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This is a summary of research done by four senior investigators. Dafermos' research focused on a number of problems that lie at the interface of continuum mechanics and analysis. Fleming's research was concerned with optimal stochastic control theory, nonlinear filtering, large deviations for Markov diffusions, and viscosity solutions of nonlinear partial differential equations. Kushner's research covered a wide range of topics in stochastic systems theory and applied probability. Souganidis worked in the area of first and second order nonlinear partial differential equations, where a number of results concerning approximations with error estimates, singular perturbations and representation formulae were found. He also worked on questions of stability of special solutions of equation in fluids, as well as the structure of solutions of equations describing flows through porous media (implosion of waves).

Let $L$ be a positive definite self-adjoint operator on the $L^2$-space associated to a $\si$-finite measure space. Let $H$ be the dual space of the domain of $L^{1/2}$ w.r.t. $L^2(\mu)$. By using an It\^o type inequality for the $H$-norm and an integrability condition for the hyperbound of the semigroup $P_t:=\e^{-Lt}$, general extinction results are derived for a class of continuous adapted processes on $H$. Main applications include stochastic and deterministic fast diffusion equations with fractional Laplacians. Furthermore, we prove exponential integrability of the extinction time for all space dimensions in the singular diffusion version of the well-known Zhang-model for self-organized criticality, provided the noise is small enough. Thus we obtain that the system goes to the critical state in finite time in the deterministic and with probability one in finite time in the stochastic case.

Let $L$ be a positive definite self-adjoint operator on the $L^2$-space associated to a $\si$-finite measure space. Let $H$ be the dual space of the domain of $L^{1/2}$ w.r.t. $L^2(\mu)$. By using an It\^o type inequality for the $H$-norm and an integrability condition for the hyperbound of the semigroup $P_t:=\e^{-Lt}$, general extinction results are derived for a class of continuous adapted processes on $H$. Main applications include stochastic and deterministic fast diffusion equations with fractional Laplacians. Furthermore, we prove exponential integrability of the extinction time for all space dimensions in the singular diffusion version of the well-known Zhang-model for self-organized criticality, provided the noise is small enough. Thus we obtain that the system goes to the critical state in finite time in the deterministic and with probability one in finite time in the stochastic case.

In this paper we study the following non-autonomous stochastic evolution equation on a UMD Banach space $E$ with type 2, {equation}\label{eq:SEab}\tag{SE} {{aligned} dU(t) & = (A(t)U(t) + F(t,U(t))) dt + B(t,U(t)) dW_H(t), \quad t\in [0,T], U(0) & = u_0. {aligned}. {equation} Here $(A(t))_{t\in [0,T]}$ are unbounded operators with domains $(D(A(t)))_{t\in [0,T]}$ which may be time dependent. We assume that $(A(t))_{t\in [0,T]}$ satisfies the conditions of Acquistapace and Terreni. The functions $F$ and $B$ are nonlinear functions defined on certain interpolation spaces and $u_0\in E$ is the initial value. $W_H$ is a cylindrical Brownian motion on a separable Hilbert space $H$. Under Lipschitz and linear growth conditions we show that there exists a unique mild solution of \eqref{eq:SEab}. Under assumptions on the interpolation spaces we extend the factorization method of Da Prato, Kwapie\'n, and Zabczyk, to obtain space-time regularity results for the solution $U$ of \eqref{eq:SEab}. For Hilbert spaces $E$ we obtain a maximal regularity result. The results improve several previous results from the literature. The theory is applied to a second order stochastic partial differential equation which has been studied by Sanz-Sol\'e and Vuillermot. This leads to several improvements of their result.

We formulate a new class of stochastic partial differential equations (SPDEs), named high-order vector backward SPDEs (B-SPDEs) with jumps, which allow the high-order integral-partial differential operators into both drift and diffusion coefficients. Under certain type of Lipschitz and linear growth conditions, we develop a method to prove the existence and uniqueness of adapted solution to these B-SPDEs with jumps. Comparing with the existing discussions on conventional backward stochastic (ordinary) differential equations (BSDEs), we need to handle the differentiability of adapted triplet solution to the B-SPDEs with jumps, which is a subtle part in justifying our main results due to the inconsistency of differential orders on two sides of the B-SPDEs and the partial differential operator appeared in the diffusion coefficient. In addition, we also address the issue about the B-SPDEs under certain Markovian random environment and employ a B-SPDE with strongly nonlinear partial differential operator in the drift coefficient to illustrate the usage of our main results in finance.

We formulate a new class of stochastic partial differential equations (SPDEs), named high-order vector backward SPDEs (B-SPDEs) with jumps, which allow the high-order integral-partial differential operators into both drift and diffusion coefficients. Under certain type of Lipschitz and linear growth conditions, we develop a method to prove the existence and uniqueness of adapted solution to these B-SPDEs with jumps. Comparing with the existing discussions on conventional backward stochastic (ordinary) differential equations (BSDEs), we need to handle the differentiability of adapted triplet solution to the B-SPDEs with jumps, which is a subtle part in justifying our main results due to the inconsistency of differential orders on two sides of the B-SPDEs and the partial differential operator appeared in the diffusion coefficient. In addition, we also address the issue about the B-SPDEs under certain Markovian random environment and employ a B-SPDE with strongly nonlinear partial differential operator in the drift coefficient to illustrate the usage of our main results in finance.

The workshop/school on Stochastic Partial Differential Equations: Theory and Applications was held January 3 through January 7, 1996 in Los Angeles. The event was organized and hosted by the University of Southern California. Funding was provided by ONR ($20,000), ARO ($5,000) and IMA ($5,000). There were 85 participants registered for the Workshop. A series of minicourses during the Workshop was given by world renowned experts in stochastic analysis and its applications including D. Dawson(Carleton University, Canada), G. Glimm (SUNY of Stony Brook), N. Krylov (University of Minnesota), and J. Lebowitz (Rutgers University). These courses served as a comprehensive review of the state of the art in SPDEs and their applications. An agreement was reached between the organizers of the conference and the American Mathematical Society that the latter will publish a Proceedings of the Workshop in the form of a monograph. It is expected that the volume will be published in 1997. The Workshop was a great success. It demonstrated clearly that SPDE's is one of the most dynamically developing areas of probability and statistics with a wide range of important applications. Many of them are of substantial importance for Navy applications (e.g. nonlinear filtering, prediction and smoothing, stochastic numerics, SPDE's of physical oceanography, etc.).

This paper is concerned with a new type of differential game problems of forwardbackward stochastic systems. There are three distinguishing features: Firstly, our game systems are forward-backward doubly stochastic differential equations, which is a class of more general game systems than other forward-backward stochastic game systems without doubly stochastic terms; Secondly, forward equations are directly related to backward equations at initial time, not terminal time; Thirdly, the admissible control is required to be adapted to a sub-information of the full information generated by the underlying Brownian motions. We give a necessary and a sufficient conditions for both an equilibrium point of nonzero-sum games and a saddle point of zero-sum games. Finally, we work out an example of linear-quadratic nonzero-sum differential games to illustrate the theoretical applications. Applying some stochastic filtering techniques, we obtain the explicit expression of the equilibrium point.

An effective method of estimating transport parameters from tracer observations was developed based on the maximum likelihood approach in stochastic partial differential equations. Different classes of statistical estimators for near surface velocities and turbulence parameters have been studied. A complete error analysis for the method of moments was performed. Hamiltonian theory of wave turbulence was extended to the oceanic Rossby waves.