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Pointwise explicit estimates for derivatives of solutions to linear parabolic PDEs with Neumann boundary conditions

C Ciccarella

TL;DR

This work derives explicit, pointwise gradient bounds for solutions to linear parabolic PDEs with Neumann boundary conditions on a bounded interval, with constants expressed solely in terms of the PDE coefficients and the domain. The method is probabilistic: it extends a derivative result for time-inhomogeneous reflected SDEs, uses a time-change to achieve constant diffusion, and applies a spectral expansion for first-hitting times to bound the gradient term. The main result provides a closed-form bound on $\partial V/\partial x$ depending on the first eigenvalue and spectral tails, along with a sufficient condition for boundedness as $t\to\infty$, enabling practical gradient estimates for verification in optimal control. The approach yields a computationally cheap tool for evaluating gradient bounds relevant to problems such as sailboat trajectory optimization.

Abstract

We derive explicit pointwise bounds for the spatial derivative $\left| \frac{\partial V}{\partial x} \right|$ of solutions to linear parabolic PDEs with Neumann boundary conditions. The bound is fully explicit in the sense that it depends only on the coefficients of the PDE and the domain, including closed-form expression for all constants. The proof is purely probabilistic. We first extend to time inhomogeneous diffusions a result concerning the derivative of the solution of a reflected SDE. Then, we combine it with the spectral expansion of the law of the first hitting time to a boundary for a reflected diffusion. The main motivation comes from optimal control where, in order to apply verification theorems, precise gradient estimates are often required when closed-form solutions of the Hamilton-Jacobi-Bellman equation. This result will be used in a forthcoming work to rigorously prove that the conjectured optimal strategy for the sailboat trajectory optimization problem is indeed optimal far from the buoy. We also state a sufficient condition for $\limsup_{t\rightarrow \infty} \left| \frac{\partial V}{\partial x}(t,x) \right|$ to be bounded, which only involves the coefficients of the problem and the first eigenvalue of the spectral expansion.

Pointwise explicit estimates for derivatives of solutions to linear parabolic PDEs with Neumann boundary conditions

TL;DR

This work derives explicit, pointwise gradient bounds for solutions to linear parabolic PDEs with Neumann boundary conditions on a bounded interval, with constants expressed solely in terms of the PDE coefficients and the domain. The method is probabilistic: it extends a derivative result for time-inhomogeneous reflected SDEs, uses a time-change to achieve constant diffusion, and applies a spectral expansion for first-hitting times to bound the gradient term. The main result provides a closed-form bound on depending on the first eigenvalue and spectral tails, along with a sufficient condition for boundedness as , enabling practical gradient estimates for verification in optimal control. The approach yields a computationally cheap tool for evaluating gradient bounds relevant to problems such as sailboat trajectory optimization.

Abstract

We derive explicit pointwise bounds for the spatial derivative of solutions to linear parabolic PDEs with Neumann boundary conditions. The bound is fully explicit in the sense that it depends only on the coefficients of the PDE and the domain, including closed-form expression for all constants. The proof is purely probabilistic. We first extend to time inhomogeneous diffusions a result concerning the derivative of the solution of a reflected SDE. Then, we combine it with the spectral expansion of the law of the first hitting time to a boundary for a reflected diffusion. The main motivation comes from optimal control where, in order to apply verification theorems, precise gradient estimates are often required when closed-form solutions of the Hamilton-Jacobi-Bellman equation. This result will be used in a forthcoming work to rigorously prove that the conjectured optimal strategy for the sailboat trajectory optimization problem is indeed optimal far from the buoy. We also state a sufficient condition for to be bounded, which only involves the coefficients of the problem and the first eigenvalue of the spectral expansion.

Paper Structure

This paper contains 6 sections, 20 theorems, 165 equations.

Key Result

Theorem 1.2

Assume Hypothesis hyp is verified. Then, for any $t \geq 0$ and $x\in \bar{{\cal I}}$, the following holds.

Theorems & Definitions (47)

  • Remark 1.1
  • Theorem 1.2
  • Remark 2.2
  • Proposition 2.3
  • proof
  • Proposition 2.4
  • proof
  • Remark 3.1
  • Lemma 3.2
  • proof
  • ...and 37 more