Dynamical phase transition in drifted Brownian motion

Nyawo, Pelerine Tsobgni; Touchette, Hugo

doi:10.1103/physreve.98.052103

Cited by 60 publications

(50 citation statements)

References 77 publications

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“…For the residence-time fluctuations, our main conclusion is the robustness of the dynamical phase transition observed by Nyawo and Touchette [34] for biased Brownian motion in continuous 1D space. One advantage of studying this observable on the lattice (as opposed to the continuum) is that we were able to obtain an explicit expression for the rate function that applies to the ARW.…”

Section: Discussionmentioning

confidence: 61%

A comparison of dynamical fluctuations of biased diffusion and run-and-tumble dynamics in one dimension

Mallmin¹,

Blythe²,

Evans³

2019

J. Phys. A: Math. Theor.

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We compare the fluctuations in the velocity and in the fraction of time spent at a given position for minimal models of a passive and an active particle: an asymmetric random walker and a run-and-tumble particle in continuous time and on a 1D lattice. We compute rate functions and effective dynamics conditioned on large deviations for these observables. While generally different, for a unique and non-trivial choice of rates (up to a rescaling of time) the velocity rate functions for the two models become identical, whereas the effective processes generating the fluctuations remain distinct. This equivalence coincides with a remarkable parity of the spectra of the processes' generators. For the occupation-time problem, we show that both the passive and active particles undergo a prototypical dynamical phase transition when the average velocity is non-vanishing in the long-time limit.Submitted to J. Phys. A: Math. Theor.

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Section: Discussionmentioning

confidence: 61%

A comparison of dynamical fluctuations of biased diffusion and run-and-tumble dynamics in one dimension

Mallmin¹,

Blythe²,

Evans³

2019

J. Phys. A: Math. Theor.

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“…Yet, a systematic procedure allows one to potentially infer an auxiliary dynamics which effectively realizes the constraint on trajectories [81][82][83]. The auxiliary dynamics considered previously are for exclusion processes [84][85][86][87], particle-based diffusive systems restricted to small noise regimes [88,89] and non-interacting cases in specific potentials [90][91][92]. Interestingly, recent works have also put forward explicit solutions in active systems for a mean-field dynamics [93] and for a many-body dynamics with pair-wise forces [36].…”

Section: Phase Transitions In Biased Ensemblesmentioning

confidence: 99%

Dissipation controls transport and phase transitions in active fluids: mobility, diffusion and biased ensembles

Fodor¹,

Nemoto²,

Vaikuntanathan³

2020

New J. Phys.

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Active fluids operate by constantly dissipating energy at the particle level to perform a directed motion, yielding dynamics and phases without any equilibrium equivalent. The emerging behaviors have been studied extensively, yet deciphering how local energy fluxes control the collective phenomena is still largely an open challenge. We provide generic relations between the activity-induced dissipation and the transport properties of an internal tracer. By exploiting a mapping between active fluctuations and disordered driving, our results reveal how the local dissipation, at the basis of self-propulsion, constrains internal transport by reducing the mobility and the diffusion of particles. Then, we employ techniques of large deviations to investigate how interactions are affected when varying dissipation. This leads us to shed light on a microscopic mechanism to promote clustering at low dissipation, and we also show the existence of collective motion at high dissipation. Overall, these results illustrate how tuning dissipation provides an alternative route to phase transitions in active fluids.

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“…In practice, computing G is a highly non-trivial procedure for many-body systems. The explicit solutions considered so far concern either exclusion processes [102][103][104] or particle-based diffusive systems restricted to small noise regimes [105,106] and non-interacting cases in some specific potentials [107][108][109].…”

Section: B Dynamical Bias and Modified Interactionsmentioning

confidence: 99%

How Dissipation Constrains Fluctuations in Nonequilibrium Liquids: Diffusion, Structure, and Biased Interactions

et al. 2019

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The dynamics and structure of nonequilibrium liquids, driven by non-conservative forces which can be either external or internal, generically hold the signature of the net dissipation of energy in the thermostat. Yet, disentangling precisely how dissipation changes collective effects remains challenging in many-body systems due to the complex interplay between driving and particle interactions. First, we combine explicit coarse-graining and stochastic calculus to obtain simple relations between diffusion, density correlations and dissipation in nonequilibrium liquids. Based on these results, we consider large-deviation biased ensembles where trajectories mimic the effect of an external drive. The choice of the biasing function is informed by the connection between dissipation and structure derived in the first part. Using analytical and computational techniques, we show that biasing trajectories effectively renormalizes interactions in a controlled manner, thus providing intuition on how driving forces can lead to spatial organization and collective dynamics. Altogether, our results show how tuning dissipation provides a route to alter the structure and dynamics of liquids and soft materials. arXiv:1808.07838v4 [cond-mat.stat-mech]

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Dynamical phase transition in drifted Brownian motion

Cited by 60 publications

References 77 publications

A comparison of dynamical fluctuations of biased diffusion and run-and-tumble dynamics in one dimension

A comparison of dynamical fluctuations of biased diffusion and run-and-tumble dynamics in one dimension

Dissipation controls transport and phase transitions in active fluids: mobility, diffusion and biased ensembles

How Dissipation Constrains Fluctuations in Nonequilibrium Liquids: Diffusion, Structure, and Biased Interactions

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