A fast reduced order method for linear parabolic inverse source problems

06/09/2023
by   Yuxuan Huang, et al.
0

In this paper, we propose a novel, computationally efficient reduced order method to solve linear parabolic inverse source problems. Our approach provides accurate numerical solutions without relying on specific training data. The forward solution is constructed using a Krylov sequence, while the source term is recovered via the conjugate gradient (CG) method. Under a weak regularity assumption on the solution of the parabolic partial differential equations (PDEs), we establish convergence of the forward solution and provide a rigorous error estimate for our method. Numerical results demonstrate that our approach offers substantial computational savings compared to the traditional finite element method (FEM) and retains equivalent accuracy.

READ FULL TEXT

page 9

page 10

research
12/21/2022

Numerical method and Error estimate for stochastic Landau–Lifshitz–Bloch equation

We study numerical methods for solving a system of quasilinear stochasti...
research
03/10/2020

A Least-Squares Finite Element Reduced Basis Method

We present a reduced basis (RB) method for parametrized linear elliptic ...
research
01/23/2020

Optimal error estimate of the finite element approximation of second order semilinear non-autonomous parabolic PDEs

In this work, we investigate the numerical approximation of the second o...
research
02/05/2022

A practical algorithm to minimize the overall error in FEM computations

Using the standard finite element method (FEM) to solve general partial ...
research
01/16/2018

A Bayesian Conjugate Gradient Method

A fundamental task in numerical computation is the solution of large lin...
research
04/12/2023

Consistent Point Data Assimilation in Firedrake and Icepack

When estimating quantities and fields that are difficult to measure dire...
research
09/13/2021

Learning reduced order models from data for hyperbolic PDEs

Given a set of solution snapshots of a hyperbolic PDE, we are interested...

Please sign up or login with your details

Forgot password? Click here to reset