Effective equilibrium states in mixtures of active particles driven by colored noise

Wittmann, René; Brader, Joseph M.; Sharma, Abhinav; Marconi, Umberto Marini Bettolo

doi:10.1103/physreve.97.012601

Cited by 36 publications

(25 citation statements)

References 60 publications

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“…We consider a well-known scheme to describe the behavior of self-propelled particles, the Active Ornstein-Uhlenbeck (AOUP) model [39][40][41][42][43][44][45][46] (also known as Gaussian Colored Noise (GCN)). The AOUP has been employed to reproduce the phenomenology of passive colloids immersed in a bath of active particles [47][48][49][50] but also-perhaps at a more approximate level-the dynamics of self-propelled particles themselves.…”

Section: Self-propelled Particlesmentioning

confidence: 99%

Fluctuation–Dissipation Relations in Active Matter Systems

2021

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We investigate the non-equilibrium character of self-propelled particles through the study of the linear response of the active Ornstein–Uhlenbeck particle (AOUP) model. We express the linear response in terms of correlations computed in the absence of perturbations, proposing a particularly compact and readable fluctuation–dissipation relation (FDR): such an expression explicitly separates equilibrium and non-equilibrium contributions due to self-propulsion. As a case study, we consider non-interacting AOUP confined in single-well and double-well potentials. In the former case, we also unveil the effect of dimensionality, studying one-, two-, and three-dimensional dynamics. We show that information about the distance from equilibrium can be deduced from the FDR, putting in evidence the roles of position and velocity variables in the non-equilibrium relaxation.

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Section: Self-propelled Particlesmentioning

confidence: 99%

Fluctuation–Dissipation Relations in Active Matter Systems

2021

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“…We study dense systems of N interacting self-propelled particles at density ρ 0 , employing the active Ornstein-Uhlenbeck particle (AOUP) model [50][51][52][53][54][55][56][57]. The AOUP is a versatile and popular model of active matter that can reproduce many aspects of the phenomenology of self-propelled particles, including the accumulation near rigid boundaries [58][59][60][61][62] or obstacles and the motility induced phase separation (MIPS) [63].…”

Section: Modelmentioning

confidence: 99%

Time-dependent properties of interacting active matter: Dynamical behavior of one-dimensional systems of self-propelled particles

Caprini

Marconi

2020

Phys. Rev. Research

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We study an interacting high-density one-dimensional system of self-propelled particles described by the active Ornstein-Uhlenbeck particle model where, even in the absence of alignment interactions, velocity and energy domains spontaneously form in analogy with those already observed in two dimensions. Such domains are regions where the individual velocities are spatially correlated as a result of the interplay between self-propulsion and interactions. Their typical size is controlled by a characteristic correlation length. In this work, we focus on a lesser-known aspect of the model, namely, its dynamical behavior. To this purpose, we investigate theoretically and numerically the time-dependent velocity autocorrelation and spatiotemporal velocity correlation functions. The study of these correlations provides a measure of the average lifetime and, thus, the stability in time of the velocity domains.

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“…However, the ABP model has not been implemented in the computational study of active/active systems. Instead, other means of activity have been examined: mixtures of active rotors [33,34], particles propelled by distinct colored noise [35], polymers and colloids equilibrating with distinct heat baths [36][37][38] or in systems of monodisperse ABPs with moving obstacles [39]. While there is a lot of work on monodisperse ABPs and more recently on mixtures of active and passive particles, the ABP model has not yet been applied to mixtures of active particles with distinct, non-zero, activity.…”

Section: Introductionmentioning

confidence: 99%

Active binary mixtures of fast and slow hard spheres

Kolb

Klotsa

2020

Soft Matter

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We computationally studied the phase behavior and dynamics of binary mixtures of active particles, where each 'species' had distinct activities leading to distinct velocities, fast and slow. We obtained phase diagrams demonstrating motility-induced phase separation (MIPS) upon varying the activity and concentration of each species, and extended current kinetic theory of active/passive mixtures to active/active mixtures. We discovered two regimes of behavior quantified through the participation of each species in the dense phase compared to their monodisperse counterparts. In regime I (active/passive and active/weakly-active), we found that the dense phase was segregated by particle type into domains of fast and slow particles. Moreover, fast particles were suppressed from entering the dense phase while slow particles were enhanced entering the dense phase, compared to monodisperse systems of all-fast or all-slow particles. These effects decayed asymptotically as the activity of the slow species increased, approaching the activity of the fast species until they were negligible (regime II). In regime II, the dense phase was homogeneously mixed and each species participated in the dense phase as if it were it a monodisperse system; each species behaved as if it weren't mixed at all. Finally, we collapsed our data defining two quantities that measure the total activity of the system. We thus found expressions that predict, a priori, the percentage of each particle type that participates in the dense phase through MIPS.

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Effective equilibrium states in mixtures of active particles driven by colored noise

Cited by 36 publications

References 60 publications

Fluctuation–Dissipation Relations in Active Matter Systems

Fluctuation–Dissipation Relations in Active Matter Systems

Time-dependent properties of interacting active matter: Dynamical behavior of one-dimensional systems of self-propelled particles

Active binary mixtures of fast and slow hard spheres

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