arXiv subjects

Sreekanth K Manikandan

Publications and source records attributed to Sreekanth K Manikandan.

16 recordsLinked to original sources

arXiv2026

Free-Energy Differences from Nonequilibrium Fluctuations in High Dissipation

Equilibrium free-energy differences can be measured from nonequilibrium work fluctuations using fluctuation theorems, such as the Jarzynski equality and the Crooks fluctuation theorem. However, these approaches become statistically inefficient in high-dissipation regimes because their convergence requires trajectories with negative entropy production, events that occur exponentially rarely. Here, we demonstrate that repeated measurements of trajectory fluctuations are sufficient to determine entropy production without relying on such rare events, or to determine a lower bound on it when only partial measurements are available. This information then yields exact estimates of free-energy differences, or rigorous bounds. We validate this approach, named EquiNET, with numerical simulations, including one of biomolecular folding and unfolding, showing that it recovers accurate free-energy estimates even in regimes where conventional approaches fail.

cond-mat.stat-mech↗

arXiv2026

Localizing entropy production along non-equilibrium trajectories

Entropy production is a universal measure of irreversibility and energy dissipation in physical, chemical, and biological systems operating far from equilibrium. However, quantifying and spatiotemporally localising it in complex processes directly from experimental data remains a major open challenge. Here we address this issue through a data-driven approach that combines the recently developed short-time thermodynamic uncertainty relation based inference scheme with machine learning techniques. Our approach leverages the flexible function representation provided by deep neural networks to achieve accurate reconstruction of high-dimensional, potentially time-dependent dissipative force fields as well as the localization of fluctuating entropy production in both space and time along nonequilibrium trajectories. We demonstrate the versatility of the framework through applications to diverse systems of fundamental interest and experimental significance, where it successfully addresses distinct challenges in localising entropy production.

cond-mat.stat-mech↗

arXiv2025

Unravelling the Flow of Information in a Nonequilibrium Process in the Presence of Hydrodynamic Interactions

Identifying the origin of nonequilibrium characteristics in a generic interacting system having multiple degrees of freedom is a challenging task. In this context, information theoretic measures such as mutual information and related polymorphs offer valuable insights. Here, we explore these measures in a minimal experimental model consisting of two hydrodynamically coupled colloidal particles, where a nonequilibrium drive is introduced via an exponentially correlated noise acting on one of the particles. We show that the information-theoretic tools considered enable a systematic, data-driven dissection of information flow within the system. These measures allow us to identify the driving node and reconstruct the directional dependencies between particles. Notably, they help explain a recently observed, counterintuitive trend in the dependence of irreversibility on interaction strength under coarse-graining (B. Das et.al., arXiv:2405.00800 (2024)). Finally, our results demonstrate how directional information measures can uncover the hidden structure of nonequilibrium dynamics and provide a framework for studying similar effects in more complex systems.

cond-mat.stat-mech↗

arXiv2025

Irreversibility of mesoscopic processes with hydrodynamic interactions

Optically confined colloidal particles, when placed in close proximity, form a dissipatively coupled system through hydrodynamic interactions. The role of such interactions influencing irreversibility and energy dissipation in out-of-equilibrium systems is often not well deciphered. Here, we demonstrate - through the estimation of the entropy production rate - that the nonequilibrium features of the system with such interactions vary depending on the nature of external driving, and importantly, on the level of coarse-graining. Crucially, we show that coarse-graining reverses the dependence of the measured entropy production rate on the strength of the hydrodynamic interactions. Furthermore, we clarify that such interactions do not violate energy balance at the level of individual trajectories, as was believed earlier. Our results highlight a previously unnoticed effect of coarse-graining in nonequilibrium systems, and have implications for the inference of entropy production in experimental contexts.

cond-mat.stat-mech↗

arXiv2024

Tuning the kinetics of intracellular transport

A variety of complex mechanisms, from chemical reaction pathways to active fluctuations, orchestrate molecular transport in intracellular environments. Despite significant recent progress in visualizing and probing these processes, little is known about how tunable the resulting dynamics is through external physical controllers. Here, we demonstrate that coarse-grained, reinforcement learning-based protocols can be developed to achieve highly localized and targeted cargo transport by kinesin motors on intracellular tracks. These protocols can be implemented in practice using optical tweezers, and their feasibility is showcased within experimentally relevant parameter regimes. Our results open new avenues for targeted control of intracellular transport processes, especially when opportunities for control are limited.

cond-mat.stat-mech↗

arXiv2024

Estimate of entropy generation rate can spatiotemporally resolve the active nature of cell flickering

We use the short-time inference scheme (Manikandan, Gupta and Krishnamurthy, Phys. Rev. Lett. 124, 120603, 2020), obtained within the framework of stochastic thermodynamics, to infer a lower-bound to entropy generation rate from flickering data generated by Interference Reflection Microscopy of HeLA cells. We can clearly distinguish active cell membranes from their ATP depleted selves and even spatio-temporally resolve activity down to the scale of about one $μ$m. Our estimate of activity is model--independent.

cond-mat.soft↗

arXiv2024

Role of interactions in non-equilibrium transformations

For arbitrary non-equilibrium 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 non-equilibrium 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.

cond-mat.stat-mech↗

arXiv2022

Inferring entropy production in anharmonic Brownian gyrators

A non-vanishing entropy production rate is one of the defining characteristics of any non-equilibrium 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 non-linear, and the exact dependences 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 non-equilibrium properties of the gyrator model with anharmonic confining potentials are considerably different from its harmonic counterpart - especially in set-ups leading to a non-equilibrium dynamics and the resulting gyration patterns.

cond-mat.stat-mech↗

arXiv2022

Non-monotonic skewness of currents in non-equilibrium steady states

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 show that for any finite-time measurement in a non-equilibrium steady state - rather counter-intuitively - fluctuations below the average are more probable. This discrepancy is 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 result from the non-monotonic 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.

cond-mat.stat-mech↗

arXiv2021

Equidistant quenches in few-level quantum systems

A recent work [Phys. Rev. Lett. 125, 110602] showed that among a pair of \textit{thermodynamically} equidistant quenches from a colder and a hotter initial state at a fixed ambient temperature, the relaxation from the colder initial state (\textit{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 behaviours.

quant-ph↗

arXiv2021

Quantitative analysis of non-equilibrium systems from short-time experimental data

We provide a minimal strategy for the quantitative analysis of a large class of non-equilibrium systems in a {statistically} steady state using the short-time Thermodynamic Uncertainty Relation (TUR). From short-time trajectory data obtained from experiments, we demonstrate how we can simultaneously infer quantitatively, both the thermodynamic force field acting on the system, as well as the (potentially exact) rate of entropy production. We benchmark this scheme first for an experimental study of a colloidal particle system where exact analytical results are known, before applying it to the case of a colloidal particle in a hydrodynamical flow field, where neither analytical nor numerical results are available. In this 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 [Phys. Rev. X 10, 021009].

cond-mat.soft↗

arXiv2021

Estimating time-dependent entropy production from non-equilibrium trajectories

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 is of great practical significance since all it requires is time-series data for the system of interest without requiring prior knowledge of the system parameters.

cond-mat.stat-mech↗

arXiv2020

Inferring entropy production from short experiments

We provide a strategy for an exact inference of the average as well as the fluctuations of the entropy production in non-equilibrium 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.

cond-mat.stat-mech↗

arXiv2019

Efficiency fluctuations in microscopic machines

Nanoscale machines are strongly influenced by thermal fluctuations, contrary to their macroscopic counterparts. As a consequence, even the efficiency of such microscopic machines becomes a fluctuating random variable. Using geometric properties and the fluctuation theorem for the total entropy production, a `universal theory of efficiency fluctuations' at long times, for machines with a finite state space, was developed in [Verley \textit{et al.}, Nat.~Commun.~\textbf{5}, 4721 (2014); Phys.~Rev.~E~\textbf{90}, 052145 (2014)]. We extend this theory to machines with an arbitrary state space. Thereby, we work out more detailed prerequisites for the `universal features' and explain under which circumstances deviations can occur. We also illustrate our findings with exact results for two non-trivial models of colloidal engines.

cond-mat.stat-mech↗

arXiv2018

Exact results for the finite time thermodynamic uncertainty relation

We obtain exact results for the recently discovered finite-time thermodynamic uncertainty relation in a stochastically driven system with non-Gaussian work statistics, both in the steady state and transient regimes, by obtaining exact expressions for any moment of the dissipated work at arbitrary times. The uncertainty function (the Fano factor of the dissipated work) is bounded from below by $2k_BT$ as expected, for all times $τ$, in both steady state and transient regimes. The lower bound is reached at $τ=0$ as well as when certain system parameters vanish (corresponding to an equilibrium state). Surprisingly, we find that the uncertainty function also reaches a constant value at large $τ$ for all the cases we have looked at. For a system starting and remaining in steady state, the uncertainty function increases monotonically, as a function of $τ$ as well as other system parameters, implying that the large $τ$ value is also an upper bound. For the same system in the transient regime, however, we find that the uncertainty function can have a local minimum at an accessible time $τ_m$, for a range of parameter values. The non-monotonicity suggests, rather counter-intuitively, that there might be an optimal time for the working of microscopic machines, as well as an optimal configuration in the phase space of parameter values. Our solutions show that the ratios of higher moments of the dissipated work are also bounded from below by $2k_BT$. For another model, also solvable by our methods, which never reaches a steady state, the uncertainty function, is in some cases, bounded from below by a value less than $2k_BT$.

cond-mat.stat-mech↗

arXiv2017

Asymptotics of work distributions in a stochastically driven system

We determine the asymptotic forms of work distributions at arbitrary times $T$, in a class of driven stochastic systems using a theory developed by Engel and Nickelsen (EN theory) (arXiv:1102.4505v1 [cond-mat.stat-mech]), which is based on the contraction principle of large deviation theory. In this paper, we extend the theory, previously applied in the context of deterministically driven systems, to a model in which the driving is stochastic. The models we study are described by overdamped Langevin equations and the work distributions in the path integral form, are characterised by having quadratic actions. We first illustrate EN theory, for a deterministically driven system - the breathing parabola model, and show that within its framework, the Crooks flucutation theorem manifests itself as a reflection symmetry property of a certain characteristic polynomial function. We then extend our analysis to a stochastically driven system, studied in ( arXiv:1212.0704v2 [cond-mat.stat-mech], arXiv:1402.5777v1 [cond-mat.stat-mech]) using a moment-generating-function method, for both equilibrium and non - equilibrium steady state initial distributions. In both cases we obtain new analytic solutions for the asymptotic forms of (dissipated) work distributions at arbitrary $T$. For dissipated work in the steady state, we compare the large $T$ asymptotic behaviour of our solution to that already obtained in ( arXiv:1402.5777v1 [cond-mat.stat-mech]). In all cases, special emphasis is placed on the computation of the pre-exponential factor and the results show excellent agreement with the numerical simulations. Our solutions are exact in the low noise limit.

cond-mat.stat-mech↗