Grant M. Rotskoff, Gavin E. Crooks, arXiv:1510.06734

[ Full text | arXiv ]

Abstract:

A general understanding of optimal control in non-equilibrium systems would illuminate the operational principles of biological and artificial nanoscale machines. Recent work has shown that a system driven out of equilibrium by a linear response protocol is endowed with a Riemannian metric related to generalized susceptibilities, and that geodesics on this manifold are the non-equilibrium control protocols with the lowest achievable dissipation. While this elegant mathematical framework has inspired numerous studies of exactly solvable systems, no description of the thermodynamic geometry yet exists when the metric cannot be derived analytically. Herein, we numerically construct the dynamic metric of the 2D Ising model in order to study optimal protocols for reversing the net magnetization.

Srividya Iyer-Biswas, Charles S. Wright, Jonathan T. Henry, Klevin Lo, Stanislav Burov, Yihan Lin, Gavin E. Crooks, Sean Crosson, Aaron R. Dinner, Norbert F. Scherer, Proc. Natl. Acad. Sci. U.S.A. (2014)

[ Full text | Journal | arXiv ]

This is the experimental paper that logically (but, alas, not chronologically) precedes the companion theory paper.

Abstract: Uncovering the quantitative laws that govern the growth and division of single cells remains a major challenge. Using a unique combination of technologies that yields unprecedented statistical precision, we find that the sizes of individual Caulobacter crescentus cells increase exponentially in time. We also establish that they divide upon reaching a critical multiple (≈1.8) of their initial sizes, rather than an absolute size. We show that when the temperature is varied, the growth and division timescales scale proportionally with each other over the physiological temperature range. Strikingly, the cell-size and division-time distributions can both be rescaled by their mean values such that the condition-specific distributions collapse to universal curves. We account for these observations with a minimal stochastic model that is based on an autocatalytic cycle. It predicts the scalings, as well as specific functional forms for the universal curves. Our experimental and theoretical analysis reveals a simple physical principle governing these complex biological processes: a single temperature-dependent scale of cellular time governs the stochastic dynamics of growth and division in balanced growth conditions.

Srividya Iyer-Biswas, Gavin E. Crooks, Norbert F. Scherer, and Aaron R. Dinner, Phys. Rev. Lett., 113, 028101 (2014)

[ Full text | Journal ]

Abstract: Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. Continue reading →

David A. Sivak, John D. Chodera, Gavin E. Crooks, arXiv:1301.3800

[ Full text | Journal | ArXiv]

Abstract: While the numerical integration of deterministic equations of motion for molecular systems now has a well-developed set of algorithms with commonly agreed-upon desirable properties, the simulation of stochastic equations of motion lacks algorithms with a similar degree of universal acceptance. Part of the difficulty is in determining which of many properties should be satisfied by such a discrete time integration scheme, with additional difficulties in satisfying many properties simultaneously with a single scheme. The desire to use these integration schemes for nonequilibrium simulations and in conjunction with recent nonequilibrium fluctuation theorems adds additional complications. Here, we compare a number of discrete time integration schemes for Langevin dynamics, Continue reading →