In the case of epigenetic memory based on freely-diffusing factors, the alternative “stable” states can probably be thought of as long-lived metastable states in “real” stochastic system, which become stable fixed points in the limit as the number of particles N goes to infinity. In models, the switching time often grows exponentially with the number of particles. You may enjoy https://arxiv.org/abs/q-bio/0410003 or https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.208101.
In the case of epigenetic memory based on freely-diffusing factors, the alternative “stable” states can probably be thought of as long-lived metastable states in “real” stochastic system, which become stable fixed points in the limit as the number of particles N goes to infinity. In models, the switching time often grows exponentially with the number of particles. You may enjoy https://arxiv.org/abs/q-bio/0410003 or https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.115.208101.
For memory based on chemical modifications embedded along the genome, like DNA methylation, there isn’t really a “large N” limit to take, and in my view things are less settled. You may enjoy https://pubmed.ncbi.nlm.nih.gov/17512413/ or (shameless plug) https://www.science.org/doi/10.1126/science.adg3053