相关论文: Cluster dynamics studied with the phase-space Mini…
Low-dimensional representation and clustering of network data are tasks of great interest across various fields. Latent position models are routinely used for this purpose by assuming that each node has a location in a low-dimensional…
This paper proposes a stable sparse rapidly-exploring random trees (SST) algorithm to solve the optimal motion planning problem for hybrid systems. At each iteration, the proposed algorithm, called HySST, selects a vertex with the lowest…
Important efforts have been dedicated in the past few years to describe near-barrier heavy-ion collisions with microscopic quantum theories like the time-dependent Hartree-Fock approach and some of its extensions. However, this field is…
Clustering under most popular objective functions is NP-hard, even to approximate well, and so unlikely to be efficiently solvable in the worst case. Recently, Bilu and Linial \cite{Bilu09} suggested an approach aimed at bypassing this…
We present results of N-body/gasdynamical simulations designed to investigate the evolution of X-ray clusters in a flat, low-density, cold dark matter (CDM) cosmogony. The density profile of the dark matter component can be fitted rather…
Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) and other rare-event physics searches, like dark matter detection, have been especially furthered by increasing sensitivity to low-energy particle interactions. Experiments using…
We study the clustering properties of galaxy clusters expected to be observed by various forthcoming surveys both in the X-ray and sub-mm regimes by the thermal Sunyaev-Zel'dovich effect. Several different background cosmological models are…
Identifying mobility behaviors in rich trajectory data is of great economic and social interest to various applications including urban planning, marketing and intelligence. Existing work on trajectory clustering often relies on similarity…
We use hydrodynamical/N-body simulations to interpret the newly discovered Bullet-cluster-like merging cluster, ZwCl 0008.8+5215 (ZwCl 0008 hereafter), where a dramatic collision is apparent from multi-wavelength observations. We have been…
We present a new algorithm to identify fragments in computer simulations of relativistic heavy ion collisions. It is based on the simulated annealing technique and can be applied to n-body transport models like the Quantum Molecular…
We analyze the physical properties of stellar clusters that are detected in massive star-forming regions in the MYStIX project--a comparative, multiwavelength study of young stellar clusters within 3.6 kpc that contain at least one O-type…
To assess the degree of equilibration of the matter created in heavy-ion reactions at low to intermediate beam energies, a hadronic transport approach (SMASH) is employed. By using a coarse-graining method, we compute the energy momentum…
The one-dimensional Hubbard model is investigated by means of two different cluster schemes suited to introduce short-range spatial correlations beyond the single-site Dynamical Mean-Field Theory, namely the Cluster-Dynamical Mean-Field…
We numerically investigate slow dynamics of a binary mixture of ultrasoft particles interacting with the generalized Hertzian potential. If the softness parameter, $\alpha$, is small, the particles at high densities start penetrating each…
We present a non-perturbative framework for deriving effective Hamiltonians that describe low-energy excitations in quantum many-body systems. The method combines block diagonalization based on the Cederbaum--Schirmer--Meyer transformation…
In certain naturally aged aluminum alloys, significant strengthening can be obtained due to the decomposition of a super-saturated solid solution into clusters. The origins of such strengthening remain unclear due to the challenge of…
Understanding the substructure of atomic nuclei, particularly the clustering of nucleons inside them, is essential for comprehending nuclear dynamics. Various cluster configurations can emerge depending on excitation energy, the number and…
Subspace clustering refers to the problem of clustering high-dimensional data points into a union of low-dimensional linear subspaces, where the number of subspaces, their dimensions and orientations are all unknown. In this paper, we…
Finding a minimum spanning tree (MST) for $n$ points in an arbitrary metric space is a fundamental primitive for hierarchical clustering and many other ML tasks, but this takes $\Omega(n^2)$ time to even approximate. We introduce a…
Structural health monitoring (SHM) relies on non-destructive techniques such as acoustic emission (AE) that generate large amounts of data over the lifespan of systems. Clustering methods are used to interpret these data and gain insights…