Observation of Dynamical Super Efimovian Expansion in a Unitary Fermi Gas

We report an observation of a dynamical super Efimovian expansion in a two-component strongly interacting Fermi gas by engineering time dependent external harmonic trap frequencies. When trap frequency is followed as $[1/4t^2+1/t^2\lambda\log(t/t_*)]^{1/2}$, where $t_*$ and $\lambda$ are two control parameters, and the change is faster than a critical value, the expansion of such the quantum gas shows a novel dynamics due to its spatial and dynamical scaling symmetry. A clear double-log periodicity, which is a hallmark of the super Efimov effect, is emergent for the cloud size in the expansion. The universality of such scaling dynamics is verified both in the non-interacting limit and in the unitarity limit. Observing super-Efmovian evolution represents a paradigm in probing universal properties and allows in a new way to study many-body nonequilibrium dynamics with experiments.Comment: 5 pages+4 figure

High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference

We propose a data-driven method for recovering miss-ing parts of 3D shapes. Our method is based on a new deep learning architecture consisting of two sub-networks: a global structure inference network and a local geometry refinement network. The global structure inference network incorporates a long short-term memorized context fusion module (LSTM-CF) that infers the global structure of the shape based on multi-view depth information provided as part of the input. It also includes a 3D fully convolutional (3DFCN) module that further enriches the global structure representation according to volumetric information in the input. Under the guidance of the global structure network, the local geometry refinement network takes as input lo-cal 3D patches around missing regions, and progressively produces a high-resolution, complete surface through a volumetric encoder-decoder architecture. Our method jointly trains the global structure inference and local geometry refinement networks in an end-to-end manner. We perform qualitative and quantitative evaluations on six object categories, demonstrating that our method outperforms existing state-of-the-art work on shape completion.Comment: 8 pages paper, 11 pages supplementary material, ICCV spotlight pape

Planning of Cellular Networks Enhanced by Energy Harvesting

We pose a novel cellular network planning problem, considering the use of renewable energy sources and a fundamentally new concept of energy balancing, and propose a novel algorithm to solve it. In terms of the network capital and operational expenditure, we conclude that savings can be made by enriching cellular infrastructure with energy harvesting sources, in comparison to traditional deployment methods.Comment: accepted to IEEE Communications Letters [source code available