Related papers: Functional principal component analysis of radio-o…
Optimal estimation of signal amplitude, background level, and photocentre location is crucial to the combined extraction of astrometric and photometric information from focal plane images, and in particular from the one-dimensional…
We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing ADI and LOCI for increasing the contrast achievable next to a bright star. The stellar PSF is…
We investigate the capability of ongoing radio telescopes for probing Faraday rotation measure (RM) due to the intergalactic magnetic field (IGMF) in the large-scale structure of the universe which is expected to be of order $O(1) {\rm…
In remote sensing rotated object detection, mainstream methods suffer from two bottlenecks, directional incoherence at detector neck and task conflict at detecting head. Ulitising fourier rotation equivariance, we introduce Fourier Angle…
An asymmetric relativistic model for FRII radio sources is described which takes account of both relativistic effects and intrinsic/environmental asymmetries to explain the observed structural asymmetry of their radio lobes. A key feature…
The study of quantum reference frames has received renewed interest over the last years, leading to the parallel development of non-equivalent frameworks by different communities. We clarify the differences between these frameworks. At the…
Functional principal component analysis (FPCA) has been widely used to capture major modes of variation and reduce dimensions in functional data analysis. However, standard FPCA based on the sample covariance estimator does not work well in…
The aim of this work is to provide new insights on the dynamics associated to the resonances which arise as a consequence of the coupling of the effect due to the oblateness of the Earth and the Solar Radiation Pressure (SRP) effect for an…
In this article we summarise on-going work on the so-called Gaia FGK Benchmark Stars. This work consists of the determination of their atmospheric parameters and of the construction of a high-resolution spectral library. The definition of…
Complex electromagnetic environments, often containing multiple jammers with different jamming patterns, produce non-uniform jamming power across the frequency spectrum. This spectral non-uniformity directly induces severe distortion in the…
Principal component analysis is a statistical method, which lowers the number of important variables in a data set. The use of this method for the bursts' spectra and afterglows is discussed in this paper. The analysis indicates that three…
The concept of quantum correlation matrix for observables leads to the application of the PCA (Principal Component Analysis) also for quantum system in Hilbert space. It is shown that, in the case of a 2x2 spin system where the observables…
We study principal component analysis (PCA) for mean zero i.i.d. Gaussian observations $X_1,\dots, X_n$ in a separable Hilbert space $\mathbb{H}$ with unknown covariance operator $\Sigma.$ The complexity of the problem is characterized by…
We present measurements of the intrinsic alignments (IAs) of the star-forming gas of galaxies in the EAGLE simulations. Radio continuum imaging of this gas enables cosmic shear measurements complementary to optical surveys. We measure the…
Rotation measure (RM) grids of extragalactic radio sources have been widely used for studying cosmic magnetism. But their potential for exploring the intergalactic magnetic field (IGMF) in filaments of galaxies is unclear, since other…
The next generation of weak lensing surveys will trace the evolution of matter perturbations and gravitational potentials from the matter dominated epoch until today. Along with constraining the dynamics of dark energy, they will probe the…
Principal Component Analysis (PCA) is an efficient tool to optimize the multiparameter tests of general relativity (GR) where one tests for simultaneous deviations in multiple post-Newtonian (PN) phasing coefficients by introducing…
Infrared target tracking plays an important role in both civil and military fields. The main challenges in designing a robust and high-precision tracker for infrared sequences include overlap, occlusion and appearance change. To this end,…
Principal component analysis (PCA) is a powerful standard tool for reducing the dimensionality of data. Unfortunately, it is sensitive to outliers so that various robust PCA variants were proposed in the literature. This paper addresses the…
Published analyses of very long baseline interferometry (VLBI) data for the sources included in the third International Celestial Reference Frame (ICRF3) catalog have revealed object-specific, excess astrometric variability and…