English

Thermodynamic precision of a chain of motors: the difference between phase and noise correlation

Statistical Mechanics 2024-03-03 v1 Soft Condensed Matter

Abstract

Inspired by recent experiments on fluctuations of the flagellar beating in sperms and C. reinhardtii, we investigate the precision of phase fluctuations in a system of nearest-neighbour-coupled molecular motors. We model the system as a Kuramoto chain of oscillators with coupling constant kk and noisy driving. The precision pp is a Fano-factor-like observable which obeys the Thermodynamic Uncertainty Relation (TUR), that is an upper bound related to dissipation. We first consider independent motor noises with diffusivity DD: in this case the precision goes as k/Dk/D, coherently with the behavior of spatial order. The minimum observed precision is that of the uncoupled oscillator puncp_{unc}, the maximum observed one is NpuncNp_{unc}, saturating the TUR bound. Then we consider driving noises which are spatially correlated, as it may happen in the presence of some direct coupling between adjacent motors. Such a spatial correlation in the noise does not reduce evidently the degree of spatial correlation in the chain, but sensibly reduces the maximum attainable precision pp, coherently with experimental observations. The limiting behaviors of the precision, in the two opposite cases of negligible interaction and strong interaction, are well reproduced by the precision of the single chain site puncp_{unc} and the precision of the center of mass of the chain NeffpuncN_{eff} p_{unc} with Neff<NN_{eff}<N: both do not depend on the degree of interaction in the chain, but NeffN_{eff} decreases with the correlation length of the motor noises.

Keywords

Cite

@article{arxiv.2401.09952,
  title  = {Thermodynamic precision of a chain of motors: the difference between phase and noise correlation},
  author = {Giulio Costantini and Andrea Puglisi},
  journal= {arXiv preprint arXiv:2401.09952},
  year   = {2024}
}

Comments

7 pages, 7 figures, accepted on the Special Issue dedcated to STATPHYS28 on the journal J. Stat. Mech