Ultrafast electron dynamics at metal surfaces: Competition between electron-phonon coupling and hot-electron transport

An experimental scheme (double pump/reflectivity probe using femtosecond laser pulses) enables the investigation of nonequilibrium electron dynamics at metal surfaces by measuring the equilibrated surface temperature. The competition between electron-phonon coupling and hot-electron transport gives rise to a reduced equilibrated temperature when the two pump pulses overlap in time, and provides a way of accurately determining the electron-phonon coupling constant. These observations have important consequences for femtosecond photochemical investigations

PRECISE 3D MEASUREMENT WITH STANDARD MEANS AND MINIMIAL USER INTERACTION - EXTENDED SINGLE-VIEW RECONSTRUCTION

The paper proposes a new method for general 3D measurement and 3D point reconstruction. Looking at its features, the method explicitly aims at practical applications. These features especially cover low technical expenses and minimal user interaction, a clear problem separation into steps that are solved by simple mathematical methods (direct, stable and optimal with respect to least error squares), and scalability. The method expects the internal and radial distortion parameters of the used camera(s) as inputs, and a plane quadrangle with known geometry within the scene. At first, for each single picture the 3D position of the reference quadrangle (with respect to each camera coordinate frame) is calculated. These 3D reconstructions of the reference quadrangle are then used to yield the relative external parameters of each camera regarding the first one. With known external parameters, triangulation is finally possible. The differences from other known procedures are outlined, paying attention to the stable mathematical methods (no usage of nonlinear optimization) and the low user interaction with good results at the same time

On the Existence of Localized Excitations in Nonlinear Hamiltonian Lattices

We consider time-periodic nonlinear localized excitations (NLEs) on one-dimensional translationally invariant Hamiltonian lattices with arbitrary finite interaction range and arbitrary finite number of degrees of freedom per unit cell. We analyse a mapping of the Fourier coefficients of the NLE solution. NLEs correspond to homoclinic points in the phase space of this map. Using dimensionality properties of separatrix manifolds of the mapping we show the persistence of NLE solutions under perturbations of the system, provided NLEs exist for the given system. For a class of nonintegrable Fermi-Pasta-Ulam chains we rigorously prove the existence of NLE solutions.Comment: 13 pages, LaTeX, 2 figures will be mailed upon request (Phys. Rev. E, in press

Rate of Convergence to Barenblatt Profiles for the Fast Diffusion Equation

We study the asymptotic behaviour of positive solutions of the Cauchy problem for the fast diffusion equation near the extinction time. We find a continuum of rates of convergence to a self-similar profile. These rates depend explicitly on the spatial decay rates of initial data

Pitch determination considering laryngealization effects in spoken dialogs

A frequent phenomenon in spoken dialogs of the information seeking type are short elliptic utterances whose mood (declarative or interrogative) can only be distinguished by intonation. The main acoustic evidence is conveyed by the fundamental frequency or Fo-contour. Many algorithms for Fo determination have been reported in the literature. A common problem are irregularities of speech known as "laryngealizations". This article describes an approach based on neural network techniques for the improved determination of fundamental frequency. First, an improved version of our neural network algorithm for reconstruction of the voice source signal (glottis signal) is presented. Second, the reconstructed voice source signal is used as input to another neural network distinguishing the three classes "voiceless", "voiced non-laryngealized", and "voiced laryngealized". Third, the results are used to improve an existing Fo algorithm. Results of this approach are presented and discussed in the context of the application in a spoken dialog system

Active Perception using Light Curtains for Autonomous Driving

Most real-world 3D sensors such as LiDARs perform fixed scans of the entire environment, while being decoupled from the recognition system that processes the sensor data. In this work, we propose a method for 3D object recognition using light curtains, a resource-efficient controllable sensor that measures depth at user-specified locations in the environment. Crucially, we propose using prediction uncertainty of a deep learning based 3D point cloud detector to guide active perception. Given a neural network's uncertainty, we derive an optimization objective to place light curtains using the principle of maximizing information gain. Then, we develop a novel and efficient optimization algorithm to maximize this objective by encoding the physical constraints of the device into a constraint graph and optimizing with dynamic programming. We show how a 3D detector can be trained to detect objects in a scene by sequentially placing uncertainty-guided light curtains to successively improve detection accuracy. Code and details can be found on the project webpage: http://siddancha.github.io/projects/active-perception-light-curtains.Comment: Published at the European Conference on Computer Vision (ECCV), 202