Non-Boltzmann stationary distributions and nonequilibrium relations in active baths

Abstract

Most natural and engineered processes, such as biomolecular reactions, protein folding, and population dynamics, occur far from equilibrium and therefore cannot be treated within the framework of classical equilibrium thermodynamics. Here we experimentally study how some fundamental thermodynamic quantities and relations are affected by the presence of the nonequilibrium fluctuations associated with an active bath. We show in particular that, as the confinement of the particle increases, the stationary probability distribution of a Brownian particle confined within a harmonic potential becomes non-Boltzmann, featuring a transition from a Gaussian distribution to a heavy-tailed distribution. Because of this, nonequilibrium relations (e.g., the Jarzynski equality and Crooks fluctuation theorem) cannot be applied. We show that these relations can be restored by using the effective potential associated with the stationary probability distribution. We corroborate our experimental findings with theoretical arguments.

Enhanced diffusion, swelling, and slow reconfiguration of a single chain in non-Gaussian active bath

“…Our model explicitly accounts for the run-and-tumble motion of bacteria in addition to the directionality of the kicks, using a shot noise, non-Gaussian in nature. sufficiently small (< τ relax τA ), a transition from Gaussian to non-Gaussian active noise is predicted which is consistent with experimental observation by Volpe et al [27]. We find, MSD of COM and end-to-end distance grow faster due to collisions from active particles and can even be superdiffusive at higher activity as observed recently in case of active enzymes [7].…”

“…τA which is structurally same as the noise autocorrelation for run and tumble motion, (∆τ − |t ′ − t ′′ |)Θ(∆τ − |t ′ − t ′′ |). Thus for large correlation time (τ A ) introduced by the active noise, a transition from Gaussian to non-Gaussian active noise is expected as predicted by Volpe et al [27].…”

“…In all of these theoretical studies, the active noise was modeled as Gaussian random variable. However, this Gaussian approximation works well when the density of the active particles is very low [25,26] or the local relaxation time (τ relax ) is greater than the correlation time (τ A ) of the active noise [27]. For harmonic motion, τ relax = γ k where γ is friction coefficient and k is spring constant.…”

Metastable clusters and channels formed by active particles with aligning interactions

“…It is interesting to explore the mutual influence between active and passive particles in hybrid systems because several natural and artificial systems feature both kinds of particles. In fact, such mixtures have already been explored in several works both experimentally [27][28][29][30][31] and theoretically [23,24,[32][33][34]. We will therefore extend the model presented in the previous section by also including M passive particles, which interact with all other (active and passive) particles through volume exclusion and are subject to translational diffusion.…”

Microparticle transport networks with holographic optical tweezers and cavitation bubbles

“…Other particles can catalize chemical reactions [12] for self propulsion like platinum-copper nanorods immersed in dilute Br 2 or I 2 solutions (self-electrophoresis) [13]. Living bacteria have also been used as active particles or as active baths that interact with artificial microbeads [14].…”