Number fluctuation signals N(t) distinguish self-propelled particle models via differences in reorientation dynamics.
Ramaswamy, The mechanics and statistics of active matter, Annual Review of Condensed Matter Physics1, 323 (2010)
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Exact solution for anisotropic mobility in trapped self-propelled particles yields non-monotonic negative excess kurtosis and a strictly sub-Gaussian steady-state distribution that displaces the particle into high-potential regions.
Self-propulsion noise statistics define speed limits on non-equilibrium transitions in active matter, with non-stationary initials allowing faster cooling than passive protocols.
A projection-operator perturbative framework yields an analytic transition rate for rare events in 1D active particles that is accurate across all persistence times via a rational approximation of the small- and large-persistence asymptotics.
An agent-based model with orientation-weighted velocity-dependent alignment generates disordered, flocking, jammed, and active-crystal-like collective phases by varying alignment strength.
citing papers explorer
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Number fluctuations distinguish different self-propelling dynamics
Number fluctuation signals N(t) distinguish self-propelled particle models via differences in reorientation dynamics.
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Mobility Anisotropy Reshapes Self-Propelled Motion
Exact solution for anisotropic mobility in trapped self-propelled particles yields non-monotonic negative excess kurtosis and a strictly sub-Gaussian steady-state distribution that displaces the particle into high-potential regions.
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Self-propulsion protocols for swift non-equilibrium state transitions and enhanced cooling in active systems
Self-propulsion noise statistics define speed limits on non-equilibrium transitions in active matter, with non-stationary initials allowing faster cooling than passive protocols.
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General perturbative framework for kinetics of rare transitions in 1-dimensional active particle systems
A projection-operator perturbative framework yields an analytic transition rate for rare events in 1D active particles that is accurate across all persistence times via a rational approximation of the small- and large-persistence asymptotics.
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Collective dynamics of active matter with orientation-weighted alignment
An agent-based model with orientation-weighted velocity-dependent alignment generates disordered, flocking, jammed, and active-crystal-like collective phases by varying alignment strength.