Skip to content
DraconiticResearch
Search Sources API
197,693 studies31 sourcesUpdated 14 min ago
PreprintCC BY 4.0arXiv

Nonequilibrium Transient Centers in Continuous-Time Systems

Abstract

Analysis of mathematical models in ecology and epidemiology often emphasizes asymptotic dynamics, such as stable equilibria, periodic orbits, and attractors. However, many biologically relevant trajectories exhibit long transient dynamics in which a relevant observable evolves slowly for an extended period before a comparatively rapid transition occurs. On finite time scales relevant to data collection, management, and intervention, such transient behavior can be more informative than the eventual asymptotic outcome. In this work, we study long-lasting and slowly varying transient dynamics in continuous-time systems through the framework of nonequilibrium transient centers. These centers are points in the state space near which the observable can remain nearly constant for a long time, even when the full state is not near an equilibrium. We develop finite-time escape criteria for identifying such centers and their reachable counterparts. These criteria provide practical conditions under which nearby trajectories can remain in a slow regime for a long period of time before eventually leaving it. We apply the theory to an epidemic model with delay of stability loss. In this model, trajectories may remain close to the disease-free manifold for a long time before the infectious population resurges. The framework developed here describes this behavior as slow evolution near a nonequilibrium transient center followed by finite-time escape from the slow regime.

Related

  1. fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios
    Laurent Excoffier, Matthieu Foll
    BioinformaticsPeer-reviewedLicence not statedFull text468 citedGenetics & genomicsHAL
  2. Disease extinction in finite time for a continuous-time SIRS model
    Abderrahman Iggidr, Mohamed Ouzahra, Gauthier Sallet
    Journal of Mathematical BiologyPeer-reviewedCC BY-NC-ND 4.0Full textGeneral biologyDynamical systemsHAL
  3. Learning continuous updating and control of neural population activities from sparse time samples
    Z. Wu, M. Zhang, N. Qian
    bioRxivPreprintCC BY-NC-NDFull textNeurosciencebioRxiv
  4. Exploring Dynamic and Reciprocal Within-Person Relations Between Emotion Regulation and Affect at Work: A Continuous Time Modeling Approach
    Cort W. Rudolph, Amelia Wilcox, Hannes Zacher
    PsyArXivPreprintCC BY 4.0Full textNeuroscienceOSF
  5. Prospective Coding Improves Learning in Deep Continuous-Time Recurrent Networks
    Shivang Rawat, Mirko Morello, Flaviano Morone +1
    arXivPreprintCC BY-NC-SA 4.0Full textNeurosciencearXiv
BibTeX
@misc{pasion2026nonequilibrium,
  title = {{Nonequilibrium Transient Centers in Continuous-Time Systems}},
  author = {Anthony Pasion and Felicia Magpantay},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.41930},
  eprint = {2610.41930},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.41930},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Nonequilibrium Transient Centers in Continuous-Time Systems
AU  - Anthony Pasion
AU  - Felicia Magpantay
PY  - 2026
DA  - 2026/10/30
PB  - arXiv
DO  - 10.48550/arxiv.2610.41930
UR  - https://arxiv.org/abs/2610.41930
AB  - Analysis of mathematical models in ecology and epidemiology often emphasizes asymptotic dynamics, such as stable equilibria, periodic orbits, and attractors. However, many biologically relevant trajectories exhibit long transient dynamics in which a relevant observable evolves slowly for an extended period before a comparatively rapid transition occurs. On finite time scales relevant to data collection, management, and intervention, such transient behavior can be more informative than the eventual asymptotic outcome. In this work, we study long-lasting and slowly varying transient dynamics in continuous-time systems through the framework of nonequilibrium transient centers. These centers are points in the state space near which the observable can remain nearly constant for a long time, even when the full state is not near an equilibrium. We develop finite-time escape criteria for identifying such centers and their reachable counterparts. These criteria provide practical conditions under which nearby trajectories can remain in a slow regime for a long period of time before eventually leaving it. We apply the theory to an epidemic model with delay of stability loss. In this model, trajectories may remain close to the disease-free manifold for a long time before the infectious population resurges. The framework developed here describes this behavior as slow evolution near a nonequilibrium transient center followed by finite-time escape from the slow regime.
ER  -