36 citations · 87 across the 7 of their papers we have counts for
7 papers
Irreversibility of mesoscopic processes with hydrodynamic interactions
Biswajit Das, Sreekanth K Manikandan, Shuvojit Paul +3
Optically confined colloidal particles, when placed in close proximity, form a dissipatively coupled system through hydrodynamic interactions. The role of such interactions influen…
Non-monotonic skewness of currents in non-equilibrium steady states
Sreekanth K Manikandan, Biswajit Das, Raunak Dey +3
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 he…
Experimental verification of Arcsine laws in mesoscopic non-equilibrium and active systems
Raunak Dey, Avijit Kundu, Biswajit Das +1
A large number of processes in the mesoscopic world occur out of equilibrium, where the time course of a system evolution becomes immensely important since it is driven principally…
Quantitative analysis of non-equilibrium systems from short-time experimental data
Sreekanth K Manikandan, Subhrokoli Ghosh, Avijit Kundu +5
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 Uncerta…
Single-shot wideband active microrheology of viscoelastic fluids using pulse-scanned optical tweezers
Shuvojit Paul, Avijit Kundu, Ayan Banerjee
We present a fast active microrheology technique exploring the phase response of a microscopic probe particle trapped in a linear viscoelastic fluid using optical tweezers under an…
Active microrheology to determine viscoelastic parameters of Stokes-Oldroyd B fluids using optical tweezers
Shuvojit Paul, Avijit Kundu, Ayan Banerjee
We use active microrheology to determine the frequency dependent moduli of a linear viscoelastic fluid in terms of the polymer time constant (), and the polymer () and solv…
Fast Bayesian inference of optical trap stiffness and particle diffusion
Sudipta Bera, Shuvojit Paul, Rajesh Singh +4
Bayesian inference provides a principled way of estimating the parameters of a stochastic process that is observed discretely in time. The overdamped Brownian motion of a particle…