Showing papers by "Udo Seifert published in 2014"
TL;DR: Stochastic thermodynamics is generalized to the presence of an information reservoir and it is shown that both the entropy production involving mutual information between system and controller and the one involving a Shannon entropy difference of an Information reservoir like a tape carry an extra term different from the usual current times affinity.
Abstract: So far, feedback-driven systems have been discussed using (i) measurement and control, (ii) a tape interacting with a system, or (iii) by identifying an implicit Maxwell demon in steady-state transport. We derive the corresponding second laws from one master fluctuation theorem and discuss their relationship. In particular, we show that both the entropy production involving mutual information between system and controller and the one involving a Shannon entropy difference of an information reservoir like a tape carry an extra term different from the usual current times affinity. We, thus, generalize stochastic thermodynamics to the presence of an information reservoir.
140 citations
TL;DR: In this paper, it was shown that the rate at which a receptor learns about the external environment can be nonzero even without any dissipation inside the cell since chemical work done by the external process compensates for this learning rate.
Abstract: We show that a rate of conditional Shannon entropy reduction, characterizing the learning of an internal process about an external process, is bounded by the thermodynamic entropy production. This approach allows for the definition of an informational efficiency that can be used to study cellular information processing. We analyze three models of increasing complexity inspired by the Escherichia coli sensory network, where the external process is an external ligand concentration jumping between two values. We start with a simple model for which ATP must be consumed so that a protein inside the cell can learn about the external concentration. With a second model for a single receptor we show that the rate at which the receptor learns about the external environment can be nonzero even without any dissipation inside the cell since chemical work done by the external process compensates for this learning rate. The third model is more complete, also containing adaptation. For this model we show inter alia that a bacterium in an environment that changes at a very slow time-scale is quite inefficient, dissipating much more than it learns. Using the concept of a coarse-grained learning rate, we show for the model with adaptation that while the activity learns about the external signal the option of changing the methylation level increases the concentration range for which the learning rate is substantial.
127 citations
TL;DR: In this paper, the authors consider the stationary state of a bipartite system from the perspective of stochastic thermodynamics and obtain integral fluctuation theorem involving the transfer entropy from one subsystem to the other.
Abstract: We consider the stationary state of a Markov process on a bipartite system from the perspective of stochastic thermodynamics. One subsystem is used to extract work from a heat bath while being affected by the second subsystem. We show that the latter allows for a transparent and thermodynamically consistent interpretation of a Maxwell's demon. Moreover, we obtain an integral fluctuation theorem involving the transfer entropy from one subsystem to the other. Comparing three different inequalities, we show that the entropy decrease of the first subsystem provides a tighter bound on the rate of extracted work than either the rate of transfer entropy from this subsystem to the demon or the heat dissipated through the dynamics of the demon. The latter two rates cannot be ordered by an inequality, as shown with the illustrative example of a four state system.
122 citations
TL;DR: In this paper, the authors consider the stationary state of a bipartite system from the perspective of stochastic thermodynamics and show that the entropy decrease of the first subsystem provides a tighter bound on the rate of extracted work than both the transfer entropy from this subsystem to the demon and the heat dissipated through the dynamics of the demon.
Abstract: We consider the stationary state of a Markov process on a bipartite system from the perspective of stochastic thermodynamics. One subsystem is used to extract work from a heat bath while being affected by the second subsystem. We show that the latter allows for a transparent and thermodynamically consistent interpretation of a Maxwell's demon. Moreover, we obtain an integral fluctuation theorem involving the transfer entropy from one subsystem to the other. Comparing three different inequalities, we show that the entropy decrease of the first subsystem provides a tighter bound on the rate of extracted work than both the rate of transfer entropy from this subsystem to the demon and the heat dissipated through the dynamics of the demon. The latter two rates cannot be ordered by an inequality as shown with the illustrative example of a four state system.
115 citations
TL;DR: It is shown that a rate of conditional Shannon entropy reduction, characterizing the learning of an internal process about an external process, is bounded by the thermodynamic entropy production, which allows for the definition of an informational efficiency that can be used to study cellular information processing.
Abstract: We show that a rate of conditional Shannon entropy reduction, characterizing the learning of an internal process about an external process, is bounded by the thermodynamic entropy production. This approach allows for the definition of an informational efficiency that can be used to study cellular information processing. We analyze three models of increasing complexity inspired by the E. coli sensory network, where the external process is an external ligand concentration jumping between two values. We start with a simple model for which ATP must be consumed so that a protein inside the cell can learn about the external concentration. With a second model for a single receptor we show that the rate at which the receptor learns about the external environment can be nonzero even without any dissipation inside the cell since chemical work done by the external process compensates for this learning rate. The third model is more complete, also containing adaptation. For this model we show inter alia that a bacterium in an environment that changes at a very slow time-scale is quite inefficient, dissipating much more than it learns. Using the concept of a coarse-grained learning rate, we show for the model with adaptation that while the activity learns about the external signal the option of changing the methylation level increases the concentration range for which the learning rate is substantial.
112 citations
TL;DR: The dynamical behavior of giant fluid vesicles in various types of external hydrodynamic flow is reviewed, finding that in linear flows with both rotational and elongational components, the properties of the tank-treading and tumbling motions are well described by theoretical and numerical models.
104 citations
TL;DR: An inequality is obtained that can derive an information processing entropy production, which gives the second law in the presence of information reservoirs, and a systematic linear response theory for information processing machines is developed.
Abstract: We generalize stochastic thermodynamics to include information reservoirs. Such information reservoirs, which can be modeled as a sequence of bits, modify the second law. For example, work extraction from a system in contact with a single heat bath becomes possible if the system also interacts with an information reservoir. We obtain an inequality, and the corresponding fluctuation theorem, generalizing the standard entropy production of stochastic thermodynamics. From this inequality we can derive an information processing entropy production, which gives the second law in the presence of information reservoirs. We also develop a systematic linear response theory for information processing machines. For a unicyclic machine powered by an information reservoir, the efficiency at maximum power can deviate from the standard value of 1/2. For the case where energy is consumed to erase the tape, the efficiency at maximum erasure rate is found to be 1/2.
82 citations
TL;DR: A microscopic model invoking classical particle trajectories subject to the Lorentz force is introduced, and a universal bound 3-2√2≃0.172 for the ratio between the maximum efficiency and the Carnot efficiency is proved.
Abstract: An analytically solvable model for a heat engine based on the Nernst effect - where an electric voltage is generated perpendicular to a heat current in the presence of a magnetic field - yields an upper bound on the efficiency.
34 citations
TL;DR: This work shows that a full understanding of the implications of the continuous interactions of fluid membranes with a scaffold can be achieved only by expanding the standard superposition models commonly used to treat these types of systems, beyond the usual harmonic level of description.
Abstract: The interaction of fluid membranes with a scaffold, which can be a planar surface or a more complex structure, is intrinsic to a number of systems - from artificial supported bilayers and vesicles to cellular membranes. In principle, these interactions can be either discrete and protein mediated, or continuous. In the latter case, they emerge from ubiquitous intrinsic surface interaction potentials as well as nature-designed steric contributions of the fluctuating membrane or from the polymers of the glycocalyx. Despite the fact that these nonspecific potentials are omnipresent, their description has been a major challenge from experimental and theoretical points of view. Here we show that a full understanding of the implications of the continuous interactions can be achieved only by expanding the standard superposition models commonly used to treat these types of systems, beyond the usual harmonic level of description. Supported by this expanded theoretical framework, we present three independent, yet mutually consistent, experimental approaches to measure the interaction potential strength and the membrane tension. Upon explicitly taking into account the nature of shot noise as well as of finite experimental resolution, excellent agreement with the augmented theory is obtained, which finally provides a coherent view of the behavior of the membrane in a vicinity of a scaffold.
23 citations
TL;DR: A new method is presented to measure the association rate k(on) of ligand-receptor pairs incorporated into lipid membranes and it is found that the k( on) for the interaction of biotin with neutravidin is larger than that for integrin binding to RGD or sialyl Lewis(x) to E-selectin.
23 citations
TL;DR: By considering subexponential contributions in large deviation theory, this approach determines the fine structure in the probability distribution of the observable displacement of a bead coupled to a molecular motor, revealing a discrete symmetry of this distribution for which hidden degrees of freedom lead to a periodic modulation of the slope typically associated with the fluctuation theorem.
Abstract: By considering subexponential contributions in large deviation theory, we determine the fine structure in the probability distribution of the observable displacement of a bead coupled to a molecular motor. More generally, for any stochastic motion along a periodic substrate, this approach reveals a discrete symmetry of this distribution for which hidden degrees of freedom lead to a periodic modulation of the slope typically associated with the fluctuation theorem. Contrary to previous interpretations of experimental data, the mean force exerted by a molecular motor is unrelated to the long-time asymptotics of this slope and must rather be extracted from its short-time limit.
TL;DR: In this paper, a combination of state-of-the-art experimental tools and theoretical modeling is used to gain valuable knowledge of the interaction between membrane-membrane or membrane-substrate interaction.
Abstract: Cell-cell or cell-substrate adhesion was long thought to be controlled only by protein molecules embedded in the cell membrane, but more recently, the little-understood membrane-membrane or membrane-substrate interaction has been added to the mix. Scientists deploy a combination of state-of-the-art experimental tools and theoretical modeling to gain valuable knowledge of this interaction.
TL;DR: It is shown that the optimized model leads to more work extraction in comparison to the memory-less model, with the gain parameter being larger in the region where the frequency of non-reliable measurements is higher and the model has two second law inequalities.
Abstract: We analyze a periodic optimal finite-time two-state information-driven machine that extracts work from a single heat bath exploring imperfect measurements. Two models are considered, a memory-less one that ignores past measurements and an optimized model for which the feedback scheme consists of a protocol depending on the whole history of measurements. Depending on the precision of the measurement and on the period length, the optimized model displays a phase transition to a phase where measurements are judged as non-reliable. We obtain the critical line exactly and show that the optimized model leads to more work extraction in comparison to the memory-less model, with the gain parameter being larger in the region where the frequency of non-reliable measurements is higher. We also demonstrate that the model has two second law inequalities, with the extracted work being bounded by the change of the entropy of the system and by the mutual information.
TL;DR: In this article, the authors present experimental observations and numerical simulations of a wrinkling instability that occurs at sufficiently high strain rates in the trembling regime of vesicle dynamics in steady linear flow.
Abstract: We present experimental observations and numerical simulations of a wrinkling instability that occurs at sufficiently high strain rates in the trembling regime of vesicle dynamics in steady linear flow. Spectral and statistical analysis of the data shows similarities and differences with the wrinkling instability observed earlier for vesicles in transient elongation flow. The critical relevance of thermal fluctuations for this phenomenon is revealed by a simple model using coupled Langevin equations that reproduces the experimental observations quite well.
TL;DR: By considering subexponential contributions in large deviation theory, the fine structure in the probability distribution of the observable displacement of a bead coupled to a molecular motor was determined in this paper, revealing a discrete symmetry of this distribution for which hidden degrees of freedom lead to a periodic modulation of the slope typically associated with the fluctuation theorem.
Abstract: By considering subexponential contributions in large deviation theory, we determine the fine structure in the probability distribution of the observable displacement of a bead coupled to a molecular motor. More generally, for any stochastic motion along a periodic substrate, this approach reveals a discrete symmetry of this distribution for which hidden degrees of freedom lead to a periodic modulation of the slope typically associated with the fluctuation theorem. Contrary to previous interpretations of experimental data, the mean force exerted by a molecular motor is unrelated to the long-time asymptotics of this slope and must rather be extracted from its short-time limit.