相关论文: A PCA-based approach for subtracting thermal backg…
We develop a novel statistical approach to identify emission features or set upper limits in high-resolution spectra in the presence of high background. The method relies on detecting differences from the background using smooth tests and…
Our ability to observe, detect, and characterize exoplanetary atmospheres has grown by leaps and bounds over the last 20 years, aided largely by developments in astronomical instrumentation; improvements in data analysis techniques; and an…
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…
The deep learning technique has been employed in removing foreground contaminants from 21 cm intensity mapping, but its effectiveness is limited by the large dynamic range of the foreground amplitude. In this study, we develop a novel…
Principal component analysis (PCA) is a widely used dimension reduction tool in the analysis of many kind of high-dimensional data. It is used in signal processing, mechanical engineering, psychometrics, and other fields under different…
High-resolution Doppler spectroscopy provides an avenue to study the atmosphere of both transiting and non-transiting planets. This powerful method has also yielded some of the most robust atmospheric detections to date. Currently,…
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…
The Phase-Induced Amplitude Apodization (PIAA) coronagraph is a high performance coronagraph concept able to work at small angular separation with little loss in throughput. We present results obtained with a laboratory PIAA system…
Direct imaging is an active research topic in astronomy for the detection and the characterization of young sub-stellar objects. The very high contrast between the host star and its companions makes the observations particularly…
We present a novel method for Cosmic Microwave Background (CMB) foreground removal based on deep learning techniques. This method employs a Transformer model, referred to as \texttt{TCMB}, which is specifically designed to effectively…
We propose two detection techniques that take advantage of a small sky area approximation and are based on modifications of the "internal linear combination" (ILC) method, an approach widely used in Cosmology for the separation of the…
A priori, cosmic-ray measurements offer a unique capability to determine the vertical profile of atmospheric temperatures directly from ground. However, despite the increased understanding of the impact of the atmosphere on cosmic-ray…
The Dark Matter Time Projection Chamber (DMTPC) collaboration is developing a low pressure gas TPC for detecting Weakly Interacting Massive Particle (WIMP)-nucleon interactions. Optical readout with CCD cameras allows for the detection of…
Spectroscopy and imaging in the mid-infrared (2.5 $\mu$m $\sim$ $\lambda$ $\sim$ 25 $\mu$m) is bedevilled by the presence of a strong 300 K thermal background at room temperature that makes IR detectors decades noisier than can be readily…
This tutorial is an introduction to High-Contrast Imaging, a technique that enables astronomers to isolate light from faint planets and/or circumstellar disks that would otherwise be lost amidst the light of their host stars. Although…
In recent years, Imaging Atmospheric Cherenkov Telescopes (IACTs) have discovered a rich diversity of very high energy (VHE, > 100 GeV) gamma-ray emitters in the sky. These instruments image Cherenkov light emitted by gamma-ray induced…
As an unsupervised dimensionality reduction method, principal component analysis (PCA) has been widely considered as an efficient and effective preprocessing step for hyperspectral image (HSI) processing and analysis tasks. It takes each…
The analysis of the wavelength-dependent albedo of exoplanets represents a direct way to provide insight of their atmospheric composition and to constrain theoretical planetary atmosphere modelling. Wavelength-dependent albedo can be…
A robust post processing technique is mandatory to analyse the coronagraphic high contrast imaging data. Angular Differential Imaging (ADI) and Principal Component Analysis (PCA) are the most used approaches to suppress the quasi-static…
Principal component analysis (PCA) is one of the most fundamental tools in machine learning with broad use as a dimensionality reduction and denoising tool. In the later setting, while PCA is known to be effective at subspace recovery and…