PreprintarXiv licencearXiv
Networks with Memory and Isospectral Reduction
Abstract
Restricting the linear dynamics of a graph to selected vertices generally introduces memory, because interactions can pass through hidden vertices before returning. The resulting rational memory kernels give isospectral reduction a dynamical interpretation and identify latent graph symmetries with symmetries of the observed evolution.
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BibTeX
@misc{molnar2026networks,
title = {{Networks with Memory and Isospectral Reduction}},
author = {Grant Molnar},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.38995},
eprint = {2610.38995},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.38995},
}
RIS
TY - UNPB
TI - Networks with Memory and Isospectral Reduction
AU - Grant Molnar
PY - 2026
DA - 2026/10/28
PB - arXiv
DO - 10.48550/arxiv.2610.38995
UR - https://arxiv.org/abs/2610.38995
AB - Restricting the linear dynamics of a graph to selected vertices generally introduces memory, because interactions can pass through hidden vertices before returning. The resulting rational memory kernels give isospectral reduction a dynamical interpretation and identify latent graph symmetries with symmetries of the observed evolution.
ER -