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Edward C. Waymire

Publications and source records attributed to Edward C. Waymire.

14 recordsLinked to original sources

Navier-Stokes Equations with Fractional Dissipation and Associated Doubly Stochastic Yule Cascades

We introduce a self-similar doubly stochastic Yule (DSY) cascade associated with the deterministic Navier-Stokes equations (NSE) in $\mathbb{R}^d$ with fractional dissipation $(-\Delta)^\gamma$. Interestingly, such a structure is well-defined only in the scaling-supercritical regime $\gamma\in(\frac{1}{2},\frac{d+2}{4})$. We then characterize parametric regions of $(d,\gamma)$ that correspond to the stochastically explosive, non-explosive, hyperexplosive, non-hyperexplosive behaviors of the DSY cascade. Stochastic solution processes are constructed recursively to randomly transform (deterministic) initial data, such that their expectations yield solutions to the fractional NSE whenever these expectations exist. Explosion and geometric properties of the DSY cascade are then exploited to establish non-uniqueness and finite-time blowup results for a scalar partial differential equation associated with the fractional NSE using a majorization principle for stochastic solution processes. In the special case $d=2$, we derive a closed form for the solution process and prove the finite-time loss of integrability of the solution process for sufficiently large initial data. This lack of integrability does not necessarily imply finite-time blowup of solutions to the fractional NSE. Indeed, for vortex-flow initial data, we show that the solution can be continued beyond the time of integrability breakdown by averaging the stochastic solution processes in a way that creates symmetry cancellations.

math.PR

Transformation of Stochastic Recursions and Critical Phenomena in the Analysis of the Aldous-Shields-Athreya Cascade and Related Mean Flow Equations

The paper has two main goals. First, we extend the contemporary probability theory on trees to investigate critical phenomena in a stochastic model of Yule type called Aldous-Shields-Athreya (ASA) cascade. Second, we apply the newly developed probabilistic framework to problems of uniqueness and nonuniqueness of solutions to the linear and nonlinear mean flow equations, referred to as the pantograph equation and $\alpha$-Riccati equation, respectively. The stochastic processes associated with these equations are related to each other via a one-parameter family of transformations. Remarkably, these simple transformations lead to infinitely many solutions to the initial-value problem of the nonlinear mean flow equation. Despite being non-explicit at the level of mean flow, their effect on the mean flow equations is reminiscent of how the Cole-Hopf transformation maps solutions of the heat equation to those of the Burgers equation. While the ASA cascade has been used to model percolation, ageing, and data compression, its relevance to any specific physical molecular dynamics is unclear to the authors. Nevertheless, our results highlight how simple stochastic-level transformations can uncover significant macroscopic structures. This principle is exemplified by the connection between spontaneous magnetization and shocks in the Burgers equation (Newman 1986) or the connection between the branching Brownian motion and the KPP equation (McKean 1975). In our model, the breakdown of uniqueness in mean flow solutions corresponds to critical phenomena in the ASA cascade such as stochastic explosion, hyperexplosion, and percolation.

math.PR

Errata to Stochastic explosion and non-uniqueness for $α$-Riccati equation

An error occurs in a part of the statement and proof of Proposition 2.2 in Jour. Math. Anal. and Appl., 476, (2019), 53-85 that is corrected in this erratum. The revised result reveals a new and unexpected critical phenomenon, having further implications for non-uniqueness of solutions to a nonlinear differential equation of the Riccati type.

math.PR

Doubly Stochastic Yule Cascades (Part I): The explosion problem in the time-reversible case

Motivated by the probabilistic methods for nonlinear differential equations introduced by McKean (1975) for the Kolmogorov-Petrovski-Piskunov (KPP) equation, and by Le Jan and Sznitman (1997) for the incompressible Navier-Stokes equations, we identify a new class of stochastic cascade models, referred to as Doubly Stochastic Yule cascades. We establish non-explosion criteria under the assumption that the randomization of Yule intensities from generation to generation is by an ergodic time-reversible Markov process. In addition to the cascade models that arise in the analysis of certain deterministic nonlinear differential equations, this model includes the multiplicative branching random walks, the branching Markov processes, and the stochastic generalizations of the percolation and/or cell aging models introduced by Aldous and Shields (1988) and independently by Athreya (1985).

math.PR

Doubly stochastic Yule cascades (Part II): The explosion problem in the non-reversible case

We analyze the explosion problem for a class of stochastic models introduced in Part I (arXiv:2103.06912), referred to as doubly stochastic Yule cascades. These models arise naturally in the construction of solutions to evolutionary PDEs as well as in purely probabilistic first passage percolation phenomena having a Markov-type statistical dependence, new for this context. Using cut-set arguments and a greedy algorithm, we respectively establish criteria for non-explosion and explosion without requiring the time-reversibility of the underlying branching Markov chain (a condition required in Part I). Notable applications include the explosion of the self-similar cascade of the Navier-Stokes equations in dimension $d=3$ and non-explosion in dimensions $d\ge 12$.

math.PR

When Fourth Moments Are Enough

This note concerns a somewhat innocent question motivated by an observation concerning the use of Chebyshev bounds on sample estimates of $p$ in the binomial distribution with parameters $n,p$. Namely, what moment order produces the best Chebyshev estimate of $p$? If $S_n(p)$ has a binomial distribution with parameters $n,p$, there it is readily observed that ${\rm argmax}_{0\le p\le 1}{\mathbb E}S_n^2(p) = {\rm argmax}_{0\le p\le 1}np(1-p) = \frac12,$ and ${\mathbb E}S_n^2(\frac12) = \frac{n}{4}$. Rabi Bhattacharya observed that while the second moment Chebyshev sample size for a $95\%$ confidence estimate within $\pm 5$ percentage points is $n = 2000$, the fourth moment yields the substantially reduced polling requirement of $n = 775$. Why stop at fourth moment? Is the argmax achieved at $p = \frac12$ for higher order moments and, if so, does it help, and compute $\mathbb{E}S_n^{2m}(\frac12)$? As captured by the title of this note, answers to these questions lead to a simple rule of thumb for best choice of moments in terms of an effective sample size for Chebyshev concentration inequalities.

math.PR

A Delayed Yule Process

In now classic work, David Kendall (1966) recognized that the Yule process and Poisson process could be related by a (random) time change. Furthermore, he showed that the Yule population size rescaled by its mean has an almost sure exponentially distributed limit as $t\to \infty$. In this note we introduce a class of coupled delayed Yule processes parameterized by $0 < α\le 1$ that includes the Poisson process at $α= {1/2}$. Moreover we extend Kendall's limit theorem to include a larger class of positive martingales derived from functionals that gauge the population genealogy. A somewhat surprising connection with the Holley-Liggett smoothing transformation also emerges in this context. Specifically, the latter is exploited to uniquely characterize the moment generating functions of distributions of the limit martingales, generalizing Kendall's mean one exponential limit.

math.PR

Continuity of Local Time: An applied perspective

Continuity of local time for Brownian motion ranks among the most notable mathematical results in the theory of stochastic processes. This article addresses its implications from the point of view of applications. In particular an extension of previous results on an explicit role of continuity of (natural) local time is obtained for applications to recent classes of problems in physics, biology and finance involving discontinuities in a dispersion coefficient. The main theorem and its corollary provide physical principles that relate macro scale continuity of deterministic quantities to micro scale continuity of the (stochastic) local time.

math.PR

Symmetry Breaking and Uniqueness for the Incompressible Navier-Stokes Equations

The present article establishes connections between the structure of the deterministic Navier-Stokes equations and the structure of (similarity) equations that govern self-similar solutions as expected values of certain naturally associated stochastic cascades. A principle result is that explosion criteria for the stochastic cascades involved in the probabilistic representations of solutions to the respective equations coincide. While the uniqueness problem itself remains unresolved, these connections provide interesting problems and possible methods for investigating symmetry breaking and the uniqueness problem for Navier-Stokes equations. In particular, new branching Markov chains, including a dilogarithmic branching random walk on the multiplicative group $(0,\infty)$, naturally arise as a result of this investigation.

math.AP

Advection-Dispersion Across Interfaces

This article concerns a systemic manifestation of small scale interfacial heterogeneities in large scale quantities of interest to a variety of diverse applications spanning the earth, biological and ecological sciences. Beginning with formulations in terms of partial differential equations governing the conservative, advective-dispersive transport of mass concentrations in divergence form, the specific interfacial heterogeneities are introduced in terms of (spatial) discontinuities in the diffusion coefficient across a lower-dimensional hypersurface. A pathway to an equivalent stochastic formulation is then developed with special attention to the interfacial effects in various functionals such as first passage times, occupation times and local times. That an appreciable theory is achievable within a framework of applications involving one-dimensional models having piecewise constant coefficients greatly facilitates our goal of a gentle introduction to some rather dramatic mathematical consequences of interfacial effects that can be used to predict structure and to inform modeling.

math.ST

On The Drift Paradox in a Regime-Switching Model

This note is motivated by the article by F. Lutscher, E. Pachepsky, and M. Lewis (2005), The Effect of Dispersal Patterns on Stream Populations SIAM Rev. Vol. 47 No. 4 pp. 749-772 on the drift paradox. We consider the case of a regime switching probabilistic model for a population of organisms living in a one dimensional environment with drift towards an absorbing boundary of the type introduced by Lutscher et al. (2005). In particular, the two regimes consist of birth/death style demographics governing the evolution of the immobile regime, and some form of advection-dispersion governing the evolution of the mobile regime, together with a regime-switching mechanism linking the two. In the present note it is shown for the regime-switching model, and in contrast to the results in the afore cited work, for any finite advection speed, no matter how large, there is a finite critical length of the domain above which the population can persist.

math.PR

First Passage Times and Breakthrough Curves Associated with Interfacial Phenomena

Advection and dispersion in highly heterogeneous environments involving interfacial discontinuities in the corresponding drift and dispersion rates are described through disparate examples from the physical and biological sciences. A mathematical framework is formulated to address specific empirical phenomena involving first passage time and occupation time functionals observed in relation to the interfacial parameters.

math.PR

Probability & incompressible Navier-Stokes equations: An overview of some recent developments

This is largely an attempt to provide probabilists some orientation to an important class of non-linear partial differential equations in applied mathematics, the incompressible Navier-Stokes equations. Particular focus is given to the probabilistic framework introduced by LeJan and Sznitman [Probab. Theory Related Fields 109 (1997) 343-366] and extended by Bhattacharya et al. [Trans. Amer. Math. Soc. 355 (2003) 5003-5040; IMA Vol. Math. Appl., vol. 140, 2004, in press]. In particular this is an effort to provide some foundational facts about these equations and an overview of some recent results with an indication of some new directions for probabilistic consideration.

math.PR

A general decomposition theory for random cascades

This announcement describes a probabilistic approach to cascades which, in addition to providing an entirely probabilistic proof of the Kahane-Peyrière theorem for independent cascades, readily applies to general dependent cascades. Moreover, this unifies various seemingly disparate cascade decompositions, including Kahane's T-martingale decomposition and dimension disintegration.

math.PR