Exploring Stochastic Mean Curvature Flow on Networks Using Ito Calculus
Fuente:
arXiv
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2024
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866911930882457600 |
|---|---|
| author | Bahadursingh, Roman |
| author_facet | Bahadursingh, Roman |
| contents | In this paper, we investigate the stochastic mean curvature flow (SMCF) on networks, a niche area within stochastic processes and geometric analysis. By applying Ito calculus, we analyze the evolution of network structures influenced by random perturbations. We derive a stochastic differential equation (SDE) for the network edges and utilize numerical simulations to study the stability, long-term behavior, and pattern formation in these systems. Our results offer new insights into the dynamics of complex networks under stochastic influences and open pathways for future research in stochastic geometry. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_16920 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring Stochastic Mean Curvature Flow on Networks Using Ito Calculus Bahadursingh, Roman Differential Geometry Statistics Theory In this paper, we investigate the stochastic mean curvature flow (SMCF) on networks, a niche area within stochastic processes and geometric analysis. By applying Ito calculus, we analyze the evolution of network structures influenced by random perturbations. We derive a stochastic differential equation (SDE) for the network edges and utilize numerical simulations to study the stability, long-term behavior, and pattern formation in these systems. Our results offer new insights into the dynamics of complex networks under stochastic influences and open pathways for future research in stochastic geometry. |
| title | Exploring Stochastic Mean Curvature Flow on Networks Using Ito Calculus |
| topic | Differential Geometry Statistics Theory |
| url | https://arxiv.org/abs/2406.16920 |