activity
20032023
most citedActive Brownian Particles. From Individual to Collective Stochastic Dynamics

1.1k citations · 1.5k across the 22 of their papers we have counts for

collaborators

23 papers

physics.bio-ph2023

Detecting a periodic signal by a population of spiking neurons in the weakly nonlinear response regime

Maria Schlungbaum, Benjamin Lindner

Motivated by experimental observations, we investigate a variant of the cocktail party problem: the detection of a weak periodic stimulus in the presence of fluctuations and anothe…

cond-mat.stat-mech2023

The active Boltzmann equation: From dilute collisions to exact kinetic theory

Thomas Ihle, Horst-Holger Boltz, Rüdiger Kürsten +1

We construct an exact kinetic theory for dilute aligning self-propelled particles by closing the BBGKY hierarchy non-locally, retaining the pair correlations during each collision.…

cond-mat.stat-mech2023

Asymptotically exact scattering theory of the Kuramoto-Vicsek model

Thomas Ihle, Horst-Holger Boltz, Rüdiger Kürsten +1

We consider the Kuramoto-Vicsek model of self-propelled particles with velocity-alignment interactions. Starting from the exact -particle Liouville equation, a kinetic equation…

nlin.AO2023★ 24 cited

A Universal Description of Stochastic Oscillators

Alberto Pérez-Cervera, Boris Gutkin, Peter J. Thomas +1

Many systems in physics, chemistry and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for exampl…

q-bio.NC2022★ 2 cited

Theory of the asynchronous state of structured rotator networks and its application to recurrent networks of excitatory and inhibitory units

Jonas Ranft, Benjamin Lindner

Recurrently coupled oscillators that are sufficiently heterogeneous and/or randomly coupled can show an asynchronous activity in which there are no significant correlations among t…

q-bio.NC2022

A self-consistent analytical theory for rotator networks under stochastic forcing: effects of intrinsic noise and common input

Jonas Ranft, Benjamin Lindner

Despite the incredible complexity of our brains' neural networks, theoretical descriptions of neural dynamics have led to profound insights into possible network states and dynamic…