Davide Vergni

Front propagation in laminar flows

The problem of front propagation in flowing media is addressed for laminar velocity fields in two dimensions. Three representative cases are discussed: stationary cellular flow, stationary shear flow, and percolating flow. Production terms of Fisher-Kolmogorov-Petrovskii-Piskunov type and of Arrhenius type are considered under the assumption of no feedback of the concentration on the velocity. Numerical simulations of advection-reaction-diffusion equations have been performed by an algorithm based on discrete-time maps. The results show a generic enhancement of the speed of front propagation by the underlying flow. For small molecular diffusivity, the front speed V(f) depends on the typical flow velocity U as a power law with an exponent depending on the topological properties of the flow, and on the ratio of reactive and advective time scales. For open-streamline flows we find always V(f) approximately U, whereas for cellular flows we observe V(f) approximately U(1/4) for fast advection and V(f) approximately U(3/4) for slow advection.

Superfast front propagation in reactive systems with non-Gaussian diffusion

We study a reactive field transported by a non-Gaussian process instead of a standard diffusion. If the process increments follow a probability distribution with exponential tails, the usual qualitative behaviour of the standard reaction diffusion system, i.e., exponential tails for the reacting field and a constant front speed, are recovered. But, if the process has power law tails and the reaction is pulled, the reacting field shows power law tails and the front speed increases exponentially with time. The comparison with other transport processes which exhibit anomalous diffusion shows that not only the presence of anomalous diffusion, but also its detailed mechanism, is relevant for the front propagation in reactive systems.

Thin front propagation in steady and unsteady cellular flows

Front propagation in two-dimensional steady and unsteady cellular flows is investigated in the limit of very fast reaction and sharp front, i.e., in the geometrical optics limit. For the steady flow, a simplified model allows for an analytical prediction of the front speed vf dependence on the stirring intensity U, which is in good agreement with numerical estimates. In particular, at large U, the behavior vf∼U/log(U) is predicted. By adding small scales to the velocity field we found that their main effect is to renormalize the flow intensity. In the unsteady (time-periodic) flow, we found that the front speed locks to the flow frequency and that, despite the chaotic nature of the Lagrangian dynamics, the front evolution is chaotic only for a transient. Asymptotically the front evolves periodically and chaos manifests only in its spatially wrinkled structure.

Macroscopic chaos in globally coupled maps

Abstract We study the coherent dynamics of globally coupled maps showing macroscopic chaos. With this term we indicate the hydrodynamical-like irregular behavior of some global observables, with typical times much longer than the times related to the evolution of the single (or microscopic) elements of the system. The usual Lyapunov exponent is not able to capture the essential features of this macroscopic phenomenon. Using the recently introduced notion of finite size Lyapunov exponent, we characterize, in a consistent way, these macroscopic behaviors. Basically, at small values of the perturbation we recover the usual (microscopic) Lyapunov exponent, while at larger values a sort of macroscopic Lyapunov exponent emerges, which can be much smaller than the former. A quantitative characterization of the chaotic motion at hydrodynamical level is then possible, even in the absence of the explicit equations for the time evolution of the macroscopic observables.

Inverse statistics of smooth signals: the case of two dimensional turbulence.

The problem of inverse statistics (statistics of distances for which the signal fluctuations are larger than a certain threshold) in differentiable signals with power law spectrum, E(k) approximately k(-alpha), 3< or =alpha<5, is discussed. We show that for these signals, with random phases, exit-distance moments follow a bifractal distribution. We also investigate two dimensional turbulent flows in the direct cascade regime, which display a more complex behavior. We give numerical evidences that the inverse statistics of 2D turbulent flows is described by a multifractal probability distribution; i.e., the statistics of laminar events is not simply captured by the exponent alpha characterizing the spectrum.

Statistical analysis of fixed income market

We present cross and time series analysis of price fluctuations in the US Treasury fixed income market. Bonds have been classified according to a suitable metric based on the correlation among them. The classification shows how the correlation among fixed income securities depends strongly on their maturity. We study also the structure of price fluctuations for single time series.

Efficiency in Foreign Exchange Markets

A quantitative check of weak efficiency in US dollar/German mark exchange rates is developed using high frequency data. We show the existence of long term return anomalies. We introduce a technique to measure the available information and show it can be profitable following a particular trading rule.

Scenario-generation methods for an optimal public debt strategy

We describe the methods employed for the generation of possible scenarios for term structure evolution. The problem originated as a request from the Italian Ministry of Economy and Finance to find an optimal strategy for the issuance of Public Debt securities. The basic idea is to split the evolution of each rate into two parts. The first component is driven by the evolution of the official rate (the European Central Bank official rate in the present case). The second component of each rate is represented by the fluctuations having null correlation with the ECB rate.

Markovian approximation in foreign exchange markets

In this paper, using the exit-time statistic, we study the structure of the price variations for the high-frequency data set of the bid–ask Deutschemark/US dollar exchange rate quotes registered by the inter-bank Reuters network over the period October 1, 1992 to September 30, 1993. Having rejected random-walk models for the returns, we propose a Markovian model which reproduce the available information of the financial series. Besides the usual correlation analysis we have verified the validity of this model by means of other tools all inspired by information theory. These techniques are not only severe tests of the approximation but also evidence of some aspects of the data series which have a clear financial relevance.

Inverse velocity statistics in two-dimensional turbulence

We present a numerical study of two-dimensional turbulent flows in the enstropy cascade regime, with different large-scale energy sinks. In particular, we study the statistics of more-than-differentiable velocity fluctuations by means of two sets of statistical estimators, namely inverse statistics and second-order differences. In this way, we are able to probe statistical fluctuations that are not captured by the usual spectral analysis. We show that a new set of exponents associated to more-than-differentiable fluctuations of the velocity field exists. We also present a numerical investigation of the temporal properties of u measured in different spatial locations.