Tag: Sreekanth K. Manikandan

Invited talk by Sreekanth K. Manikandan at the online Workshop on Stochastic Thermodynamics (WOST), 14th May 2025

Recent advances in nonequilibrium physics allow extracting thermodynamic quantities, such as entropy production, directly from dynamical information in microscopic movies. (Image by S. Manikandan.)
Localizing entropy production in cellular processes
Sreekanth Manikandan
Date: 14 Mar 2025
Time: 17:30 CEST
Place: Online
Part of the Workshop on Stochastic Thermodynamics

Quantifying the spatiotemporal forces, affinities, and dissipative costs of cellular-scale non-equilibrium processes from experimental data and localizing it in space and time remain a significant open challenge. Here, I explore how principles from stochastic thermodynamics, combined with machine learning techniques, offer a promising approach to addressing this issue. I will present preliminary results from experiments on fluctuating cell membranes and simulations of non-equilibrium systems in stationary and time-dependently driven states. These studies reveal potential strategies for localizing entropy production in experimental biophysical contexts while also highlighting key challenges and limitations that must be addressed.

Invited talk by S. Manikandan at the 14th Nordic Workshop on Statistical Physics, Nordita, 5 March 2025

Recent advances in nonequilibrium physics allow extracting thermodynamic quantities, such as entropy production, directly from dynamical information in microscopic movies. (Image by S. Manikandan.)
Localizing entropy production in non-equilibrium processes
Sreekanth Manikandan
Date: 5 Mar 2025
Time: 14:45
Place: Nordita
Part of the 14th Nordic Workshop on Statistical Physics

Quantifying the spatiotemporal forces, affinities, and dissipative costs of cellular-scale non-equilibrium processes from experimental data and localizing it in space and time remain a significant open challenge. Here, I explore how principles from stochastic thermodynamics, combined with machine learning techniques, offer a promising approach to addressing this issue. I will present preliminary results from experiments on fluctuating cell membranes and simulations of non-equilibrium systems in stationary and time-dependently driven states. These studies reveal potential strategies for localizing entropy production in experimental biophysical contexts while also highlighting key challenges and limitations that must be addressed.

Sreekanth K. Manikandan joins the Soft Matter Lab

(Photo by A. Ciarlo.)
Sreekanth K. Manikandan began working as a researcher at the Physics Department of the University of Gothenburg on December 9, 2024.

He received his Ph.D. in Theoretical Physics in 2020 from Stockholm University under the supervision of Supriya Krishnamurthy. His thesis, titled “Nonequilibrium Thermodynamics at the Microscopic Scales,” focused on finite and short-time fluctuations in non-equilibrium systems, as opposed to the large-time asymptotic properties studied within the framework of large deviation theory. One of the key outcomes of his Ph.D. research was the development of a method to infer entropy production rates directly from experimentally accessible trajectories in a model-independent manner.

Following his PhD, Sreekanth received the NORDITA postdoctoral fellowship for independent research. During this time, he expanded on his earlier work by developing generalizations of the inference scheme for entropy production and integrating it with machine-learning tools for practical inference of dissipative forces and entropy production from experimental data. Later, in 2022, he was awarded the Wallenberg Scholarship for postdoctoral research at Stanford, where he developed machine-learning-based non-equilibrium control techniques for targeted self-assembly and transport of biomolecular systems.

Currently he is interested in combining methods from Non-equilibrium Physics and Machine Learning to quantitatively characterize and control nanoscale biophysical processes.

Presentation by Sreekanth K Manikandan, 10 February 2023

Inferring entropy production in microscopic systems
Sreekanth K. Manikandan
Stanford University
10 February 2023, 15:00, Raven and Fox

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 (entropy production) to the environment from passive, equilibrium processes is a very challenging task and a vastly developing field of research. In this talk, I will present a simple and effective way to infer entropy production in microscopic non-equilibrium systems, from short empirical trajectories [1]. I will also demonstrate how this scheme can be used to spatiotemporally resolve the active nature of cell flickering [2]. Our result is built upon the Thermodynamic Uncertainty Relation (TUR) which relates current fluctuations in non-equilibrium states to the entropy production rate.

References

[1] Inferring entropy production from short experiments [ Phys. Rev. Lett. 124, 120603 (2020) ]

[2] Estimate of entropy generation rate can spatiotemporally resolve the active nature of cell flickering [arXiv:2205.12849]

Bio: Sreekanth completed his PhD at the department of Physics, Stockholm University, in June 2020. His PhD supervisor was Supriya Krishnamurthy. From August 2020 – October 2022, Sreekanth was a Nordita fellow postdoc in the soft condensed matter group at Nordita. Currently, he is a postdoctoral scholar at the Department of Chemistry at Stanford University, funded by the Wallenberg foundation.