Abstract
A general understanding of the thermodynamic costs of nonequilibrium processes would illuminate the design principles of efficient microscopic machines. Considerable effort has gone into finding and classifying the deterministic control protocols that drive a system rapidly between states at minimum energetic cost. But for autonomous microscopic systems—like molecular machines—driving processes are themselves stochastic. In this chapter we generalize a linear-response framework to incorporate such protocol variability, deriving a lower bound on the work that is realized at finite protocol duration, far from the quasistatic limit. We illustrate our findings in two model systems. Ultimately, this theoretical framework provides a thermodynamic rationale for rapid operation, independent of any functional incentives.
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Notes
- 1.
Material in this chapter also appears in Ref. [3].
- 2.
For a harmonic system, the forces are linear in position f ∝ x, and thus 〈δf(0)δf(t)〉∝〈δx(0)δx(t)〉. This implies that the force relaxation time and position relaxation time are equivalent.
References
P.R. Zulkowski, M.R. DeWeese, Optimal finite-time erasure of a classical bit. Phys. Rev. E 89, 052140 (2014)
D.A. Sivak, G.E. Crooks, Thermodynamic geometry of minimum-dissipation driven barrier crossing. Phys. Rev. E 94, 052106 (2016)
S.J. Large, R. Chetrite, D.A. Sivak, Stochastic control in microscopic nonequilibrium systems. EPL 124, 20001 (2018)
M. Yoshida, E. Muneyuki, T. Hisabori, ATP synthase—a marvellous rotary engine of the cell. Nat. Rev. Mol. Cell Biol. 2, 669 (2001)
D.A. Sivak, G.E. Crooks, Thermodynamic metrics and optimal paths. Phys. Rev. Lett. 108, 190602 (2012)
C. Gardiner, Stochastic Methods, A Handbook for the Natural and Social Sciences, 4th edn. (Springer, 2009)
N.G. van Kampen, Stochastic Processes in Physics and Chemistry, 3rd edn. (Elsevier, 2007)
G. Casella, R.R. Berger, Statistical Inference (Thompson Learning, 2002)
G.E. Crooks, Measuring thermodynamic length. Phys. Rev. Lett. 99, 100602 (2007)
B.B. Machta, Dissipation bound for thermodynamic control. Phys. Rev. Lett. 115, 260603 (2015)
A. Berezhkovskii, A. Szabo, Time scale separation leads to position-dependent diffusion along a slow coordinate. J. Chem. Phys. 135, 174108 (2011)
P.R. Zulkowski, M.R. DeWeese, Optimal control of overdamped systems. Phys. Rev. E 92, 032117 (2015)
O. Mazonka, C. Jarzynski, Exactly solvable model illustrating far-from-equilibrium predictions. 1999, arxiv:9912121
S. Tafoya, S.J. Large, S. Liu, C. Bustamante, D.A. Sivak, Using a system’s equilibrium behaviour to reduce its energy dissipation in nonequilibrium processes. Proc. Natl. Acad. Sci. U. S. A. 116, 5920–5924 (2019)
J.M. Horowitz, M. Esposito, Work producing reservoirs: stochastic thermodynamics with generalized Gibbs ensembles. Phys. Rev. E 94, 020102(R) (2016)
A.C. Barato, U. Seifert, Thermodynamic cost of external control. New J. Phys. 19, 073021 (2017)
G. Verley, C. Van den Broeck, M. Esposito, Work statistics of stochastically driven systems. New J. Phys. 16, 095001 (2014)
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Large, S.J. (2021). Stochastic Control in Microscopic Nonequilibrium Systems. In: Dissipation and Control in Microscopic Nonequilibrium Systems. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-030-85825-4_6
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DOI: https://doi.org/10.1007/978-3-030-85825-4_6
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