English

Deconvolution on graphs via linear programming

Functional Analysis 2026-05-19 v2

Abstract

The main challenge addressed in this paper is to identify individual terms in a superposition of heat kernels on a graph. We establish geometric conditions on the vertices at which these heat kernels are centered and find bounds on the time parameter governing the evolution under the heat semigroup that guarantee a successful recovery. This result can be viewed as a type of deconvolution on a graph. A first main result addresses the setting of a common time parameter for all the heat kernels. We also treat a more general setting when the time parameter depends on the location at which the heat kernel is centered.

Keywords

Cite

@article{arxiv.2305.02635,
  title  = {Deconvolution on graphs via linear programming},
  author = {Bernhard G. Bodmann and Jennifer J. May},
  journal= {arXiv preprint arXiv:2305.02635},
  year   = {2026}
}

Comments

14 pages, AMS LaTeX; update contains corrections and section on approximate duals and noisy recovery

R2 v1 2026-06-28T10:25:23.621Z