Excess Electron Relaxation Dynamics at Water/Air Interfaces

We have performed mixed quantum-classical molecular dynamics simulations of the relaxation of a ground state excess electron at interfaces of different phases of water with air. The investigated systems included ambient water/air, supercooled water/air, Ih ice/air and an amorphous solid water/air interfaces. The present work explores the possible connections of the examined interfacial systems to finite size cluster anions, and the three-dimensional infinite, fully hydrated electron. Localization site analyses indicate that in the absence of nuclear relaxation the electron localizes in a shallow potential trap on the interface in all examined systems in a diffuse, surface-bound (SB) state. With relaxation, the weakly bound electron undergoes an ultrafast localization and stabilization on the surface with the concomitant collapse of its radius. In the case of the ambient liquid interface the electron slowly (on the 10 ps timescale) diffuses into the bulk to form an interior-bound (IB) state. In each other case, the excess electron persists on the interface in surface-bound (SB) states. The relaxation dynamics occur through distinct SB structures which are easily distinguishable by their energetics, geometries, and interactions with the surrounding water bath. The systems exhibiting the most stable SB excess electron states (supercooled water/air and Ih ice/air interfaces) are identified by their characteristic hydrogen-bonding motifs which are found to contain double acceptor type water molecules in the close vicinity of the electron. These surface states correlate reasonably with those extrapolated to infinite size from simulated water cluster anions

Excess Electron Localization Sites in Neutral Water Clusters

We present approximate pseudopotential quantum mechanical calculations of the excess electron states of equilibrated neutral water clusters sampled by classical molecular dynamics simulations. The internal energy of the clusters are representative of those present at temperatures of 200 K and 300 K. Correlated electronic structure calculations are used to validate the pseudopotential for this purpose. We find that the neutral clusters support localized, bound excess electron ground states in about 50 % of the configurations for the smallest cluster size studied (n=20), and in almost all configurations for larger clusters (n>66). The state is always exterior to the molecular frame, forming typically a diffuse surface state. Both cluster size and temperature dependence of energetic and structural properties of the clusters and the electron distribution are explored. We show that the stabilization of the electron is strongly correlated with the pre-existing instantaneous dipole moment of the neutral clusters, and its ground state energy is reflected in the electronic radius. The findings are consistent with electron attachment via an initial surface state. The hypothetical spectral dynamics following such attachment is also discussed

Enhancing Perceptual Attributes with Bayesian Style Generation

Deep learning has brought an unprecedented progress in computer vision and significant advances have been made in predicting subjective properties inherent to visual data (e.g., memorability, aesthetic quality, evoked emotions, etc.). Recently, some research works have even proposed deep learning approaches to modify images such as to appropriately alter these properties. Following this research line, this paper introduces a novel deep learning framework for synthesizing images in order to enhance a predefined perceptual attribute. Our approach takes as input a natural image and exploits recent models for deep style transfer and generative adversarial networks to change its style in order to modify a specific high-level attribute. Differently from previous works focusing on enhancing a specific property of a visual content, we propose a general framework and demonstrate its effectiveness in two use cases, i.e. increasing image memorability and generating scary pictures. We evaluate the proposed approach on publicly available benchmarks, demonstrating its advantages over state of the art methods.Comment: ACCV-201

Interior- and Surface-Bound Excess Electron States in Large Water Cluster Anions

We present the results of mixed quantum/classical simulations on relaxed thermal nanoscale water cluster anions,(H_2O)^-_n, with n=200, 500, 1000 and 8000. By using initial equilibration with constraints, we investigate stable/metastable negatively charged water clusters with both surface-bound and interior-bound excess electron states. Characterization of these states is performed in terms of geometrical parameters, energetics, and optical absorption spectroscopy of the clusters. The calculations provide data characterizing these states in the gap between previously published calculations, and experiments, on smaller clusters and the limiting cases of either an excess electron in bulk water, or an excess electron at an infinite water/air interface. The present results are in general agreement with previous simulations and provide a consistent picture of the evolution of the physical properties of water cluster anions with size over the entire size range, including results for vertical detachment energies and absorption spectra that would signify their presence. In particular, the difference in size dependence between surface-bound and interior-bound state absorption spectra is dramatic, while for detachment energies the dependence is qualitatively the same

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid over-fitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian matrix factorization algorithm using stochastic gradient MCMC. Our algorithm, based on Distributed Stochastic Gradient Langevin Dynamics, can not only match the prediction accuracy of standard MCMC methods like Gibbs sampling, but at the same time is as fast and simple as stochastic gradient descent. In our experiments, we show that our algorithm can achieve the same level of prediction accuracy as Gibbs sampling an order of magnitude faster. We also show that our method reduces the prediction error as fast as distributed stochastic gradient descent, achieving a 4.1% improvement in RMSE for the Netflix dataset and an 1.8% for the Yahoo music dataset

The Kramers equation simulation algorithm I. Operator analysis

Using an operatorial formalism, we study the Kramers equation and its applications to numerical simulations. We obtain classes of algorithms which may be made precise at every desired order in the time step $\epsilon$ and with a set of free parameters which can be used to reduce autocorrelations. We show that it is possible to use a global Metropolis test to restore Detailed Balance.Comment: 32 pages, REVTeX 3.0, IFUP-TH-2

Relationship between quantum decoherence times and solvation dynamics in condensed phase chemical systems

A relationship between the time scales of quantum coherence loss and short-time solvent response for a solute/bath system is derived for a Gaussian wave packet approximation for the bath. Decoherence and solvent response times are shown to be directly proportional to each other, with the proportionality coefficient given by the ratio of the thermal energy fluctuations to the fluctuations in the system-bath coupling. The relationship allows the prediction of decoherence times for condensed phase chemical systems from well developed experimental methods.Comment: 10 pages, no figures, late

Mixing Quantum and Classical Mechanics

Using a group theoretical approach we derive an equation of motion for a mixed quantum-classical system. The quantum-classical bracket entering the equation preserves the Lie algebra structure of quantum and classical mechanics: The bracket is antisymmetric and satisfies the Jacobi identity, and, therefore, leads to a natural description of interaction between quantum and classical degrees of freedom. We apply the formalism to coupled quantum and classical oscillators and show how various approximations, such as the mean-field and the multiconfiguration mean-field approaches, can be obtained from the quantum-classical equation of motion.Comment: 31 pages, LaTeX2