Seminars and Colloquia by Series

Nonlinear Scattering Theory for Asymptotically de Sitter Vacuum Solutions

Series
PDE Seminar
Time
Tuesday, November 19, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Serban Cicortas Princeton University

We will talk about recent work establishing a quantitative nonlinear scattering theory for asymptotically de Sitter solutions of the Einstein vacuum equations in (n+1) dimensions with n ≥ 4 even, which are determined by small scattering data at future infinity and past infinity. We will also explain why the case of even spatial dimension n poses significant challenges compared to its odd counterpart and was left open by the previous works in the literature.

Mean viability and 2nd-order Hamilton-Jacobi-Bellman equations

Series
PDE Seminar
Time
Tuesday, November 12, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Christian KellerUniversity of Central Florida
I present a new approach of proving uniqueness for viscosity solutions of fully nonlinear 2nd-order Hamilton-Jacobi-Bellman equations. 
This approach is purely probabilistic. It uses the concept of mean viability and the closely related notion of quasi-contingent solution. 
Unlike all existing methods in the literature, my approach does not rely on finite-dimensional results. 
This is of relevance for genuinely infinite-dimensional open problems.

 

Schrödinger Equation with Coulomb Potential

Series
PDE Seminar
Time
Tuesday, October 22, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Ebru ToprakYale University

I will begin by presenting our recent results on the spherically symmetric Coulomb waves. Specifically, we study the evolution operator of H= -\Delta+q/|x| where q>0. Utilizing a distorted Fourier transform adapted to H, we explicitly compute the evolution kernel. A detailed analysis of this kernel reveals that e^itH satisfies an L^1 \to L^{\infty} dispersive estimate with the natural decay rate t^{-3/2}. This work was conducted in collaboration with Adam Black, Bruno Vergara, and Jiahua Zhou. Following this, I will discuss our ongoing research on the nonlinear Schrödinger equation, where we apply the distorted Fourier transform developed for the Coulomb Hamiltonian. This work is being carried out in collaboration with Mengyi Xie.

Sparsity of Fourier mass of passively advected scalars in the Batchelor regime

Series
PDE Seminar
Time
Tuesday, October 8, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Manh Khang HuynhGeorgia Tech

In this paper we propose a general dynamical mechanism that can lead to the failure of the Batchelor's mode-wise power spectrum law in passive scalar turbulence and hyperbolic dynamics, while the cumulative law remains true. Of technical interest, we also employ a novel method of power spectral variance to establish an exponential radial shell law for the Batchelor power spectrum. An accessible explanation of the power spectrum laws via harmonic analysis is also given.

Shock formation in weakly viscous conservation laws

Series
PDE Seminar
Time
Friday, October 4, 2024 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Cole GrahamUniversity of Wisconsin–Madison

The compressible Euler equations readily form shocks, but in 1D the inclusion of viscosity prevents such singularities. In this talk, we will quantitatively examine the interaction between generic shock formation and viscous effects as the viscosity tends to zero. We thereby obtain sharp rates for the vanishing-viscosity limit in Hölder norms, and uncover universal viscous structure near shock formation. The results hold for large classes of viscous hyperbolic conservation laws, including compressible Navier–Stokes with physical rather than artificial viscosity. This is joint work with John Anderson and Sanchit Chaturvedi.

Bifurcation for hollow vortex desingularization

Series
PDE Seminar
Time
Tuesday, October 1, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Ming ChenUniversity of Pittsburgh

A hollow vortex is a region of constant pressure bounded by a vortex sheet and suspended inside a perfect fluid; we can think of it as a spinning bubble of air in water. In this talk, we present a general method for desingularizing non-degenerate steady point vortex configurations into collections of steady hollow vortices. The machinery simultaneously treats the translating, rotating, and stationary regimes. Through global bifurcation theory, we further obtain maximal curves of solutions that continue until the onset of a singularity. As specific examples, we obtain the first existence theory for co-rotating hollow vortex pairs and stationary hollow vortex tripoles, as well as a new construction of Pocklington’s classical co-translating hollow vortex pairs. All of these families extend into the non-perturbative regime, and we obtain a rather complete characterization of the limiting behavior along the global bifurcation curve. This is a joint work with Samuel Walsh (Missouri) and Miles Wheeler (Bath).

Existence of stationary measures for partially damped SDEs with generic, Euler-type nonlinearities

Series
PDE Seminar
Time
Tuesday, September 24, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Keagan CallisGeorgia Tech

We study nonlinear energy transfer and the existence of stationary measures in a class of degenerately forced SDEs on R^d with a quadratic, conservative nonlinearity B(x, x) constrained to possess various properties common to finite-dimensional fluid models and a linear damping term −Ax that acts only on a proper subset of phase space in the sense that dim(kerA) ≫ 1. Existence of a stationary measure is straightforward if kerA = {0}, but when the kernel of A is nontrivial a stationary measure can exist only if the nonlinearity transfers enough energy from the undamped modes to the damped modes. We develop a set of sufficient dynamical conditions on B that guarantees the existence of a stationary measure and prove that they hold “generically” within our constraint class of nonlinearities provided that dim(kerA) < 2d/3 and the stochastic forcing acts directly on at least two degrees of freedom. We also show that the restriction dim(kerA) < 2d/3 can be removed if one allows the nonlinearity to change by a small amount at discrete times. In particular, for a Markov chain obtained by evolving our SDE on approximately unit random time intervals and slightly perturbing the nonlinearity within our constraint class at each timestep, we prove that there exists a stationary measure whenever just a single mode is damped.

Finite-time blowup for the Fourier-restricted Euler and hypodissipative Navier-Stokes model equations

Series
PDE Seminar
Time
Tuesday, September 17, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Evan MillerUniversity of Alabama in Huntsville

In this talk, I will introduce the Fourier-restricted Euler and hypodissipative Navier–Stokes equations. These equations are analogous to the Euler equation and hypodissipative Navier–Stokes equation, respectively, but with the Helmholtz projection replaced by a projection onto a more restrictive constraint space. The nonlinear term arising from the self-advection of velocity is otherwise unchanged. I will prove finite time-blowup when the dissipation is weak enough, by making use of a permutation symmetric Ansatz that allows for a dyadic energy cascade of the type found in the Friedlander-Katz-Pavlović dyadic Euler/Navier–Stokes model equation.

Fourier Galerkin approximation of mean field control problems

Series
PDE Seminar
Time
Tuesday, September 3, 2024 - 15:30 for 1 hour (actually 50 minutes)
Location
ONLINE: https://gatech.zoom.us/j/92007172636?pwd=intwy0PZMdqJX5LUAbseRjy3T9MehD.1
Speaker
Mattia MartiniLaboratoire J.A. Dieudonné, Université Côte d&#039;Azur
Over the past twenty years, mean field control theory has been developed to study cooperative games between weakly interacting agents (particles).  The limiting formulation of a (stochastic) mean field control problem, arising as the number of agents approaches infinity, is a control problem for trajectories with values in the space of probability measures. The goal of this talk is to introduce a finite dimensional approximation of the solution to a mean field control problem set on the $d$-dimensional torus.  Our approximation is obtained by means of a Fourier-Galerkin method, the main principle of which is to truncate the Fourier expansion of probability measures. 
 
First, we prove that the Fourier-Galerkin method induces a new finite-dimensional control problem with trajectories in the space of probability measures with a finite number of Fourier coefficients. Subsequently, our main result asserts that, whenever the cost functionals are smooth and convex, the optimal control, trajectory, and value function from the approximating problem converge to their counterparts in the original mean field control problem. Noticeably, we show that our method yields a polynomial convergence rate directly proportional to the data's regularity. This convergence rate is faster than the one achieved by the usual particles methods available in the literature, offering a more efficient alternative. Furthermore, our technique also provides an explicit method for constructing an approximate optimal control along with its corresponding trajectory. This talk is based on joint work with François Delarue.

Differential Equations for Continuous-Time Deep Learning

Series
PDE Seminar
Time
Friday, April 19, 2024 - 15:00 for 1 hour (actually 50 minutes)
Location
CSIP Library (Room 5126), 5th floor, Centergy one
Speaker
Dr.Lars RuthottoResearch Associate Professor in the Department of Mathematics and the Department of Computer Science at Emory University

In this talk, we introduce and survey continuous-time deep learning approaches based on neural ordinary differential equations (neural ODEs) arising in supervised learning, generative modeling, and numerical solution of high-dimensional optimal control problems. We will highlight theoretical advantages and numerical benefits of neural ODEs in deep learning and their use to solve otherwise intractable PDE problems.

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