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Gianmarco Del Sarto

Publications and source records attributed to Gianmarco Del Sarto.

11 recordsLinked to original sources

Continuous Data Assimilation for the 2D Navier-Stokes Equations from Partial Tangential Boundary Observations

We study continuous data assimilation for the two-dimensional Navier--Stokes equations on a smooth, bounded, connected domain with Navier-slip boundary conditions, using no interior observations. The available data consist only of finite-dimensional measurements of the tangential velocity on a non-empty relatively open subset $Γ\subset\partialΩ$. We prove that sufficiently strong boundary feedback, constructed from sufficiently fine observations, generates a coercive spectral gap for the assimilation error. The limiting gap is identified with that of a mixed-boundary problem obtained by imposing a homogeneous Dirichlet condition on $Γ$, and is shown to be of order $ν$. Combining this feedback-induced coercivity with an estimate of the non-linear error production in terms of the long-time averaged symmetric-gradient energy of the reference solution, we obtain a sufficient criterion for exponential synchronisation. We verify this criterion in the unforced case, for sufficiently small forcing when the unnudged Navier-slip form has an $\mathrm{L}^2$ spectral gap, for sufficiently large viscosity on domains without tangential rigid motions, and for sufficiently large viscosity in the presence of positive boundary friction. We also treat perfect slip on domains admitting tangential rigid motions, where synchronisation follows under a smallness condition on the non-rigid solenoidal component of the forcing.

math.AP↗

Continuous Data Assimilation for Semilinear Parabolic Equations with Multiplicative Observation Noise

The problem of continuous data assimilation for semilinear parabolic equations based on partial observations corrupted by noise is investigated. The noise is allowed to be multiplicative, with additive noise arising as a special case. In a general Gelfand triple framework, an abstract theory for the nudging equation is developed that covers both weak and strong formulations. Mean square convergence of the assimilation error is proved under suitable assumptions, and, under additional integrability conditions on the noise, a uniform almost sure convergence result is established. Finally, the framework is applied to several PDE models, including the 2D Navier-Stokes, 2D magnetohydrodynamics, 2D quasi-geostrophic, and 1D Allen-Cahn equations.

math.AP↗

Noise-Driven Free Boundaries In The Compressible Navier-Stokes Equations

A stochastic free-boundary problem for the three-dimensional barotropic compressible Navier--Stokes equations is studied. The main feature of the model is that the free boundary is transported by a Stratonovich stochastic flow, so that the noise enters the kinematic boundary condition and hence the evolution of the moving domain. An additional Itô forcing in the momentum equation is also allowed. The problem is transformed by a stochastic Lagrangian map generated by the velocity and the transport vector fields. In these coordinates the density is represented through the Jacobian of the flow, and the remaining system is solved by combining stochastic maximal regularity, deterministic %\rL^p%-%\rL^q$ estimates, and a localized contraction argument. Local pathwise well-posedness is obtained up to an a.s. positive stopping time, with strictly positive density and pathwise uniqueness.

math.AP↗

Optimal response for stochastic differential equations in $\mathbb{T}^d$ with perturbations on the drift term

We study stochastic differential equations on the $d$-dimensional flat torus $\mathbb{T}^d$ with drift and perturbation coefficients in $L^{\infty}(\mathbb{T}^d;\mathbb{R}^d)$ and additive non-degenerate noise. For the associated transfer operators, we analyse the dependence of the stationary measure and of the expectation of a given observable on small perturbations of the drift. In this framework, we prove a linear response formula for the invariant density and for the expectation of a given observable. We then address an optimal response problem, namely the determination of admissible perturbations that maximise the first-order variation of a prescribed observable. We establish existence of optimal perturbations and, in a Hilbert space framework, prove uniqueness and provide an explicit characterisation of the optimiser. This yields a practical Fourier-based numerical method, which we implement in several numerical examples, including both low and high-dimensional settings.

math.DS↗

Global well-posedness for small data in a 3D temperature-velocity model with Dirichlet boundary noise

We study a three-dimensional Boussinesq-type temperature-velocity system on a bounded smooth domain $\mathcal D\subset\mathbb R^3$, where the velocity $u^\varepsilon$ solves the Navier-Stokes equations and the temperature $θ^\varepsilon$ is driven by Dirichlet boundary noise of intensity $\sqrt{\varepsilon}$. The boundary forcing produces a stochastic convolution $Z^\varepsilon$ which is, in general, only continuous in time with values in $H^{-\frac12-δ_θ}(\mathcal D)$. To handle this roughness together with initial data $θ_0\in W^{s,6/5}(\mathcal D)$, we work in the ambient space $H^{-\frac12-δ_u}(\mathcal D)$ with $δ_u\ge \max\{δ_θ,\frac12-s\}$. Given a finite time $T>0$, for any $p>4$ and sufficiently small initial data, we prove existence and uniqueness of a mild solution $(u^\varepsilon,θ^\varepsilon)$ up to a stopping time $τ^\varepsilon\le T$ such that \[ u^\varepsilon \in W^{1,p}(0,τ^\varepsilon;H^{-\frac12-δ_u}(\mathcal D)) \cap L^p (0,τ^\varepsilon;H^{\frac32-δ_u}(\mathcal D)), \quad θ^\varepsilon \in C(0,τ^\varepsilon;H^{-\frac12-δ_u}(\mathcal D)). \] Moreover, we obtain a high-probability global existence estimate of the form $\mathbb P(τ^\varepsilon=T)\geq 1- C\varepsilon $, with $C= C( δ_θ, T)>0.$

math.PR↗

A Multiplicative-Noise Mechanism for Variability Amplification under Radiative Forcing in an Arctic Energy-Balance Model

We propose and analyse a mechanism by which $\mathrm{CO}_2$-driven radiative forcing can increase Arctic temperature variability in a stochastic Sellers-type energy-balance model. Starting from a fast-slow formulation in which insolation is modelled by a rapidly mean-reverting Ornstein-Uhlenbeck process while temperature evolves on a slow macroweather timescale, a Wong-Zakai reduction leads to a stochastic energy-balance equation with \emph{multiplicative} noise. After linearising around the stable equilibrium $T^{*,λ}$, we derive an explicit expression for the stationary variance of the temperature anomaly and prove that it increases monotonically with the forcing parameter $λ$ whenever $T^{*,λ}$ lies in the ice-sensitive regime of the co-albedo. We then consider a spatial anomaly model and its finite-difference semi-discretisation, obtaining a finite-dimensional SDE. Under natural stability conditions and nonnegative noise correlations, we establish a component-wise monotone increase of the stationary covariance matrix with respect to $λ$, including its off-diagonal entries. In particular, radiative forcing amplifies not only local variances but also the covariance between temperature anomalies at distinct spatial locations, indicating increased similarity in the variability of the anomaly field across space.

math.PR↗

Continuous Data Assimilation for Semilinear Parabolic Equations: A General Approach by Evolution Equations

This article develops a general framework for continuous deterministic data assimilation for semilinear parabolic equations by means of evolution equations. Introducing a nudged model driven by partial observations, the global well-posedness of the reference and the approximating systems is established under natural assumptions. In addition, it is shown that the approximating solution converges exponentially to the solution of the reference system, provided the observational resolution and the nudging parameter are suitably chosen. The approach allows us to consider many systems, such as the Allen-Cahn, Cahn-Hilliard, Sellers-type energy balance, and bidomain systems, for the first time.

math.AP↗

Time-periodic solutions to an energy balance model coupled with an active fluid under arbitrary large forces

This article concerns time-periodic solutions to a two-dimensional Sellers-type energy balance model coupled to the three-dimensional primitive equations via a dynamic boundary condition. It is shown that the underlying equations admit at least one strong time-periodic solution, provided the forcing term is time-periodic. The forcing term does not need to satisfy a smallness condition and is allowed to be arbitrarily large.

math.AP↗

Dynamic boundary conditions with noise for energy balance models coupled to geophysical flows

This article investigates an energy balance model coupled to the primitive equations by a dynamic boundary condition with and without noise on the boundary. It is shown that this system is globally strongly well-posed both in the deterministic setting for arbitrary large data in $W^{2(1-\frac{1}{p}),p}$ for $p \in [2,\infty)$ and in the stochastic setting for arbitrary large data in $H^1$.

math.AP↗

A non-autonomous framework for climate change and extreme weather events increase in a stochastic energy balance model

We develop a three-timescale framework for modelling climate change and introduce a space-heterogeneous one-dimensional energy balance model. This model, addressing temperature fluctuations from rising carbon dioxide levels and the super-greenhouse effect in tropical regions, fits within the setting of stochastic reaction-diffusion equations. Our results show how both mean and variance of temperature increase, without the system going through a bifurcation point. This study aims to advance the conceptual understanding of the extreme weather events frequency increase due to climate change.

physics.ao-ph↗

A Mean Field Game approach for pollution regulation of competitive firms

We develop a model based on mean-field games of competitive firms producing similar goods according to a standard AK model with a depreciation rate of capital generating pollution as a byproduct. Our analysis focuses on the widely-used cap-and-trade pollution regulation. Under this regulation, firms have the flexibility to respond by implementing pollution abatement, reducing output, and participating in emission trading, while a regulator dynamically allocates emission allowances to each firm. The resulting mean-field game is of linear quadratic type and equivalent to a mean-field type control problem, i.e., it is a potential game. We find explicit solutions to this problem through the solutions to differential equations of Riccati type. Further, we investigate the carbon emission equilibrium price that satisfies the market clearing condition and find a specific form of FBSDE of McKean-Vlasov type with common noise. The solution to this equation provides an approximate equilibrium price. Additionally, we demonstrate that the degree of competition is vital in determining the economic consequences of pollution regulation.

q-fin.MF↗