"Spectrally gapped" random walks on networks: a Mean First Passage Time formula
We derive an approximate but explicit formula for the Mean First Passage Time of a random walker between a source and a target node of a directed and weighted network. The formula does not require any matrix inversion, and it takes as only input the transition probabilities into the target node....
Guardado en:
Autor principal: | |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
SciPost
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/38d508ff284d4a79a3b1c6b3f62a6b31 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:38d508ff284d4a79a3b1c6b3f62a6b31 |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:38d508ff284d4a79a3b1c6b3f62a6b312021-11-04T18:40:56Z"Spectrally gapped" random walks on networks: a Mean First Passage Time formula2542-465310.21468/SciPostPhys.11.5.088https://doaj.org/article/38d508ff284d4a79a3b1c6b3f62a6b312021-11-01T00:00:00Zhttps://scipost.org/SciPostPhys.11.5.088https://doaj.org/toc/2542-4653We derive an approximate but explicit formula for the Mean First Passage Time of a random walker between a source and a target node of a directed and weighted network. The formula does not require any matrix inversion, and it takes as only input the transition probabilities into the target node. It is derived from the calculation of the average resolvent of a deformed ensemble of random sub-stochastic matrices $H=\langle H\rangle +\delta H$, with $\langle H\rangle$ rank-$1$ and non-negative. The accuracy of the formula depends on the spectral gap of the reduced transition matrix, and it is tested numerically on several instances of (weighted) networks away from the high sparsity regime, with an excellent agreement.Silvia Bartolucci, Fabio Caccioli, Francesco Caravelli, Pierpaolo VivoSciPostarticlePhysicsQC1-999ENSciPost Physics, Vol 11, Iss 5, p 088 (2021) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Physics QC1-999 |
spellingShingle |
Physics QC1-999 Silvia Bartolucci, Fabio Caccioli, Francesco Caravelli, Pierpaolo Vivo "Spectrally gapped" random walks on networks: a Mean First Passage Time formula |
description |
We derive an approximate but explicit formula for the Mean First Passage Time
of a random walker between a source and a target node of a directed and
weighted network. The formula does not require any matrix inversion, and it
takes as only input the transition probabilities into the target node. It is
derived from the calculation of the average resolvent of a deformed ensemble of
random sub-stochastic matrices $H=\langle H\rangle +\delta H$, with $\langle
H\rangle$ rank-$1$ and non-negative. The accuracy of the formula depends on the
spectral gap of the reduced transition matrix, and it is tested numerically on
several instances of (weighted) networks away from the high sparsity regime,
with an excellent agreement. |
format |
article |
author |
Silvia Bartolucci, Fabio Caccioli, Francesco Caravelli, Pierpaolo Vivo |
author_facet |
Silvia Bartolucci, Fabio Caccioli, Francesco Caravelli, Pierpaolo Vivo |
author_sort |
Silvia Bartolucci, Fabio Caccioli, Francesco Caravelli, Pierpaolo Vivo |
title |
"Spectrally gapped" random walks on networks: a Mean First Passage Time formula |
title_short |
"Spectrally gapped" random walks on networks: a Mean First Passage Time formula |
title_full |
"Spectrally gapped" random walks on networks: a Mean First Passage Time formula |
title_fullStr |
"Spectrally gapped" random walks on networks: a Mean First Passage Time formula |
title_full_unstemmed |
"Spectrally gapped" random walks on networks: a Mean First Passage Time formula |
title_sort |
"spectrally gapped" random walks on networks: a mean first passage time formula |
publisher |
SciPost |
publishDate |
2021 |
url |
https://doaj.org/article/38d508ff284d4a79a3b1c6b3f62a6b31 |
work_keys_str_mv |
AT silviabartoluccifabiocacciolifrancescocaravellipierpaolovivo spectrallygappedrandomwalksonnetworksameanfirstpassagetimeformula |
_version_ |
1718444642300592128 |