Topic
Centroid
About: Centroid is a research topic. Over the lifetime, 4110 publications have been published within this topic receiving 53637 citations. The topic is also known as: barycenter (geometry) & geometric center of a plane figure.
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TL;DR: In this article, a weak-lensing study of the cluster A520 based on Advanced Camera for Surveys (ACS) data is presented, which confirms the previous claims that a substantial amount of dark mass is present between two luminous subclusters where we observe very little light.
Abstract: We present a weak-lensing study of the cluster A520 based on Advanced Camera for Surveys (ACS) data. The excellent data quality provides a mean source density of ~109 arcmin–2, which improves both resolution and significance of the mass reconstruction compared to a previous study based on Wide Field Planetary Camera 2 (WFPC2) images. We take care in removing instrumental effects such as the charge trailing due to radiation damage of the detector and the position-dependent point-spread function. This new ACS analysis confirms the previous claims that a substantial amount of dark mass is present between two luminous subclusters where we observe very little light. The centroid of the dark peak in the current ACS analysis is offset to the southwest by ~1' with respect to the centroid from the WFPC2 analysis. Interestingly, this new centroid is in better agreement with the location where the X-ray emission is strongest, and the mass-to-light ratio estimated with this centroid is much higher (813 ± 78 M ☉/L R☉) than the previous value; the aperture mass with the WFPC2 centroid provides a consistent mass. Although we cannot provide a definite explanation for the dark peak, we discuss a revised scenario, wherein dark matter with a more conventional range (σDM/m DM < 1 cm2 g–1) of self-interacting cross-section can lead to the detection of this dark substructure. If supported by detailed numerical simulations, this hypothesis opens up the possibility that the A520 system can be used to establish a lower limit of the self-interacting cross-section of dark matter.
79 citations
08 Sep 2018
TL;DR: In this article, a deep learning architecture for 3D semantic segmentation of unstructured point clouds is presented, where point neighborhoods are defined in the initial world space and the learned feature space.
Abstract: In this paper, we present a deep learning architecture which addresses the problem of 3D semantic segmentation of unstructured point clouds (Fig. 1). Compared to previous work, we introduce grouping techniques which define point neighborhoods in the initial world space and the learned feature space. Neighborhoods are important as they allow to compute local or global point features depending on the spatial extend of the neighborhood. Additionally, we incorporate dedicated loss functions to further structure the learned point feature space: the pairwise distance loss and the centroid loss. We show how to apply these mechanisms to the task of 3D semantic segmentation of point clouds and report state-of-the-art performance on indoor and outdoor datasets.
78 citations
TL;DR: In this paper, the location of the image centroid of Sgr A* should depend on observing frequency because of relativistic and radiative transfer effects, and the same effects introduce a generic dependence of the source polarization on frequency.
Abstract: The inferred black hole in the Galactic center spans the largest angle on the sky among all known black holes. Forthcoming observational programs plan to localize or potentially resolve the image of Sgr A* to an exquisite precision, comparable to the scale of the black hole horizon. Here we show that the location of the image centroid of Sgr A* should depend on observing frequency because of relativistic and radiative transfer effects. The same effects introduce a generic dependence of the source polarization on frequency. Future detection of the predicted centroid shift and the polarization dependence on frequency can be used to determine the unknown black hole spin and verify the validity of General Relativity.
78 citations
TL;DR: In this article, an efficient video-based multi-frame particle displacement tracking technique is presented on a thermocapillary flow and the Cramer-Rao lower bound centroid measurement uncertainty is derived for Gaussian particle images with Poisson noise recorded on a CCD array.
Abstract: An efficient video based, multi-frame particle displacement tracking technique is presented. The technique is demonstrated on a thermocapillary flow. The Cramer-Rao lower bound centroid measurement uncertainty is derived for Gaussian particle images with Poisson noise recorded on a CCD array. The optimal particle image diameter is determined to be approximately 11/2 pixels. The centroid error increases for particle image diameters larger or smaller than the optimal value. The particle centroid results are carried over to the case of a cross-correlation peak centroid estimate. Particle tracking techniques are shown to have higher accuracy than auto or cross-correlation techniques when the individual velocity measurements are averaged over a comparable correlation subregion.
78 citations
TL;DR: The approach is to obtain the congruent transformations which make the transformed image a good match with the original image, and the directional correlation of edge features is used to evaluate how well the original and transformed images match.
77 citations