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Time-resolved X-ray absorption can reveal the dynamical screening of the local Coulomb interaction in strongly correlated photo-excited materials. Here, we focus on the theoretical prediction of X-ray absorption in the presence of dynamical…
We study halo clustering bias with second- and third-order statistics of halo and matter density fields in the MICE Grand Challenge simulation. We verify that two-point correlations deliver reliable estimates of the linear bias parameters…
The correlation function of galaxy clusters has often been used as a test of cosmological models. A number of assumptions are implicit in the comparison of theoretical expectations to data. Here we use an ensemble of ten large N-body…
K-Means clustering algorithm is one of the most commonly used clustering algorithms because of its simplicity and efficiency. K-Means clustering algorithm based on Euclidean distance only pays attention to the linear distance between…
We propose a direct measure of tripartite quantum correlation in an arbitrary symmetric pure state of N correlated two-level atoms (qubits). We compute the third order moments of the collective pseudo-spin operators in terms of the…
Upcoming multi-wavelength astronomical surveys will soon discover all massive galaxy clusters and provide unprecedented constraints on cosmology and cluster astrophysics. In this paper, we investigate the constraining power of the…
We suggest a set of morphological measures that we believe can help in quantifying the shapes of two-dimensional cosmological images such as galaxies, clusters, and superclusters of galaxies. The method employs non-parametric morphological…
The clustering signals of galaxy clusters are known to be powerful tools for self-calibrating the mass-observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three…
Benefiting from the capability of building inter-dependencies among channels or spatial locations, attention mechanisms have been extensively studied and broadly used in a variety of computer vision tasks recently. In this paper, we…
We analyse the correlation function of mock galaxy clusters in redshift space. We constructed several mock catalogues designed to mimic the selection biases inherent in a variety of observational surveys. We explore different effects that…
Clustering is one of the main tasks in exploratory data analysis and descriptive statistics where the main objective is partitioning observations in groups. Clustering has a broad range of application in varied domains like climate,…
Surveys of galaxy clusters provide a promising method of testing models of structure formation in the universe. Within the context of our standard structure formation scenario, surveys provide measurements of the geometry of the universe…
We present the first measurement of the angular correlation function in a $K$-selected galaxy survey, from two fields covering almost 10 square degrees. The angular correlation function at small angles is well described by a $\theta^{-0.8}$…
QSOs and radio-galaxies, together with the CMB, ``normal'' galaxies and clusters, represent the main source of information about the origin and evolution of the Large Scale Structure. They can be used either directly, as tracers of the…
Observed galaxy clustering exhibits local transverse statistical isotropy around the line-of-sight (LOS). The variation of the LOS across a galaxy survey complicates the measurement of the observed clustering as a function of the angle to…
Forthcoming large galaxy cluster surveys will yield tight constraints on cosmological models. It has been shown that in an idealized survey, containing > 10,000 clusters, statistical errors on dark energy and other cosmological parameters…
We present the clustering of galaxy clusters as a useful addition to the common set of cosmological observables. The clustering of clusters probes the large-scale structure of the Universe, extending galaxy clustering analysis to the…
Detecting parity violation on cosmological scales would provide a striking clue to new physics. Large-scale structure offers the raw statistical power -- many three-dimensional modes -- to make such tests. However, for scalar observables,…
The modern image search system requires semantic understanding of image, and a key yet under-addressed problem is to learn a good metric for measuring the similarity between images. While deep metric learning has yielded impressive…
The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods…