ON THE INVERSE PROBLEM FOR THE BURGERS' EQUATION WITH SMOOTH INITIAL DATA IN A BOUNDED DOMAIN

In this paper, we study the inverse problem of recovering smooth initial data for the one-dimensional Burgers' equation on a bounded spatial domain. Specifically, this problem focuses on recovering the initial condition from measurements at a part of the boundary over a given time interval. We therefore prove the uniqueness of the solution to the direct problem and establish, under certain assumptions, a stability estimate for the inverse problem based on a backward method in time and space, showing that the initial data can be reconstructed in this smooth case. To validate our theoretical results, we perform several numerical simulations and demonstrate the effectiveness of the proposed approaches.

Authors

Publication Details

Journal
Journal of Applied Analysis & Computation
Published
2026-09-24
DOI
https://doi.org/10.11948/20260119
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

ON THE INVERSE PROBLEM FOR THE BURGERS' EQUATION WITH SMOOTH INITIAL DATA IN A BOUNDED DOMAIN

Lea Safetly, Toni Sayah
Journal of Applied Analysis & Computation
Numerical methods in inverse problems
article

ON THE INVERSE PROBLEM FOR THE BURGERS' EQUATION WITH SMOOTH INITIAL DATA IN A BOUNDED DOMAIN

Lea Safetly, Toni Sayah
article en

Abstract

In this paper, we study the inverse problem of recovering smooth initial data for the one-dimensional Burgers' equation on a bounded spatial domain. Specifically, this problem focuses on recovering the initial condition from measurements at a part of the boundary over a given time interval. We therefore prove the uniqueness of the solution to the direct problem and establish, under certain assumptions, a stability estimate for the inverse problem based on a backward method in time and space, showing that the initial data can be reconstructed in this smooth case. To validate our theoretical results, we perform several numerical simulations and demonstrate the effectiveness of the proposed approaches.

Journal of Applied Analysis & ComputationVol. 17(2)
Openalex Percentile: Top 6%
Numerical methods in inverse problems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.