相关论文: A New Framework for Multi-Line Analysis Combined K…

We apply principal component analysis (PCA) to the integrated intensity maps of 13 molecular lines of the nearby type-2 Seyfert galaxy NGC 1068 obtained by Atacama Large Millimeter/sub-millimeter Array (ALMA) to objectively visualize the…

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which better exploits the complicated spatial structure of high-dimensional features.…

We dissect the kinematics and morphology of the molecular gas within the near-nuclear region of NGC 1068 to understand the mechanisms in the central AGN that might be fueling it, and the impact of its energy output on the surrounding…

Recent developments in (sub-)millimeter facilities have drastically changed the amount of information obtained from extragalactic spectral scans. In this paper, we present a feature extraction technique using principal component analysis…

In recent years, machine learning models have been increasingly applied to spectroscopic datasets for chemical and biomedical analysis. For their successful adoption, particularly in clinical and safety-critical settings, professionals and…

Active galactic nuclei (AGNs) influence their host galaxies through winds and jets that can drive molecular outflows, traceable with CO line emissions using the Atacama Large Millimeter Array (ALMA). Recent studies leveraging ALMA data have…

Principal Component Analysis (PCA) and its nonlinear extension Kernel PCA (KPCA) are widely used across science and industry for data analysis and dimensionality reduction. Modern deep learning tools have achieved great empirical success,…

Principal component analysis (PCA) is largely adopted for chemical process monitoring and numerous PCA-based systems have been developed to solve various fault detection and diagnosis problems. Since PCA-based methods assume that the…

Kernel methods have been proven to be a powerful tool for the integration and analysis of highthroughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products. The kernelized…

Three-dimensional (3D) spectroscopy techniques are becoming more and more popular, producing an increasing number of large data cubes. The challenge of extracting information from these cubes requires the development of new techniques for…

We present a detailed analysis of ALMA Bands 7 and 9 data of CO, HCO+, HCN and CS, augmented with Plateau de Bure Interferometer (PdBI) data of the ~ 200 pc circumnuclear disk (CND) and the ~ 1.3 kpc starburst ring (SB ring) of NGC~1068, a…

Methodologies for multidimensionality reduction aim at discovering low-dimensional manifolds where data ranges. Principal Component Analysis (PCA) is very effective if data have linear structure. But fails in identifying a possible…

Principal Component Analysis (PCA) is a powerful and popular dimensionality reduction technique. However, due to its linear nature, it often fails to capture the complex underlying structure of real-world data. While Kernel PCA (kPCA)…

We present an imaging molecular line survey in the 3-mm band (85-114 GHz) focused on one of the nearest galaxies with an active galactic nucleus (AGN), NGC 1068, based on observations taken with the Atacama Large Millimeter/submillimeter…

Principal Component Analysis (PCA) is a highly useful topic within an introductory Linear Algebra course, especially since it can be used to incorporate a number of applied projects. This method represents an essential application and…

Molecular lines are powerful diagnostics of the physical and chemical properties of the interstellar medium (ISM). These ISM properties, which affect future star formation, are expected to differ in starburst galaxies from those of more…

We analyse a sample of 26 active galactic nuclei with deep XMM-Newton observations, using principal component analysis (PCA) to find model independent spectra of the different variable components. In total, we identify at least 12…

We present 0.8-mm band molecular images and spectra obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) toward one of the nearest galaxies with an active galactic nucleus (AGN), NGC 1068. Distributions of CO isotopic…

The ALMA large program exoALMA offers a unique window into the three-dimensional physical and dynamical properties of 15 circumstellar disks where planets may be actively forming. Here, we present an analysis methodology to map the gas disk…

We use the Atacama Large sub/Millimetre Array (ALMA) to efficiently observe spectral lines across Bands 3, 4, 5, 6, 7, and 8 at high-resolution (0.5" - 0.1") for 16 bright southern Herschel sources at $1.5 < z < 4.2$. With only six and a…