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Karel Proesmans

Publications and source records attributed to Karel Proesmans.

At least 19 recordsLinked to original sources

Exact Mapping of Nonequilibrium to Equilibrium Phase Transitions for Systems in Contact with Two Thermal Baths

We show that a large class of nonequilibrium many-body systems in contact with two thermal baths admit an exact mapping onto equivalent equilibrium systems. This mapping provides direct access to nonequilibrium phase transition points from known equilibrium results, irrespective of the model, interaction topology, or distance from equilibrium. We verify the universality of this correspondence using paradigmatic models (Ising, Potts, and Blume-Capel), and highlight distinctive features in entropy production close to critical and tricritical points. Our findings connect equilibrium and nonequilibrium statistical mechanics, with implications for microscopic thermal machines and stochastic thermodynamics.

cond-mat.stat-mech

Identifying non-equilibrium fluctuations in Intracellular Motion Using Recurrent Neural Networks

Distinguishing active from passive dynamics is a fundamental challenge in understanding the motion of living cells and other active matter systems. Here, we introduce a framework that combines physical modeling, analytical theory, and machine learning to identify and characterize active fluctuations from trajectory data. We train a long short-term memory (LSTM) neural network on synthetic trajectories generated from well-defined stochastic models of active particles, enabling it to classify motion as passive or active and to infer the underlying active process. Applied to experimental trajectories of a tracer in the cytoplasm of a living cell, the method robustly identifies actively driven motion and selects an Ornstein-Uhlenbeck active noise model as the best description. Crucially, the classifier's performance on simulated data approaches the theoretical optimum that we derive, and it also yields accurate estimates of the active diffusion coefficient. This integrated approach opens a powerful route to quantify non-equilibrium fluctuations in complex biological systems from limited data.

cond-mat.stat-mech

Insertion space in repulsive active matter

For equilibrium hard spheres, the statistical geometry of the insertion space, the room to accommodate another sphere, relates exactly to the equation of state. We begin to extend this idea to active matter, analyzing the insertion space for repulsive active particles in one and two dimensions using both on- and off-lattice models. In one dimension, we derive closed-form expressions for the mean insertion cavity size, cavity number, and total insertion volume, all in excellent agreement with simulations. Strikingly, activity increases the total insertion volume and tends to keep the insertion space more connected. We also find that insertion space metrics contain signatures of collective phase behaviors occurring at previously predicted packing fractions. Taken together, our work provides the first quantitative foundation for the statistical geometry of active matter.

cond-mat.soft

Thermodynamic control of non-equilibrium systems

We study the thermodynamic cost associated with driving systems between different non-equilibrium steady states. In particular, we combine a linear-response framework for non-equilibrium Markov systems with Lagrangian techniques to minimize the dissipation associated with driving processes. We then apply our framework to a simple toy model. Our results show several remarkable properties for the optimal protocol, such as diverging parameters and finite entropy production in the slow-driving limit.

cond-mat.stat-mech

Quantifying dissipation in flocking dynamics: When tracking internal states matters

Aligning self-propelled particles undergo a nonequilibrium flocking transition from apolar to polar phases as their interactions become stronger. We propose a thermodynamically consistent lattice model, in which the internal state of the particles biases their diffusion, to capture such a transition. Changes of internal states and jumps between lattice sites obey local detailed balance with respect to the same interaction energy. We unveil a crossover between two regimes: for weak interactions, the dissipation is maximal, and partial inference (namely, based on discarding the dynamics of internal states) leads to a severe underestimation; for strong interactions, the dissipation is reduced, and partial inference captures most of the dissipation. Finally, we reveal that the macroscopic dissipation, evaluated at the hydrodynamic level, coincides with the microscopic dissipation upon coarse-graining. We argue that this correspondence stems from a generic mapping of active lattice models with local detailed balance into a specific class of non-ideal reaction-diffusion systems.

cond-mat.stat-mech

Positional information trade-offs in boundary-driven reaction-diffusion systems

Individual components such as cells, particles, or agents within a larger system often require detailed understanding of their relative position to act accordingly, enabling the system as a whole to function in an organised and efficient manner. Through the concept of positional information, such components are able to specify their position in order to, e.g., create robust spatial patterns or coordinate specific functionality. Such complex behaviour generally occurs far from thermodynamic equilibrium and thus requires the dissipation of free energy to sustain functionality. We show that in boundary-driven simple exclusion systems with position-dependent Langmuir kinetics, non-trivial Pareto-optimal trade-offs exist between the positional information, rescaled entropy production rate and global reaction current. Phase transitions in the optimal protocols that tune the densities of the system boundaries emerge as a result, showing that distinct protocols are able to exchange global optimality similar to phase coexistence in liquid-gas phase transitions, and that increasing the positional information can lead to diminishing returns when considering increased dissipation.

cond-mat.stat-mech

Learning optimal erasure of a Static Random Access Memory

In this paper, we study the thermodynamic cost associated with erasing a static random access memory. By combining the stochastic thermodynamics framework of electronic circuits with machine learning-based optimization techniques, we show that it is possible to erase an electronic random access memory at arbitrarily fast speed and finite heat dissipation. This disproves a widely held belief that heat dissipation scales linearly with erasure speed. Furthermore, we find driving protocols that minimize the heat dissipation, leading to explicit design principles for future computer memories. This bridges an important gap between the theoretical framework of stochastic thermodynamics and applications in electronic engineering.

cond-mat.stat-mech

Irreversibility in Non-reciprocal Chaotic Systems

How is the irreversibility of a high-dimensional chaotic system controlled by the heterogeneity in the non-reciprocal interactions among its elements? In this paper, we address this question using a stochastic model of random recurrent neural networks that undergoes a transition from quiescence to chaos at a critical heterogeneity. In the thermodynamic limit, using dynamical mean field theory, we obtain an exact expression for the averaged entropy production rate - a measure of irreversibility - for any heterogeneity level J. We show how this quantity becomes a constant at the onset of chaos while changing its functional form upon crossing this point. The latter can be elucidated by closed-form approximations valid for below and slightly above the critical point and for large J.

cond-mat.stat-mech

Limits to positional information in boundary-driven systems

Chemical gradients can be used by a particle to determine its position. This \textit{positional information} is of crucial importance, for example in developmental biology in the formation of patterns in an embryo. The central goal of this paper is to study the fundamental physical limits on how much positional information can be stored inside a system. To achieve this, we study positional information for general boundary-driven systems, and derive, in the near-equilibrium regime, a universal expression involving only the chemical potential and density gradients of the system. We also conjecture that this expression serves as an upper bound on the positional information of boundary driven systems beyond linear response. To support this claim, we test it on a broad range of solvable boundary-driven systems.

cond-mat.stat-mech

Trade-offs and thermodynamics of energy-relay proofreading

Biological processes that are able to discriminate between different molecules consume energy and dissipate heat. They operate at different levels of fidelity and speed, and as a consequence there exist fundamental trade-offs between these quantities and the entropy production rate. Usually, the energy source required to operate in a high-fidelity regime comes from the consumption of external energetic molecules, e.g., GTP hydrolysis in protein translation . In this work, we study trade-offs between several kinetic and thermodynamic observables for Hopfield's energy-relay mechanism, which does not consume external molecules and is able to operate in depleted regions, at the cost of a higher error rate. The trade-offs are obtained both analytically and numerically via Pareto optimal fronts. We find that the scheme is able to operate in three distinct regimes: an energy relay regime, a mixed relay-Michaelis-Menten regime, and a Michaelis-Menten regime, depending on the kinetic and energetic parameters that tune transitions between states. The mixed regime features a dynamical phase transition in the error-entropy production Pareto trade-off, while the pure energy relay regime contains a region where this type of proofreading energetically outperforms standard kinetic proofreading.

cond-mat.stat-mech

Work statistics at first-passage times

We investigate the work fluctuations in an overdamped non-equilibrium process that is stopped at a stochastic time. The latter is characterized by a first passage event that marks the completion of the non-equilibrium process. In particular, we consider a particle diffusing in one dimension in the presence of a time-dependent potential $U(x,t) = k |x-vt|^n/n$, where $k>0$ is the stiffness and $n>0$ is the order of the potential. Moreover, the particle is confined between two absorbing walls, located at $L_{\pm}(t) $, that move with a constant velocity $v$ and are initially located at $L_{\pm}(0) = \pm L$. As soon as the particle reaches any of the boundaries, the process is said to be completed and here, we compute the work done $W$ by the particle in the modulated trap upto this random time. Employing the Feynman-Kac path integral approach, we find that the typical values of the work scale with $L$ with a crucial dependence on the order $n$. While for $n>1$, we show that $\mom{W} \sim L^{1-n}~\exp \left[ \left( {k L^{n}}/{n}-v L \right)/D \right] $ for large $L$, we get an algebraic scaling of the form $\mom{W} \sim L^n$ for the $n<1$ case. The marginal case of $n=1$ is exactly solvable and our analysis unravels three distinct scaling behaviours: (i) $\mom{W} \sim L$ for $v>k$, (ii) $\mom{W} \sim L^2$ for $v=k$ and (iii) $\mom{W} \sim \exp\left[{-(v-k)L}\right]$ for $v<k$. For all cases, we also obtain the probability distribution associated with the typical values of $W$. Finally, we observe an interesting set of relations between the relative fluctuations of the work done and the first-passage time for different $n$ -- which we argue physically. Our results are well supported by the numerical simulations.

cond-mat.stat-mech

Universal thermodynamic bounds on the Fano factor of discriminatory networks with unidirectional transitions

We derive a universal lower bound on the Fano factors of general biochemical discriminatory networks involving irreversible catalysis steps, based on the thermodynamic uncertainty relation, and compare it to a numerically exact Pareto optimal front. This bound is completely general, involving only the reversible entropy production per product formed and the error fraction of the system. We then show that by judiciously choosing which transitions to include in the reversible entropy production, one can derive a family of bounds that can be fine-tuned to include physical observables at hand. Lastly, we test our bound by considering three discriminatory schemes: a multi-stage Michaelis-Menten network, a Michaelis-Menten network with correlations between subsequent products, and a multi-stage kinetic proofreading network, where for the latter application the bound is altered to include the hydrolytic cost of the proofreading steps. We find that our bound is remarkably tight.

cond-mat.stat-mech

Inferring entropy production from time-dependent moments

Measuring entropy production of a system directly from the experimental data is highly desirable since it gives a quantifiable measure of the time-irreversibility for non-equilibrium systems and can be used as a cost function to optimize the performance of the system. Although numerous methods are available to infer the entropy production of stationary systems, there are only a limited number of methods that have been proposed for time-dependent systems and, to the best of our knowledge, none of these methods have been applied to experimental systems. Herein, we develop a general non-invasive methodology to infer a lower bound on the mean total entropy production for arbitrary time-dependent continuous-state Markov systems in terms of the moments of the underlying state variables. The method gives surprisingly accurate estimates for the entropy production, both for theoretical toy models and for experimental bit erasure, even with a very limited amount of experimental data.

cond-mat.stat-mech

Thermodynamics of interacting systems: the role of the topology and collective effects

We will study a class of system composed of interacting unicyclic machines placed in contact with a hot and cold thermal baths subjected to a non-conservative driving worksource. Despite their simplicity, these models showcase an intricate array of phenomena, including pump and heat engine regimes as well as a discontinuous phase transition. We will look at three distinctive topologies: a minimal and beyond minimal (homogeneous and heterogeneous interaction structures). The former case is represented by stark different networks ("all-to-all" interactions and only a central interacting to its neighbors) and present exact solutions, whereas homogeneous and heterogeneous structures have been analyzed by numerical simulations. We find that the topology plays a major role on the thermodynamic performance for smaller values of individual energies, in part due to the presence of first-order phase-transitions.Contrariwise, the topology becomes less important as individual energies increases and results are well-described by a system with all-to-all interactions.

cond-mat.stat-mech

Active matter under control: Insights from response theory

Active constituents burn fuel to sustain individual motion, giving rise to collective effects that are not seen in systems at thermal equilibrium, such as phase separation with purely repulsive interactions. There is a great potential in harnessing the striking phenomenology of active matter to build novel controllable and responsive materials that surpass passive ones. Yet, we currently lack a systematic roadmap to predict the protocols driving active systems between different states in a way that is thermodynamically optimal. Equilibrium thermodynamics is an inadequate foundation to this end, due to the dissipation rate arising from the constant fuel consumption in active matter. Here, we derive and implement a versatile framework for the thermodynamic control of active matter. Combining recent developments in stochastic thermodynamics and nonequilibrium response theory, our approach shows how to find the optimal control for either continuous- or discrete-state active systems operating arbitrarily far from equilibrium. Our results open the door to designing novel active materials which are not only built to stabilize specific nonequilibrium collective states, but are also optimized to switch between different states at minimum dissipation.

cond-mat.stat-mech

Precision-dissipation trade-off for driven stochastic systems

In this paper, I derive a closed expression for how precisely a small-scaled system can follow a pre-defined trajectory, while keeping its dissipation below a fixed limit. The total amount of dissipation is approximately inversely proportional to the expected deviation from the pre-defined trajectory. The optimal driving protocol is derived and it is shown that associated time-dependent probability distribution conserves its shape throughout the protocol. Potential applications are discussed in the context of bit erasure and electronic circuits.

cond-mat.stat-mech

Obtaining efficient thermal engines from interacting Brownian particles under time dependent periodic drivings

We introduce an alternative route for obtaining reliable cyclic engines, based on interacting Brownian particles under time-periodic drivings. General expressions for the thermodynamic fluxes, such as power and heat, are obtained using the framework of Stochastic Thermodynamics. Several protocols for optimizing the engine performance are considered, by looking at system parameters such as the output forces and their phase-difference. We study both work-to-work and heat-to-work engines. Our results suggest that carefully designed interactions between particles can lead to more efficient engines.

cond-mat.stat-mech

Relaxation-speed crossover in anharmonic potentials

In a recent Letter [A. Lapolla and A. Godec, Phys. Rev. Lett. 125, 110602 (2020)], thermal relaxation was observed to occur faster from cold to hot (heating) than from hot to cold (cooling). Here we show that overdamped diffusion in anharmonic potentials generically exhibits both faster heating and faster cooling, depending on the initial temperatures and on the potential's degree of anharmonicity. We draw a relaxation-speed phase diagram that localises the different behaviours in parameter space. In addition to faster-heating and faster-cooling regions, we identify a crossover region in the phase diagram, where heating is initially slower but asymptotically faster than cooling. The structure of the phase diagram is robust against the inclusion of a confining, harmonic term in the potential as well as moderate changes of the measure used to define initially equidistant temperatures.

cond-mat.stat-mech