Phase space structures and ionization dynamics of hydrogen atom in elliptically polarized microwaves

The multiphoton ionization of hydrogen atoms in a strong elliptically polarized microwave field exhibits complex features that are not observed for ionization in circular and linear polarized fields. Experimental data reveal high sensitivity of ionization dynamics to the small changes of the field polarization. The multidimensional nature of the problem makes widely used diagnostics of dynamics, such as Poincar\'{e} surfaces of section, impractical. We analyze the phase space dynamics using finite time stability analysis rendered by the fast Lyapunov Indicators technique. The concept of zero--velocity surface is used to initialize the calculations and visualize the dynamics. Our analysis provides stability maps calculated for the initial energy at the maximum and below the saddle of the zero-velocity surface. We estimate qualitatively the dependence of ionization thresholds on the parameters of the applied field, such as polarization and scaled amplitude

Modeling of Small Sea Floaters in the Central Mediterranean Sea: Seasonality of At--Sea Distributions

Floating marine debris represent a threat to marine and coastal ecology. Since the Mediterranean basin is one of the highly impacted regions, both by the coastal pollution as well as from sea traffic, the potential harm of a floating pollution on the marine ecology could be overwhelming in this area. Our study area covers the central Mediterranean crossing that connects the western and eastern Mediterranean and is one of the areas impacted by a high intensity of sea traffic. To identify regions in the central Mediterranean that could be more exposed by high concentration of floating marine pollutants we use Leeway model for lower windage small-size particles. We perform numerical simulation of a large ensemble of Lagrangian particles that approximate at-sea debris. The particles are forced by high-resolution sea kinematics from the Copernicus Marine Environment Monitoring Service (CMEMS) and 10 m atmospheric wind from the European Centre for Medium-Range Weather Forecasts (ECMWF) for two reference periods in summer and winter of 2013-2016. We identify the regions with a high accumulation of particles in terms of particle surface densities per unit area. Although seasonal and annual variability of ocean current and atmospheric wind is an important factor that influences accumulation regimes across the central Mediterranean, we found that the border of the Libyan shelf harbors larger percentage of particles after 30 days of simulation.

Effect of periodic parametric excitation on an ensemble of force-coupled self-oscillators

We report the synchronization behavior in a one-dimensional chain of identical limit cycle oscillators coupled to a mass-spring load via a force relation. We consider the effect of periodic parametric modulation on the final synchronization states of the system. Two types of external parametric excitations are investigated numerically: periodic modulation of the stiffness of the inertial oscillator and periodic excitation of the frequency of the self-oscillatory element. We show that the synchronization scenarios are ruled not only by the choice of parameters of the excitation force but depend on the initial collective state in the ensemble. We give detailed analysis of entrainment behavior for initially homogeneous and inhomogeneous states. Among other results, we describe a regime of partial synchronization. This regime is characterized by the frequency of collective oscillation being entrained to the stimulation frequency but different from the average individual oscillators frequency.Comment: Comments and suggestions are welcom

Anticipating Recessions using Inclination Analysis

Recessions are economic downturns that can be recognized from macro-indicators such as the Dow Jones Industrial Average (DJIA) and the Federal Reserve Interest Rate (FRIR). To provide early-warning signals of recessions and similar systemic transitions, here we propose a new approach based on pattern recognition, called inclination analysis [1, 2]. For this purpose, we develop a stochastic model based on time-series analysis to assess the probability of a recession to occur at a given moment in the past, present, or future. Calibrating our model to data proceeds in three steps, involving the coarse-graining of the available input time series, the identification of short series motifs that foreshadow recessions, and the optimization of key model parameters according to the model’s desired forecasting horizon

A new search-and-rescue service in the Mediterranean Sea: a demonstration of the operational capability and an evaluation of its performance using real case scenarios

Abstract. A new web-based and mobile decision support system (DSS) for search-and-rescue (SAR) at sea is presented, and its performance is evaluated using real case scenarios. The system, named OCEAN-SAR, is accessible via the website http://www.ocean-sar.com. In addition to the website, dedicated applications for iOS and Android have been created to optimise the user experience on mobile devices. OCEAN-SAR simulates drifting objects at sea, using as input ocean currents and wind data provided, respectively, by the CMEMS and ECMWF. The modelling of the drifting objects is based on the leeway model, which parameterises the wind drag of an object using a series of coefficients. These coefficients have been measured in field experiments for different types of objects, ranging from a person in the water to a coastal freighter adrift. OCEAN-SAR provides the user with an intuitive interface to run simulations and to visualise their results using Google Maps. The performance of the service is evaluated by comparing simulations to data from the Italian Coast Guard pertaining to actual incidents in the Mediterranean Sea

When does a disaster become a systemic event? Estimating indirect economic losses from natural disasters

Reliable estimates of indirect economic losses arising from natural disasters are currently out of scientific reach. To address this problem, we propose a novel approach that combines a probabilistic physical damage catastrophe model with a new generation of macroeconomic agent-based models (ABMs). The ABM moves beyond the state of the art by exploiting large data sets from detailed national accounts, census data, and business information, etc., to simulate interactions of millions of agents representing \emph{each} natural person or legal entity in a national economy. The catastrophe model introduces a copula approach to assess flood losses, considering spatial dependencies of the flood hazard. These loss estimates are used in a damage scenario generator that provides input for the ABM, which then estimates indirect economic losses due to the event. For the first time, we are able to link environmental and economic processes in a computer simulation at this level of detail. We show that moderate disasters induce comparably small but positive short- to medium-term, and negative long-term economic impacts. Large-scale events, however, trigger a pronounced negative economic response immediately after the event and in the long term, while exhibiting a temporary short- to medium-term economic boost. We identify winners and losers in different economic sectors, including the fiscal consequences for the government. We quantify the critical disaster size beyond which the resilience of an economy to rebuild reaches its limits. Our results might be relevant for the management of the consequences of systemic events due to climate change and other disasters

Phase Coherence Analysis of Insect Flight

This paper has been withdrawn by the author due to a errors in figure 3,4Comment: This paper has been withdraw