Adherent cells ensure membrane homeostasis during de-adhesion by various mechanisms, including endocytosis. Although mechano-chemical feedbacks involved in this process have been studied, the step-by-step build-up and resolution of the mechanical changes by endocytosis are poorly understood. To investigate this, we studied the de-adhesion of HeLa cells using a combination of interference reflection microscopy, optical trapping and fluorescence experiments. We found that de-adhesion enhanced membrane height fluctuations of the basal membrane in the presence of an intact cortex. A reduction in the tether force was also noted at the apical side. However, membrane fluctuations reveal phases of an initial drop in effective tension followed by saturation. The area fractions of early (Rab5-labelled) and recycling (Rab4-labelled) endosomes, as well as transferrin-labelled pits close to the basal plasma membrane, also transiently increased. On blocking dynamin-dependent scission of endocytic pits, the regulation of fluctuations was not blocked, but knocking down AP2-dependent pit formation stopped the tension recovery. Interestingly, the regulation could not be suppressed by ATP or cholesterol depletion individually but was arrested by depleting both. The data strongly supports Clathrin and AP2-dependent pit-formation to be central to the reduction in fluctuations confirmed by super-resolution microscopy. Furthermore, we propose that cholesterol-dependent pits spontaneously regulate tension under ATP-depleted conditions.

For arbitrary nonequilibrium transformations in complex systems, we show that the distance between the current state and a target state can be decomposed into two terms: one corresponding to an independent estimate of the distance, and another corresponding to interactions, quantified using the relative mutual information between the variables. This decomposition is a special case of a more general decomposition involving successive orders of correlation or interactions among the degrees of freedom of the system. To illustrate its practical significance, we study the thermal relaxation of two interacting, optically trapped colloidal particles, where increasing pairwise interaction strength is shown to prolong the longevity of the time-dependent nonequilibrium state. Additionally, we study a system with both pairwise and triplet interactions, where our approach identifies their distinct contributions to the transformation. In more general setups where it is possible to control the strength of different orders of interactions, our findings provide a way to disentangle their effects and identify interactions that facilitate the transformation.

Here we explore the possibility of precise time keeping in quantum systems using athermal resources. We show that quantum measurement engineered reservoirs can be used as athermal resources to drive the ticks of a quantum clock. Two- and three-level quantum systems act as transducers in our model, converting the quantum measurement-induced noise to produce a series of ticks. The ticking rate of the clock is maximized when the measured observable maximally noncommutes with the clock's Hamiltonian. We use the large deviation principle to characterize the statistics of observed ticks within a given time period and show that it can be sub-Poissonian—quantified by Mandel's Q parameter—alluding to the quantum nature of the clock. We discuss the accuracy and efficiency of the clock, and extend our framework to include hybrid quantum clocks fueled by both measurements, and thermal resources. We make comparisons to relatable recent proposals for quantum clocks, and discuss alternate device implementations harvesting the quantum measurement engineered nonequilibrium conditions, beyond the clock realization.

The rate of entropy production provides a useful quantitative measure of a non-equilibrium system and estimating it directly from time-series data from experiments is highly desirable. Several approaches have been considered for stationary dynamics, some of which are based on a variational characterization of the entropy production rate. However, the issue of obtaining it in the case of non-stationary dynamics remains largely unexplored. Here, we solve this open problem by demonstrating that the variational approaches can be generalized to give the exact value of the entropy production rate even for non-stationary dynamics. On the basis of this result, we develop an efficient algorithm that estimates the entropy production rate continuously in time by using machine learning techniques and validate our numerical estimates using analytically tractable Langevin models in experimentally relevant parameter regimes. Our method only requires time-series data for the system of interest without any prior knowledge of the system’s parameters.

A nonvanishing entropy production rate is one of the defining characteristics of any nonequilibrium system, and several techniques exist to determine this quantity directly from experimental data. The short-time inference scheme, derived from the thermodynamic uncertainty relation, is a recent addition to the list of these techniques. Here we apply this scheme to quantify the entropy production rate in a class of microscopic heat engine models called Brownian gyrators. In particular, we consider models with anharmonic confining potentials. In these cases, the dynamical equations are indelibly nonlinear, and the exact dependencies of the entropy production rate on the model parameters are unknown. Our results demonstrate that the short-time inference scheme can efficiently determine these dependencies from a moderate amount of trajectory data. Furthermore, the results show that the nonequilibrium properties of the gyrator model with anharmonic confining potentials are considerably different from its harmonic counterpart; especially in setups leading to a nonequilibrium dynamics and the resulting gyration patterns.

Measurements of any property of a microscopic system are bound to show significant deviations from the average, due to thermal fluctuations. For time-integrated currents such as heat, work, or entropy production in a steady state, it is in fact known that there will be long stretches of fluctuations both above as well as below the average, occurring equally likely at large times. In this paper we demonstrate that for any finite-time measurement in a nonequilibrium steady state—rather counterintuitively—fluctuations below the average are more probable. This discrepancy is found to be higher when the system is further away from equilibrium. For overdamped diffusive processes, there is even an optimal time when time-integrated current fluctuations mostly lie below the average. We demonstrate that these effects are consistent with a nonmonotonic skewness of current fluctuations and provide evidence that they are easily observable in experiments. We also discuss their extensions to discrete space Markov jump processes and implications to biological and synthetic microscopic engines.

A recent work [A. Lapolla and A. Godec, Phys. Rev. Lett. 125, 110602 (2020)] showed that among a pair of thermodynamically equidistant quenches from a colder and a hotter initial state at a fixed ambient temperature, the relaxation from the colder initial state (uphill relaxation) is always faster, for dynamics close to stable minima. Here we show that this is not generically the case for open quantum systems with two or three energy levels. We find that both faster uphill and faster downhill relaxation and symmetric thermal relaxation can be observed in equidistant quenches, depending on the transition rates and the choice of the distance measure used. Furthermore, we obtain a phase diagram in the parameter space for the three-level system corresponding to different thermalization behaviors.

Estimating entropy production directly from experimental trajectories is of great current interest but often requires a large amount of data or knowledge of the underlying dynamics. In this paper, we propose a minimal strategy using the short-time Thermodynamic Uncertainty Relation (TUR) by means of which we can simultaneously and quantitatively infer the thermodynamic force field acting on the system and the (potentially exact) rate of entropy production from experimental short-time trajectory data. We benchmark this scheme first for an experimental study of a colloidal particle system where exact analytical results are known, prior to studying the case of a colloidal particle in a hydrodynamical flow field, where neither analytical nor numerical results are available. In the latter case, we build an effective model of the system based on our results. In both cases, we also demonstrate that our results match with those obtained from another recently introduced scheme.

We provide a strategy for the exact inference of the average as well as the fluctuations of the entropy production in nonequilibrium systems in the steady state, from the measurements of arbitrary current fluctuations. Our results are built upon the finite-time generalization of the thermodynamic uncertainty relation, and require only very short time series data from experiments. We illustrate our results with exact and numerical solutions for two colloidal heat engines.

An inherent feature of small systems in contact with thermal reservoirs, be it a pollen grain in water, or an active microbe flagellum, is fluctuations. Even with advanced microscopic techniques, distinguishing active, non-equilibrium processes defined by a constant dissipation of energy to the environment from passive, equilibrium processes is a very challenging task and a vastly developing field of research. For small (microscopic) systems in contact with thermal reservoirs, the experimental / theoretic framework that addresses these fundamental questions, is called stochastic thermodynamics.

In this thesis, we study the stochastic thermodynamics of microscopic machines with colloidal particles as working substances. In particular, we use a path integral based framework to characterize the fluctuations of thermodynamic observables, such as Work, Heat and Entropy production in colloidal heat engines. We obtain exact analytic solutions at finite operational times and the results reveal model independent features of Work and Efficiency fluctuations.

We also discuss the thermodynamic uncertainty relations, which relate current fluctuations in non-equilibrium steady states to the average rate of entropy production. Based on this relation, as well as exact analytical solutions for explicit models, we propose a simple and effective way to infer dissipation from current fluctuations in non-equilibrium systems, from short empirical trajectories.

Finally, we conclude with a discussion on possible extensions of our results.