Nonlinear interactions between high-Q optical and acoustic modes in dielectric particles

The interaction between acoustic breathing modes and optical Mie resonances in a spherical particle made of a chalcogenide glass material is investigated by means of rigorous calculations, correct to any order in the acousto-optic coupling parameter. Our results reveal the occurrence of strong effects beyond the linear-response approximation, which lead to enhanced modulation of light by acoustic waves through multiphonon exchange mechanisms when both photons and phonons have a very long lifetime inside the particle

Melting of genomic DNA: predictive modeling by nonlinear lattice dynamics

The melting behavior of long, heterogeneous DNA chains is examined within the framework of the nonlinear lattice dynamics based Peyrard-Bishop-Dauxois (PBD) model. Data for the pBR322 plasmid and the complete T7 phage have been used to obtain model fits and determine parameter dependence on salt content. Melting curves predicted for the complete fd phage and the Y1 and Y2 fragments of the $\phi$X174 phage without any adjustable parameters are in good agreement with experiment. The calculated probabilities for single base-pair opening are consistent with values obtained from imino proton exchange experiments.Comment: 5 pages, 4 figures, to appear in Phys. Rev.

Translating Videos to Commands for Robotic Manipulation with Deep Recurrent Neural Networks

We present a new method to translate videos to commands for robotic manipulation using Deep Recurrent Neural Networks (RNN). Our framework first extracts deep features from the input video frames with a deep Convolutional Neural Networks (CNN). Two RNN layers with an encoder-decoder architecture are then used to encode the visual features and sequentially generate the output words as the command. We demonstrate that the translation accuracy can be improved by allowing a smooth transaction between two RNN layers and using the state-of-the-art feature extractor. The experimental results on our new challenging dataset show that our approach outperforms recent methods by a fair margin. Furthermore, we combine the proposed translation module with the vision and planning system to let a robot perform various manipulation tasks. Finally, we demonstrate the effectiveness of our framework on a full-size humanoid robot WALK-MAN

Real-Time 6DOF Pose Relocalization for Event Cameras with Stacked Spatial LSTM Networks

We present a new method to relocalize the 6DOF pose of an event camera solely based on the event stream. Our method first creates the event image from a list of events that occurs in a very short time interval, then a Stacked Spatial LSTM Network (SP-LSTM) is used to learn the camera pose. Our SP-LSTM is composed of a CNN to learn deep features from the event images and a stack of LSTM to learn spatial dependencies in the image feature space. We show that the spatial dependency plays an important role in the relocalization task and the SP-LSTM can effectively learn this information. The experimental results on a publicly available dataset show that our approach generalizes well and outperforms recent methods by a substantial margin. Overall, our proposed method reduces by approx. 6 times the position error and 3 times the orientation error compared to the current state of the art. The source code and trained models will be released.Comment: 7 pages, 5 figure

Self trapping transition for a nonlinear impurity within a linear chain

In the present work we revisit the issue of the self-trapping dynamical transition at a nonlinear impurity embedded in an otherwise linear lattice. For our Schr\"odinger chain example, we present rigorous arguments that establish necessary conditions and corresponding parametric bounds for the transition between linear decay and nonlinear persistence of a defect mode. The proofs combine a contraction mapping approach applied in the fully dynamical problem in the case of a 3D-lattice, together with variational arguments for the derivation of parametric bounds for the creation of stationary states associated with the expected fate of the self-trapping dynamical transition. The results are relevant for both power law nonlinearities and saturable ones. The analytical results are corroborated by numerical computations.Comment: 16 pages, 7 figures. To be published in Journal of Mathematical Physic

Validity of the Gor'kov expansion near the upper critical field in type II superconductors

We have examined the validity of the Gor'kov expansion in the strength of the order parameter of type II superconductors near the upper critical field. Although the degeneracy of the electron levels in a magnetic field gives non- perturbative terms in the solution to the Bogoliubov-de Gennes equations we find, contrary to recent claims, that these non-perturbative terms cancel in the expression for the thermodynamic potential, and that the traditional Gor'kov theory is correct sufficiently close to Hc2 at finite temperature. We have derived conditions for the validity of the Gor'kov theory which essentially state, that the change in the quasiparticle energies as compared to the normal state energies cannot be too large compared to the temperature.Comment: 5 pages, 3 figures. One reference adde