Analysis of White Noise Limits for Stochastic Systems with Two Fast Relaxation Times

In this paper we present a rigorous asymptotic analysis for stochastic systems with two fast relaxation times. The mathematical model analyzed in this paper consists of a Langevin equation for the particle motion with time-dependent force constructed through an infinite dimensional Gaussian noise process. We study the limit as the particle relaxation time as well as the correlation time of the noise tend to zero and we obtain the limiting equations under appropriate assumptions on the Gaussian noise. We show that the limiting equation depends on the relative magnitude of the two fast time scales of the system. In particular, we prove that in the case where the two relaxation times converge to zero at the same rate there is a drift correction, in addition to the limiting It\^{o} integral, which is not of Stratonovich type. If, on the other hand, the colored noise is smooth on the scale of particle relaxation then the drift correction is the standard Stratonovich correction. If the noise is rough on this scale then there is no drift correction. Strong (i.e. pathwise) techniques are used for the proof of the convergence theorems.Comment: 35 pages, 0 figures, To appear in SIAM J. MM

Standing the Test of Time: The Breadth of Majority Coalitions and the Fate of U.S. Supreme Court Precedents

Should a strategic Justice assemble a broader coalition for the majority opinion than is necessary, even if that means accommodating changes that move the opinion away from the author’s ideal holding? If the author’s objective is to durably move the law to his or her ideal holding, the conventional answer is no, because there is a cost and no corresponding benefit. We consider whether attracting a broad majority coalition can placate future courts. Controlling for the size of the coalition, we find that cases with ideologically narrow coalitions are more likely to be treated negatively by later courts. Specifically, adding either ideological breadth or a new member to the majority coalition results in an opinion that is less likely to be overruled, criticized, or questioned by a later court. Our findings contradict the conventional wisdom regarding the coalition-building strategy of a rational and strategic opinion author, establishing that the author has an incentive to go beyond the four most ideologically proximate Justices in building a majority coalition. And because of later interpreters’ negative reactions to narrow coalitions, the law ends up being less ideological than the Justices themselves

Gamma Limit for Transition Paths of Maximal Probability

Chemical reactions can be modelled via diffusion processes conditioned to make a transition between specified molecular configurations representing the state of the system before and after the chemical reaction. In particular the model of Brownian dynamics - gradient flow subject to additive noise - is frequently used. If the chemical reaction is specified to take place on a given time interval, then the most likely path taken by the system is a minimizer of the Onsager-Machlup functional. The Gamma limit of this functional is determined in the case where the temperature is small and the transition time scales as the inverse temperatur

Hempstead Union Free School District and United Public Service Employees Union

In the matter of the fact-finding between the Hempstead Union Free School District, employer, and the United Public Service Employees Union, union. PERB case no. M2009-300. Before: Stuart L. Bass, fact finder

Analysis of the 3DVAR Filter for the Partially Observed Lorenz '63 Model

The problem of effectively combining data with a mathematical model constitutes a major challenge in applied mathematics. It is particular challenging for high-dimensional dynamical systems where data is received sequentially in time and the objective is to estimate the system state in an on-line fashion; this situation arises, for example, in weather forecasting. The sequential particle filter is then impractical and ad hoc filters, which employ some form of Gaussian approximation, are widely used. Prototypical of these ad hoc filters is the 3DVAR method. The goal of this paper is to analyze the 3DVAR method, using the Lorenz '63 model to exemplify the key ideas. The situation where the data is partial and noisy is studied, and both discrete time and continuous time data streams are considered. The theory demonstrates how the widely used technique of variance inflation acts to stabilize the filter, and hence leads to asymptotic accuracy

Analysis of SPDEs Arising in Path Sampling Part I: The Gaussian Case

In many applications it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite dimensional analogue of the Langevin SDE used in finite dimensional sampling. Here the theory is developed for conditioned Gaussian processes for which the resulting SPDE is linear. Applications include the Kalman-Bucy filter/smoother. A companion paper studies the nonlinear case, building on the linear analysis provided here