Engineered swift equilibration for arbitrary geometries

Frim, Adam G.; Zhong, Adrianne; Chen, Shi-Fan; Mandal, Dibyendu; DeWeese, Michael R.

doi:10.1103/physreve.103.l030102

Cited by 18 publications

(22 citation statements)

References 36 publications

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“…A similar approach could prove useful, where such contributions lead one to treat the space of control parameters as a Finsler manifold with a potentially asymmetric Finsler metric. Likewise, lessons from studies of finite-time processes that shortcut relaxation timescales could further facilitate the development of optimal cyclic engines [46][47][48][49][50][51][52][53][54][55][56].…”

Section: (B) Itmentioning

confidence: 99%

Optimal finite-time Brownian Carnot engine

Frim,

DeWeese

2021

Preprint

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Recent advances in experimental control of colloidal systems have spurred a revolution in the production of mesoscale thermodynamic devices. Functional "textbook" engines, such as the Stirling and Carnot cycles, have been produced in colloidal systems where they operate far from equilibrium. Simultaneously, significant theoretical advances have been made in the design and analysis of such devices. Here, we use methods from thermodynamic geometry to characterize the optimal finitetime, nonequilibrium cyclic operation of the parametric harmonic oscillator contact with with a time-varying heat bath, with particular focus on the Brownian Carnot cycle. We derive the optimally parametrized Carnot cycle, along with two other new cycles and compare their dissipated energy, efficiency, and steady-state power production against each other and a previously tested experimental protocol for the Carnot cycle. We demonstrate a 20% improvement in dissipated energy over previous experimentally tested protocols and a ∼50% improvement under other conditions for one of our engines, while our final engine is more efficient and powerful than the others we considered. Our results provide the means for experimentally realizing optimal mesoscale heat engines.

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Section: (B) Itmentioning

confidence: 99%

Optimal finite-time Brownian Carnot engine

Frim,

DeWeese

2021

Preprint

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“…Over the past several decades, stochastic thermodynamics has dramatically improved our understanding of nonequilibrium statistical physics [1][2][3][4][5][6][7]. A major focus of study in this area has been the performance of engines operating in finite time, where both power and dissipation are finite, often with an emphasis on engines operating at maximal power [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. A recurring theme has been the interplay, and often incompatibility, among high efficiency, high output power, and low dissipation [13,15,18,21].…”

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confidence: 99%

“…A major focus of study in this area has been the performance of engines operating in finite time, where both power and dissipation are finite, often with an emphasis on engines operating at maximal power [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. A recurring theme has been the interplay, and often incompatibility, among high efficiency, high output power, and low dissipation [13,15,18,21]. To that end, we recently characterized optimal protocols for the finite-time operation of a Brownian Carnot engine [21], a colloidal system introduced in [24], finding minimally dissipative cycles often came at the expense of reduced power and efficiency.…”

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confidence: 99%

A geometric bound on the efficiency of irreversible thermodynamic cycles

Frim,

DeWeese

2021

Preprint

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“…On the other hand, the scope of CD driving is not limited to the quantum realm. Because of the close mathematical analogies between classical stochastic systems and quantum mechanics, it was recently recognized that the CD paradigm can also be formalized for classical scenarios [23,44,[47][48][49][50][51][52][53]. The classical analogue of driving a system along a target trajectory of eigenstates is a trajectory of instantaneous stationary distributions.…”

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confidence: 99%

Shortcuts in stochastic systems and control of biophysical processes

İlker

Güngör

Kuznets-Speck

et al. 2021

Preprint

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The biochemical reaction networks that regulate living systems are all stochastic to varying degrees. The resulting randomness affects biological outcomes at multiple scales, from the functional states of single proteins in a cell to the evolutionary trajectory of whole populations. Controlling how the distribution of these outcomes changes over time—via external interventions like timevarying concentrations of chemical species—is a complex challenge. In this work, we show how counterdiabatic (CD) driving, first developed to control quantum systems, provides a versatile tool for steering biological processes. We develop a practical graph-theoretic framework for CD driving in discrete-state continuous-time Markov networks. We illustrate the formalism with examples from gene regulation and chaperone-assisted protein folding, demonstrating the possibility that nature can exploit CD driving to accelerate response to sudden environmental changes. We generalize the method to continuum Fokker-Planck models, and apply it to study AFM single-molecule pulling experiments in regimes where the typical assumption of adiabaticity breaks down, as well as an evolutionary model with competing genetic variants subject to time-varying selective pressures. The AFM analysis shows how CD driving can eliminate non-equilibrium artifacts due to large force ramps in such experiments, allowing accurate estimation of biomolecular properties.

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Engineered swift equilibration for arbitrary geometries

Cited by 18 publications

References 36 publications

Optimal finite-time Brownian Carnot engine

Optimal finite-time Brownian Carnot engine

A geometric bound on the efficiency of irreversible thermodynamic cycles

Shortcuts in stochastic systems and control of biophysical processes

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