Inverse Wave Problems on Graphs
Abstract
We study inverse wave problems on finite graphs from time-dependent measurements on a prescribed set of vertices. With the graph geometry known, we consider recovery of either the initial signal or the vertex wave speeds when the other is given. Initial-signal recovery is characterized by observability of the associated finite-dimensional system, while a single experiment determines the vertex wave speeds under a zero forcing condition and a natural nonharmonicity assumption. We establish stability estimates for both recovery problems, develop a nonlinear least-squares reconstruction method, and extend the results to positively weighted graphs. Numerical simulations illustrate the reconstruction and examine the effects of observation geometry, time horizon, coefficient localization, and measurement noise on its performance. Our results are motivated both by numerical approaches to continuous inverse wave problems, where spatial discretization leads naturally to graph-based systems, and by applications in which the underlying dynamics are inherently discrete and evolve on networks.
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BibTeX
@misc{moradifam2026inverse,
title = {{Inverse Wave Problems on Graphs}},
author = {Amir Moradifam and Oliver P. Waite},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.21821},
eprint = {2610.21821},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.21821},
}
RIS
TY - UNPB
TI - Inverse Wave Problems on Graphs
AU - Amir Moradifam
AU - Oliver P. Waite
PY - 2026
DA - 2026/10/15
PB - arXiv
DO - 10.48550/arxiv.2610.21821
UR - https://arxiv.org/abs/2610.21821
AB - We study inverse wave problems on finite graphs from time-dependent measurements on a prescribed set of vertices. With the graph geometry known, we consider recovery of either the initial signal or the vertex wave speeds when the other is given. Initial-signal recovery is characterized by observability of the associated finite-dimensional system, while a single experiment determines the vertex wave speeds under a zero forcing condition and a natural nonharmonicity assumption. We establish stability estimates for both recovery problems, develop a nonlinear least-squares reconstruction method, and extend the results to positively weighted graphs. Numerical simulations illustrate the reconstruction and examine the effects of observation geometry, time horizon, coefficient localization, and measurement noise on its performance. Our results are motivated both by numerical approaches to continuous inverse wave problems, where spatial discretization leads naturally to graph-based systems, and by applications in which the underlying dynamics are inherently discrete and evolve on networks.
ER -