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Gennady Uraltsev

Publications and source records attributed to Gennady Uraltsev.

9 recordsLinked to original sources

Probabilistic well-posedness of generalized cubic nonlinear Schrödinger equations with strong dispersion using higher order expansions

In this paper, we study the local well-posedness of the cubic Schrödinger equation $$(i\partial_t + \mathcal{L}) u = \pm |u|^2 u \qquad \textrm{on} \quad \ I\times \mathbb{R}^d ,$$ with initial data being a Wiener randomization at unit scale of a given function $f$ and $\mathcal{L}$ being an operator of degree $σ\geq 2$. In particular, we prove that a solution exists almost-surely locally in time provided $f\in H^{S}_{x}(\mathbb{R}^{d})$ with $S>\frac{2-σ}{4}$ for $d\leq \frac{3σ}{2}$, i.e. even if the initial datum is taken in certain negative order Sobolev spaces. The solutions are constructed as a sum of an explicit multilinear expansion of the flow in terms of the random initial data and of an additional smoother remainder term with deterministically subcritical regularity. We develop the framework of directional space-time norms to control the (probabilistic) multilinear expansion and the (deterministic) remainder term and to obtain improved bilinear probabilistic-deterministic Strichartz estimates.

math.AP↗

Higher order expansion for the probabilistic local well-posedness theory for a cubic nonlinear Schrödinger equation

In this paper, we study the probabilistic local well-posedness of the cubic Schrödinger equation (cubic NLS): \[ (i\partial_{t} + Δ) u = \pm |u|^{2} u \text{ on } [0,T) \times \mathbb{R}^{d}, \] with initial data being a Wiener randomization at unit scale of a given function $f$. We prove that a solution exists almost-surely locally in time provided \(f\in H^{S}_{x}(\mathbb{R}^{d})\) with \(S>\max\big(\frac{d-3}{4},\frac{d-4}{2}\big)\) for \(d\geq 3\). In particular, we establish that the local well-posedness holds for any \(S>0\) when \(d=3\). We also show that, under appropriate smallness conditions for the initial data, the solutions are global in time and scatter. The solutions are constructed as a sum of an explicit multilinear expansion of the flow in terms of the random initial data and of an additional smoother remainder term with deterministically subcritical regularity. This construction allows us to introduce a new and refined notion of graded scattering. We develop the framework of directional space-time norms to control the (probabilistic) multilinear expansion and the (deterministic) remainder term and to obtain improved bilinear probabilistic-deterministic Strichartz estimates.

math.AP↗

Almost sure local well-posedness for cubic nonlinear Schrodinger equation with higher order operators

In this paper, we study the local well-posedness of the cubic Schrödinger equation: \[ (i \partial_t - \mathscr{L}) u = \pm |u|^2 u \quad \text{ on } I \times \mathbb{R}^d, \] with randomized initial data, and $\mathscr{L}$ being an operator of degree $σ\geq 2$. Using estimates in directional spaces, we improve and extend known results for the standard Schrödinger equation (i.e. $\mathscr{L} = Δ$) to any dimension and obtain results under natural assumptions for general $\mathscr{L}$.

math.AP↗

The full range of uniform bounds for the bilinear Hilbert transform

We prove uniform uniform $L^{p}$ bounds for the family of bilinear Hilbert transforms $\mathrm{BHT}_β [f_1, f_2] (x) := \mathrm{p.v.} \int_{\mathbb{R}} f_1 (x - t) f_2 (x + βt) \frac{\mathrm{d} t}{t}$. We show that the operator $\mathrm{BHT}_β$ maps $L^{p_{1}}\times L^{p_{2}}$ into $L^{p}$ as long as $p_1 \in (1, \infty)$, $p_2 \in (1, \infty)$, and $p > \frac{2}{3}$ with a bound independent of $β\in(0,1]$. This is the full open range of exponents where the modulation invariant class of bilinear operators containing $\mathrm{BHT}_β$ can be bounded uniformly. This is done by proving boundedness of certain affine transformations of the frequency-time-scale space $\mathbb{R}^{3}_{+}$ in terms of iterated outer Lebesgue spaces. This results in new linear and bilinear wave packet embedding bounds well suited to study uniform bounds.

math.CA↗

The bilinear Hilbert transform in UMD spaces

We prove $L^p$-bounds for the bilinear Hilbert transform acting on functions valued in intermediate UMD spaces. Such bounds were previously unknown for UMD spaces that are not Banach lattices. Our proof relies on bounds on embeddings from Bochner spaces $L^p(\mathbb{R};X)$ into outer Lebesgue spaces on the time-frequency-scale space $\mathbb{R}^3_+$.

math.CA↗

Banach-valued modulation invariant Carleson embeddings and outer-$L^p$ spaces: the Walsh case

We prove modulation invariant embedding bounds from Bochner spaces $L^p(\mathbb{W};X)$ on the Walsh group to outer-$L^p$ spaces on the Walsh extended phase plane. The Banach space $X$ is assumed to be UMD and sufficiently close to a Hilbert space in an interpolative sense. Our embedding bounds imply $L^p$ bounds and sparse domination for the Banach-valued tritile operator, a discrete model of the Banach-valued bilinear Hilbert transform.

math.CA↗

Variational Carleson operators in UMD spaces

We prove $L^p$-boundedness of variational Carleson operators for functions valued in intermediate UMD spaces. This provides quantitative information on the rate of convergence of partial Fourier integrals of vector-valued functions. Our proof relies on bounds on wave packet embeddings into outer Lebesgue spaces on the time-frequency-scale space $\mathbb{R}^3_+$, which are the focus of this paper.

math.CA↗

Variational Carleson embeddings into the upper 3-space

In this paper we formulate embedding maps into time-frequency space related to the Carleson operator and its variational counterpart. We prove bounds for these embedding maps by iterating the outer measure theory of [DT15]. Introducing iterated outer $L^p$ spaces is a main novelty of this paper. [DT15] Yen Do and Christoph Thiele. "$L^p$ theory for outer measures and two themes of Lennart Carleson united". In: Bulletin of the American Mathematical Society 52.2 (2015), pp. 249-296.

math.CA↗

On the Distributional Hessian of the Distance Function

We describe the precise structure of the distributional Hessian of the distance function from a point of a Riemannian manifold. In doing this we also discuss some geometrical properties of the cutlocus of a point and we compare some different weak notions of Hessian and Laplacian.

math.DG↗