Electronic charges and electric potential at LaAlO3/SrTiO3 interfaces studied by core-level photoemission spectroscopy

We studied LaAlO3/SrTiO3 interfaces for varying LaAlO3 thickness by core-level photoemission spectroscopy. In Ti 2p spectra for conducting "n-type" interfaces, Ti3+ signals appeared, which were absent for insulating "p-type" interfaces. The Ti3+ signals increased with LaAlO3 thickness, but started well below the critical thickness of 4 unit cells for metallic transport. Core-level shifts with LaAlO3 thickness were much smaller than predicted by the polar catastrophe model. We attribute these observations to surface defects/adsorbates providing charges to the interface even below the critical thickness

Catastrophic eruption of magnetic flux rope in the corona and solar wind with and without magnetic reconnection

It is generally believed that the magnetic free energy accumulated in the corona serves as a main energy source for solar explosions such as coronal mass ejections (CMEs). In the framework of the flux rope catastrophe model for CMEs, the energy may be abruptly released either by an ideal magnetohydrodynamic (MHD) catastrophe, which belongs to a global magnetic topological instability of the system, or by a fast magnetic reconnection across preexisting or rapidly-developing electric current sheets. Both ways of magnetic energy release are thought to be important to CME dynamics. To disentangle their contributions, we construct a flux rope catastrophe model in the corona and solar wind and compare different cases in which we either prohibit or allow magnetic reconnection to take place across rapidly-growing current sheets during the eruption. It is demonstrated that CMEs, even fast ones, can be produced taking the ideal MHD catastrophe as the only process of magnetic energy release. Nevertheless, the eruptive speed can be significantly enhanced after magnetic reconnection sets in. In addition, a smooth transition from slow to fast eruptions is observed when increasing the strength of the background magnetic field, simply because in a stronger field there is more free magnetic energy at the catastrophic point available to be released during an eruption. This suggests that fast and slow CMEs may have an identical driving mechanism.Comment: 7 pages, 4 figures, ApJ, in press (vol. 666, Sept. 2007

The application of componentised modelling techniques to catastrophe model generation

In this paper we show that integrated environmental modelling (IEM) techniques can be used to generate a catastrophe model for groundwater flooding. Catastrophe models are probabilistic models based upon sets of events representing the hazard and weights their likelihood with the impact of such an event happening which is then used to estimate future financial losses. These probabilistic loss estimates often underpin re-insurance transactions. Modelled loss estimates can vary significantly, because of the assumptions used within the models. A rudimentary insurance-style catastrophe model for groundwater flooding has been created by linking seven individual components together. Each component is linked to the next using an open modelling framework (i.e. an implementation of OpenMI). Finally, we discuss how a flexible model integration methodology, such as described in this paper, facilitates a better understanding of the assumptions used within the catastrophe model by enabling the interchange of model components created using different, yet appropriate, assumptions

Analysis of intellectual property cooperation behavior based on stochastic catastrophe theory and the QSIM algorithm

This article introduces a new model, the catastrophe model of intellectual property cooperation behavior. The purpose of the model is to analyze the evolutionary track of intellectual property cooperation behavior. After providing a general of catastrophe mechanism of intellectual property cooperation behavior and introducing stochastic catastrophe theory, this article offers a catastrophe model of intellectual property cooperation behavior. And then, based on the survey data of high-tech enterprises, the model parameters were given by introducing the qualitative simulation algorithm. The results demonstrate that intellectual property cooperation is composed of a cooperation strategic planning stage, cooperation system formation stage, cooperation system working stage, and cooperation profit distribution stage. Under the influence of control variables, the intellectual property cooperation behavior will appear catastrophic near the set of bifurcation points. Most previous studies on intellectual property cooperation have disregarded the characteristic of the sudden changes in cooperation behavior. Therefore, this article offers an integrated catastrophe model and explains the nature of intellectual property cooperation behavior

Realizing stock market crashes: stochastic cusp catastrophe model of returns under the time-varying volatility

This paper develops a two-step estimation methodology, which allows us to apply catastrophe theory to stock market returns with time-varying volatility and model stock market crashes. Utilizing high frequency data, we estimate the daily realized volatility from the returns in the first step and use stochastic cusp catastrophe on data normalized by the estimated volatility in the second step to study possible discontinuities in markets. We support our methodology by simulations where we also discuss the importance of stochastic noise and volatility in deterministic cusp catastrophe model. The methodology is empirically tested on almost 27 years of U.S. stock market evolution covering several important recessions and crisis periods. Due to the very long sample period we also develop a rolling estimation approach and we find that while in the first half of the period stock markets showed marks of bifurcations, in the second half catastrophe theory was not able to confirm this behavior. Results suggest that the proposed methodology provides an important shift in application of catastrophe theory to stock markets

Bayesian Inference for Stochastic Cusp Catastrophe Model

In modern financial econometrics, diffusion processes have been broadly used to model the stochastic behavior of economic variables such as stock prices, interest rates, and exchange rates. Well-known models such as Black-Scholes, Vasicek, and Cox-Ingersoll-Ross (CIR mdoel), all assume that the underlying state variables follow diffusion processes. If one believes that the observed time-series are generated according to some parametric specification, developing rigorous statistical methods to calibrate the underlying model to measured observations has become a considerable subject of the field. The thesis considers cusp model, one of the elementary catastrophe models studied in catastrophe theory. The research problem of this thesis is to develop an accurate and computationally feasible parameter estimation algorithm based on Bayesian principle that can be implemented in absence of an exact transition distribution for cusp model using discretely sampled observations. The problem can be further specified as parameter estimations using complete observations and using partial observations. Accuracy and efficiency of the approach are demonstrated and examined in a series of simulation-based studies that consist of both trajectory simulations and parameter estimations. We extend the developed algorithm and apply it to Bayesian hierarchical modeling and cusp model with time-varying parameters.Doctor of Philosoph