23,206 research outputs found
Anisotropic collisions of dipolar Bose-Einstein condensates in the universal regime
We report the measurement of collisions between two Bose-Einstein condensates
with strong dipolar interactions. The collision velocity is significantly
larger than the internal velocity distribution widths of the individual
condensates, and thus, with the condensates being sufficiently dilute, a halo
corresponding to the two-body differential scattering cross section is
observed. The results demonstrate a novel regime of quantum scattering,
relevant to dipolar interactions, in which a large number of angular momentum
states become coupled during the collision. We perform Monte-Carlo simulations
to provide a detailed comparison between theoretical two-body cross sections
and the experimental observations.Comment: 10 pages, 5 figure
Uniform tail asymptotics for the stochastic present value of aggregate claims in the renewal risk model
Consider an insurer who is allowed to make risk-free and risky investments. The price process of the investment portfolio is described as a geometric Lévy process. We study the tail probability of the stochastic present value of future aggregate claims. When the claim-size distribution is of Pareto type, we obtain a simple asymptotic formula which holds uniformly for all time horizons. The same asymptotic formula holds for the finite-time and infinite-time ruin probabilities. Restricting our attention to the so-called constant investment strategy, we show how the insurer adjusts his investment portfolio to maximize the expected terminal wealth subject to a constraint on the ruin probability. © 2009 Elsevier B.V. All rights reserved.postprin
Superconducting correlations in ultra-small metallic grains
To describe the crossover from the bulk BCS superconductivity to a
fluctuation-dominated regime in ultrasmall metallic grains, new order
parameters and correlation functions, such as ``parity gap'' and ``pair-mixing
correlation function'', have been recently introduced. In this paper, we
discuss the small-grain behaviour of the Penrose-Onsager-Yang off-diagonal
long-range order (ODLRO) parameter in a pseudo-spin representation. Relations
between the ODLRO parameter and those mentioned above are established through
analytical and numerical calculations.Comment: 7 pages, 1 figur
Learning to Dress {3D} People in Generative Clothing
Three-dimensional human body models are widely used in the analysis of human
pose and motion. Existing models, however, are learned from minimally-clothed
3D scans and thus do not generalize to the complexity of dressed people in
common images and videos. Additionally, current models lack the expressive
power needed to represent the complex non-linear geometry of pose-dependent
clothing shapes. To address this, we learn a generative 3D mesh model of
clothed people from 3D scans with varying pose and clothing. Specifically, we
train a conditional Mesh-VAE-GAN to learn the clothing deformation from the
SMPL body model, making clothing an additional term in SMPL. Our model is
conditioned on both pose and clothing type, giving the ability to draw samples
of clothing to dress different body shapes in a variety of styles and poses. To
preserve wrinkle detail, our Mesh-VAE-GAN extends patchwise discriminators to
3D meshes. Our model, named CAPE, represents global shape and fine local
structure, effectively extending the SMPL body model to clothing. To our
knowledge, this is the first generative model that directly dresses 3D human
body meshes and generalizes to different poses. The model, code and data are
available for research purposes at https://cape.is.tue.mpg.de.Comment: CVPR-2020 camera ready. Code and data are available at
https://cape.is.tue.mpg.d
Anisotropic expansion of a thermal dipolar Bose gas
We report on the anisotropic expansion of ultracold bosonic dysprosium gases
at temperatures above quantum degeneracy and develop a quantitative theory to
describe this behavior. The theory expresses the post-expansion aspect ratio in
terms of temperature and microscopic collisional properties by incorporating
Hartree-Fock mean-field interactions, hydrodynamic effects, and
Bose-enhancement factors. Our results extend the utility of expansion imaging
by providing accurate thermometry for dipolar thermal Bose gases, reducing
error in expansion thermometry from tens of percent to only a few percent.
Furthermore, we present a simple method to determine scattering lengths in
dipolar gases, including near a Feshbach resonance, through observation of
thermal gas expansion.Comment: main text and supplement, 11 pages total, 4 figure
Multi-View Label Prediction for Unsupervised Learning Person Re-Identification
Person re-identification (ReID) aims to match pedestrian images across disjoint cameras. Existing supervised ReID methods utilize deep networks and train them with identity-labeled images, which suffer from limited annotations. Recently, clustering-based unsupervised ReID attracts more and more attention. It first clusters unlabeled images and assigns cluster index to the pseudo-identity-labels, then trains a ReID model with the pseudo-identity-labels. However, considering the slight inter-class variations and significant intra-class variations, pseudo-identity-labels learned from clustering algorithms are usually noisy and coarse. To alleviate the problems above, besides clustering pseudo-identity-labels, we propose to learn pseudo-patch-labels, which brings two advantages: (1) Patch naturally alleviates the effect of backgrounds, occlusions, and carryings since they usually occupy small parts in images, thus overcome noisy labels. (2) It is plausible that patches from different pedestrians belong to the same pseudo-identity-label. For example, pedestrians have a high probability of wearing either the same shoes or pants but a low possibility of wearing both. The experiments demonstrate our proposed method achieves the best performance by a large margin on both image- and video-based datasets
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