12,983 research outputs found
Fermionization of a bosonic gas under highly-elongated confinement: A diffusion quantum Monte Carlo study
The diffusion quantum Monte Carlo technique is used to solve the many-body
Schroedinger equation fully quantum mechanically and nonperturbatively for
bosonic atomic gases in cigar-shaped confining potentials. By varying the
aspect ratio of the confining potential from 1 (spherical trap) to 10000
(highly elongated trap), we characterize the transition from the
three-dimensional regime to the (quasi-)one-dimensional regime. Our results
confirm that the bosonic gas undergoes ``fermionization'' for large aspect
ratios. Importantly, many-body correlations are included explicitly in our
approach.Comment: 10 pages, 8 figure
Local Kernels and the Geometric Structure of Data
We introduce a theory of local kernels, which generalize the kernels used in
the standard diffusion maps construction of nonparametric modeling. We prove
that evaluating a local kernel on a data set gives a discrete representation of
the generator of a continuous Markov process, which converges in the limit of
large data. We explicitly connect the drift and diffusion coefficients of the
process to the moments of the kernel. Moreover, when the kernel is symmetric,
the generator is the Laplace-Beltrami operator with respect to a geometry which
is influenced by the embedding geometry and the properties of the kernel. In
particular, this allows us to generate any Riemannian geometry by an
appropriate choice of local kernel. In this way, we continue a program of
Belkin, Niyogi, Coifman and others to reinterpret the current diverse
collection of kernel-based data analysis methods and place them in a geometric
framework. We show how to use this framework to design local kernels invariant
to various features of data. These data-driven local kernels can be used to
construct conformally invariant embeddings and reconstruct global
diffeomorphisms
Diffusion maps embedding and transition matrix analysis of the large-scale flow structure in turbulent Rayleigh--B\'enard convection
By utilizing diffusion maps embedding and transition matrix analysis we
investigate sparse temperature measurement time-series data from
Rayleigh--B\'enard convection experiments in a cylindrical container of aspect
ratio between its diameter () and height (). We consider
the two cases of a cylinder at rest and rotating around its cylinder axis. We
find that the relative amplitude of the large-scale circulation (LSC) and its
orientation inside the container at different points in time are associated to
prominent geometric features in the embedding space spanned by the two dominant
diffusion-maps eigenvectors. From this two-dimensional embedding we can measure
azimuthal drift and diffusion rates, as well as coherence times of the LSC. In
addition, we can distinguish from the data clearly the single roll state (SRS),
when a single roll extends through the whole cell, from the double roll state
(DRS), when two counter-rotating rolls are on top of each other. Based on this
embedding we also build a transition matrix (a discrete transfer operator),
whose eigenvectors and eigenvalues reveal typical time scales for the stability
of the SRS and DRS as well as for the azimuthal drift velocity of the flow
structures inside the cylinder. Thus, the combination of nonlinear dimension
reduction and dynamical systems tools enables to gain insight into turbulent
flows without relying on model assumptions
Koopman analysis of the long-term evolution in a turbulent convection cell
We analyse the long-time evolution of the three-dimensional flow in a closed
cubic turbulent Rayleigh-B\'{e}nard convection cell via a Koopman eigenfunction
analysis. A data-driven basis derived from diffusion kernels known in machine
learning is employed here to represent a regularized generator of the unitary
Koopman group in the sense of a Galerkin approximation. The resulting Koopman
eigenfunctions can be grouped into subsets in accordance with the discrete
symmetries in a cubic box. In particular, a projection of the velocity field
onto the first group of eigenfunctions reveals the four stable large-scale
circulation (LSC) states in the convection cell. We recapture the preferential
circulation rolls in diagonal corners and the short-term switching through roll
states parallel to the side faces which have also been seen in other
simulations and experiments. The diagonal macroscopic flow states can last as
long as a thousand convective free-fall time units. In addition, we find that
specific pairs of Koopman eigenfunctions in the secondary subset obey enhanced
oscillatory fluctuations for particular stable diagonal states of the LSC. The
corresponding velocity field structures, such as corner vortices and swirls in
the midplane, are also discussed via spatiotemporal reconstructions.Comment: 32 pages, 9 figures, article in press at Journal of Fluid Mechanic
The Local Structure of Space-Variant Images
Local image structure is widely used in theories of both machine and biological vision. The form of the differential operators describing this structure for space-invariant images has been well documented (e.g. Koenderink, 1984). Although space-variant coordinates are universally used in mammalian visual systems, the form of the operators in the space-variant domain has received little attention. In this report we derive the form of the most common differential operators and surface characteristics in the space-variant domain and show examples of their use. The operators include the Laplacian, the gradient and the divergence, as well as the fundamental forms of the image treated as a surface. We illustrate the use of these results by deriving the space-variant form of corner detection and image enhancement algorithms. The latter is shown to have interesting properties in the complex log domain, implicitly encoding a variable grid-size integration of the underlying PDE, allowing rapid enhancement of large scale peripheral features while preserving high spatial frequencies in the fovea.Office of Naval Research (N00014-95-I-0409
- …