Search Results for author: Michael Assaf

Found 6 papers, 0 papers with code

Emergence of a Novel Phase in Population and Community Dynamics Due to Fat-Tailed Environmental Correlations

no code implementations15 Nov 2023 Immanuel Meyer, Ami Taitelbaum, Michael Assaf, Nadav M. Shnerb

For an isolated population, the time to extinction in this phase exhibits a novel scaling with the abundance, and also a non-monotonic dependence on the spectral exponent.

Outbreak-size distributions under fluctuating rates

no code implementations25 Aug 2023 Jason Hindes, Luis Mier-y-Teran-Romero, Ira B. Schwartz, Michael Assaf

Finally, we show that the crossover to the white-noise regime typically occurs for correlation times that are on the same order as the characteristic recovery time in the model.

Evolutionary Dynamics in a Varying Environment: Continuous versus Discrete Noise

no code implementations19 Dec 2022 Ami Taitelbaum, Robert West, Mauro Mobilia, Michael Assaf

Here, we study population dynamics subject to a fluctuating environment modeled by a varying carrying capacity changing continuously in time according to either binary random switches, or by being driven by a noise of continuous range.

Extreme outbreak dynamics in epidemic models

no code implementations2 Aug 2021 Jason Hindes, Michael Assaf, Ira B. Schwartz

Motivated by recent epidemic outbreaks, including those of COVID-19, we solve the canonical problem of calculating the dynamics and likelihood of extensive outbreaks in a population within a large class of stochastic epidemic models with demographic noise, including the Susceptible-Infected-Recovered (SIR) model and its general extensions.

Ergodicity breaking in area-restricted search of avian predators

no code implementations27 Jan 2021 Ohad Vilk, Yotam Orchan, Motti Charter, Nadav Ganot, Sivan Toledo, Ran Nathan, Michael Assaf

Quantifying and comparing patterns of dynamical ecological systems require averaging over measurable quantities.

Reconstructing an epigenetic landscape using a genetic `pulling' approach

no code implementations24 Sep 2019 Michael Assaf, Shay Be'er, Elijah Roberts

We derive the mathematical theory needed and then use the method on simulated data to reconstruct the landscapes.

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