ZAP -- Enhanced PCA Sky Subtraction for Integral Field Spectroscopy

A Semi-blind PCA-based Foreground Subtraction Method for 21 cm Intensity Mapping

The Principal Component Analysis (PCA) method and the Singular Value Decomposition (SVD) method are widely used for foreground subtraction in 21 cm intensity mapping experiments. We show their equivalence, and point out that the condition for completely clean separation of foregrounds and cosmic 21 cm signal using the PCA/SVD is unrealistic. We propose a PCA-based foreground subtraction method, dubbed "Singular Vector Projection (SVP)" method, which exploits a priori information of the left and/or right singular vectors of the foregrounds. We demonstrate with simulation tests that this new, se…

Telluric-line subtraction in high-accuracy velocimetry: a PCA-based approach

Optical velocimetry has led to the detection of more than 500 planets to date and there is a strong effort to push m/s velocimetry to the near-infrared to access cooler and lighter stars. The presence of numerous telluric absorption lines in the nIR brings an important challenge. As the star's barycentric velocity varies through the year, the telluric absorption lines effectively varies in velocity relative to the star's spectrum by the same amount leading to important systematic RV offsets. We present a novel principal component analysis-based approach for telluric line subtraction and demons…

Eliminating Primary Beam Effect in Foreground Subtraction of Neutral Hydrogen Intensity Mapping Survey with Deep Learning

In the neutral hydrogen (HI) intensity mapping (IM) survey, the foreground contamination on the cosmological signals is extremely severe, and the systematic effects caused by radio telescopes themselves further aggravate the difficulties in subtracting foreground. In this work, we investigate whether the deep learning method, concretely the 3D U-Net algorithm here, can play a crucial role in foreground subtraction when considering the systematic effect caused by the telescope's primary beam. We consider two beam models, i.e., the Gaussian beam model as a simple case and the Cosine beam model a…

Sky subtraction at the Poisson limit with fibre-optic multi-object spectroscopy

We report on the limitations of sky subtraction accuracy for long duration fibre-optic multi-object spectroscopy of faint astronomical sources during long duration exposures. We show that while standard sky subtraction techniques yield accuracies consistent with the Poisson noise limit for exposures of 1 hour duration, there are large scale systematic defects that inhibit the sensitivity gains expected on the summation of longer duration exposures. For the AAOmega system at the Anglo-Australian Telescope we identify a limiting systematic sky subtraction accuracy which is reached after integrat…

射电相机共模背景涨落扣除的新方法：分块主成分分析方法

New method for subtraction of common background fluctuation for radio camera: Chunked Principal Component Analysis method

本文提出 ChunkedPCA 算法，通过分组未观测源的探测器像素来估计并扣除射电相机共模背景涨落，在模拟和野边山 45 米望远镜 MKID 相机实测数据上验证了其相比传统 PCA 能保留源流量并获得更干净基线。

Spectral and angular differential imaging with SPHERE/IFS. Assessing the performance of various PCA-based approaches to PSF subtraction

Angular differential imaging (ADI) and spectral differential imaging (SDI) are commonly used for direct detection and characterisation of young, Jovian exoplanets in datasets obtained with the SPHERE/IFS instrument. We compare the performance of ADI, SDI, and three combinations of ADI and SDI to find which technique achieves the highest signal-to-noise ratio (S/N), and we analyse their performance as functions of integration time, field rotation, and wavelength range. We analyse SPHERE/IFS observations of three known exoplanets, namely Beta Pictoris b, 51 Eridani b, and HR 8799 e, with five di…