Zurich Extragalactic Bayesian Redshift Analyzer, is a tool for estimating redshifts and template types of galaxies using medium- and broad-band photometric data. ZEBRA employs novel techniques within the template-fitting approach…

For the sake of complete theoretical research of atmospheric refraction, the atmospheric refraction under the condition of lower angles of elevation is still worthy to be analyzed and explored. In some engineering applications, the objects…

We consider the problem of synthetic aperture radar (SAR) imaging and motion estimation of complex scenes. By complex we mean scenes with multiple targets, stationary and in motion. We use the usual setup with one moving antenna emitting…

We present a new, fast, algorithm for the separation of astrophysical components superposed in maps of the sky, based on the fast Independent Component Analysis technique (FastICA). It allows to recover both the spatial pattern and the…

The Multi Unit Spectroscopic Explorer (MUSE) is an integral-field spectrograph operating in the visible wavelength range, and installed at the Very Large Telescope (VLT). The official MUSE pipeline is available from ESO. However, for the…

Ground-based large-aperture telescopes, interferometers, and future Extremely Large Telescopes equipped with adaptive-optics systems provide angular resolution and high-contrast performance that are superior to space-based telescopes at…

We present the first tests of a new method, the Correlated Component Analysis (CCA) based on second-order statistics, to estimate the mixing matrix, a key ingredient to separate astrophysical foregrounds superimposed to the Cosmic Microwave…

The Sloan Digital Sky Survey (SDSS) currently provides by far the largest homogeneous sample of intermediate signal-to-noise ratio (S/N) optical spectra of galaxies and quasars. The fully automated SDSS spectroscopic reduction pipeline has…

In the last decade, the study of cosmic microwave background (CMB) data has become one of the most powerful tools to study and understand the Universe. More precisely, measuring the CMB power spectrum leads to the estimation of most…

Cosmic shear surveys serve as a powerful tool for mapping the underlying matter density field, including non-visible dark matter. A key challenge in cosmic shear surveys is the accurate reconstruction of lensing convergence ($\kappa$) maps…

We propose a postselected amplification (PSA) scheme for phase shift measurement of optical coherent states when passing through the Mach-Zehnder-interferometer (MZI). Different from the usual weak-value-amplification (WVA) formulation, the…

Our main objective is to develop a denoising strategy to increase the signal to noise ratio of individual spectral lines of stellar spectropolarimetric observations. We use a multivariate statistics technique called Principal Component…

We model a 21 cm intensity mapping survey in the redshift range 0.01<z<1.5 designed to simulate the skies as seen by future radio telescopes such as the Square Kilometre Array (SKA), including instrumental noise and Galactic foregrounds. In…

Many powerful imaging techniques for cold atoms are based on determining the optical density by comparing a beam image having passed through the atom cloud to a reference image taken under similar conditions with no atoms. In practice the…

We present a new algorithm, ChunkedPCA, to remove common background fluctuations from datasets acquired with a radio camera. ChunkedPCA is an improvement on using PCA to achieve fewer artifacts and better RMS on the cleaned dataset. The…

In recent years, Artificial Intelligence techniques have proved to be very successful when applied to problems in physical sciences. Here we apply an unsupervised Machine Learning (ML) algorithm called Principal Component Analysis (PCA) as…