相关论文: HIKER: a halo-finding method based on kernel-shift…

We describe a new Python-based stand-alone halo finding algorithm, Haskap Pie, that combines several methods of halo finding and tracking into a single calculation. Our halo-finder flexibly solves halos for simulations produced by eight…

Examining the properties of subhalos with strong gravitational lensing images can shed light on the nature of dark matter. From upcoming large-scale surveys, we expect to discover orders of magnitude more strong lens systems that can be…

Cosmological simulations are an important method for investigating the evolution of the Universe. In order to gain further insight into the processes of structure formation, it is necessary to identify isolated bound objects within the…

Although numerous dynamical techniques have been developed to estimate the total dark matter halo mass of the Milky Way, it remains poorly constrained, with typical systematic uncertainties of 0.3 dex. In this study, we apply a neural…

We study a simple model of dark matter that is gravitationally clustered around the sun in the form of a spherical halo of a degenerate gas of heavy neutrinos. It is shown that for neutrino masses $m_{\nu} \stackrel {\textstyle <}{\sim}…

We present a generalization of our recently proposed machine learning framework, aiming to provide new physical insights into dark matter halo formation. We investigate the impact of the initial density and tidal shear fields on the…

We use a set of large cosmological N-body simulations to study the internal structure of dark matter haloes which form in scale-free models. We find that the radius r_178 corresponding to a mean interior overdensity of 178 accurately…

In a previous paper, we described a new method for including detailed information about substructure in semi-analytic models of halo formation based on merger trees. In this paper, we compare the predictions of our model with results from…

We study the reliability of dark-matter halo detections with three different linear filters applied to weak-lensing data. We use ray-tracing in the multiple lens-plane approximation through a large cosmological simulation to construct…

We introduce a new method to calculate dark matter halo density profiles from simulations. Each particle is 'smeared' over its orbit to obtain a dynamical profile that is averaged over a dynamical time, in contrast to the traditional…

Multiresolution analysis is applied to the problem of halo identification in cosmological N-body simulations. The procedure makes use of a discrete wavelet transform known as the algorithme a trous and segmentation analysis. It has the…

We describe our new "MLAPM-halo-finder" (MHF) which is based on the adaptive grid structure of the N-body code MLAPM. We then extend the MHF code in order to track the orbital evolution of gravitationally bound objects through any given…

We study the ability of the Hyper-Kamiokande (HyperK) experiment, currently under construction, to constrain a neutrino signal produced via the annihilation of dark matter captured in the Sun. We simulate upward stopping and upward…

Generative deep learning methods built upon Convolutional Neural Networks (CNNs) provide a great tool for predicting non-linear structure in cosmology. In this work we predict high resolution dark matter halos from large scale, low…

This paper presents a kernel formulation of the recently introduced diff-hash algorithm for the construction of similarity-sensitive hash functions. Our kernel diff-hash algorithm that shows superior performance on the problem of image…

We present a new algorithm for detecting filamentary structure FilFinder. The algorithm uses the techniques of mathematical morphology for filament identification, presenting a complementary approach to current algorithms which use matched…

A major question in $\Lambda$CDM is what this theory actually predicts for the properties of subhalo populations. Subhalos are difficult to simulate and to find within simulations, and this propagates into uncertainty in theoretical…

We investigate the possibility of applying machine learning techniques to images of strongly lensed galaxies to detect a low mass cut-off in the spectrum of dark matter sub-halos within the lens system. We generate lensed images of systems…

In two previous papers (Salvador-Sol\'e 2012a,b), it was shown that: i) the typical structural and kinematic properties of haloes in (bottom-up) hierarchical cosmologies endowed with random Gaussian density perturbations of dissipationless…

Cosmological structure formation predicts that our galactic halo contains an enormous hierarchy of substructures and streams, the remnants of the merging hierarchy that began with tiny Earth mass microhalos. If these structures persist…