Thermodynamics of information processing based on enzyme kinetics: An exactly solvable model of an information pump

Cao, Yuansheng; Gong, Zongping; Quan, H. T.

doi:10.1103/physreve.91.062117

Cited by 17 publications

(22 citation statements)

References 66 publications

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“…We propose biochemical information-exploiting devices to show both thermodynamically (via Eq. 1) and physically (via the actual information-processing mechanism) how mutual information can be used to do work, setting the basis for more sophisticated information-exploiting devices.Our first device is a "tape-driven" biochemical machine, which, unlike previous tape-driven devices [13,22,[24][25][26][27][28][29], exploits mutual information within the input. The information-processing mechanism is explicit, differing from measurement-feedback devices previously considered [15,22,31,32].…”

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confidence: 99%

“…Information appears inherently abstract and workperforming devices coupled to strings of 0s and 1s [13,22,[24][25][26][27][28][29] can seem remarkable. However, as Landauer pointed out, "information is physical" [30], and processing it calls for a physical realisation.…”

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confidence: 99%

“…[24], with X/X * as degenerate 0s and 1s storing free energy purely through H(A n ) < H eq (A n ) = ln 2. Cao et al [28] proposed using an enzyme in this context, but without a physical tape. In these studies it appears remarkable that abstract strings of bits can be used for work.…”

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confidence: 99%

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Biochemical Machines for the Interconversion of Mutual Information and Work

et al. 2017

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We propose a physically-realizable information-driven device consisting of an enzyme in a chemical bath, interacting with pairs of molecules prepared in correlated states. These correlations persist without direct interaction and thus store free energy equal to the mutual information. The enzyme can harness this free energy, and that stored in the individual molecular states, to do chemical work. Alternatively, the enzyme can use the chemical driving to create mutual information. A modified system can function without external intervention, approaching biological systems more closely.Organisms exploit correlations in their environment to survive and grow. This fact holds across scales, from bacterial chemotaxis, which leverages the spatial clustering of food molecules [1,2], to the loss of leaves by deciduous trees, which is worthwhile because sunlight exposure is highly correlated from day to day. Evolution itself relies on correlations across time and space, otherwise a mutation which is beneficial would immediately lose its utility and selection would be impossible.Biological systems also generate correlations. In particular, information transmission is an exercise in correlating input and output [3], and recent years have thus seen information theory applied to biological systems involved in sensing [4][5][6], signalling [7,8], chemotaxis [1, 2], adaption [9, 10] and beyond [11]. In the language of information theory, correlated variables X and Y have a positive mutual informationp(x)p(y) (measured in nats), with p(x, y) the joint probability of a given state and p(x), p(y) the marginals. The "information entropy" H(Y ) = − y∈Y p(y) ln p(y) quantifies Y 's uncertainty, and I(X; Y ) is the reduction in this entropy given knowledge of X: I(X; Y ) = H(Y ) − H(Y |X). The mutual information is symmetric, non-negative, and zero if and only if X and Y are statistically independent.Information theory is also deeply connected to thermodynamics [12][13][14][15][16][17][18][19][20]. Sagawa and Ueda [14], building on [12,13], showed that measurement cycles have a minimal work cost equal to the mutual information generated between data and memory. Horowitz and Esposito showed that entropy production within a system X can be negative if X is coupled to a second system Y , and transitions in X decrease I(X; Y ) [18]. A third key result, essential to exorcising Maxwell's Demon [6,21], is that if X and Y are uncoupled from each other, yet coupled to heat baths at temperature T , then the total free energy is [22,23] HereF (X) = F eq (X) − kT x∈X p(x) ln(p eq (x)/p(x)) is the non-equilibrium free energy [20,23], with the tilde indicating the generalisation from the standard equilibrium free energy F eq (X). Systems X and Y could be two non-interacting spins, or two physically separated molecules. For uncoupled systems, the partition function is separable and X and Y are independent in equilibrium, I eq (X; Y ) = 0. However, correlations induced by coupling between X and Y at earlier times could persist even after the coupling...

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Biochemical Machines for the Interconversion of Mutual Information and Work

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“…Studies on Maxwell's demon can broadly be grouped into two categories. Demons which rely on external control [60,61,68,77,78,80,87,88,[90][91][92][93][94][95][96] and autonomous demons [41,64,86,[97][98][99][100][101][102][103][104][105][106][107][108][109][110][111][112][113][114], where no external control is needed. Connections between autonomous and nonautonomous implementations of Maxwell's demon were investigated in Refs.…”

Section: Introductionmentioning

confidence: 99%

“…Autonomous demons offer the possibility to keep track of information flows and to investigate the necessary entropy production associated to a certain level of performance. Such devices often either rely on an information reservoir [41,97,98,100,101,103,105,107,110], providing a storage medium for the measurement outcomes, or on thermal reservoirs [64,99,102,106,108,109,111,112,114]. The latter are of particular interest as they only require standard thermodynamic resources and are thus within the paradigm that addresses the question what can be achieved by coupling a small system to thermal reservoirs?…”

Section: Introductionmentioning

confidence: 99%

Autonomous conversion of information to work in quantum dots

Sánchez

Samuelsson

Potts

2019

Phys. Rev. Research

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We consider an autonomous implementation of Maxwell's demon in a quantum dot architecture. As in the original thought experiment, only the second law of thermodynamics is seemingly violated when disregarding the demon. The autonomous architecture allows us to compare descriptions in terms of information to a more traditional, thermoelectric characterization. Our detailed investigation of information-to-work conversion is based on fluctuation relations and second law like inequalities in addition to the average heat and charge currents. By introducing a time-reversal on the level of individual electrons, we find a novel fluctuation relation that is not connected to any symmetry of the moment generating function of heat and particle flows. Furthermore, we show how an effective Markovian master equation with broken detailed balance for the system alone can emerge from a full description, allowing for an investigation of the entropic cost associated to breaking detailed balance. Interestingly, while the entropic cost of performing a perfect measurement diverges, the entropic cost of breaking detailed balance does not. Our results connect various approaches and idealized scenarios found in the literature and can be tested experimentally with present day technology. arXiv:1907.02866v1 [cond-mat.mes-hall]

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Leveraging Environmental Correlations: The Thermodynamics of Requisite Variety

2017

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Key to biological success, the requisite variety that confronts an adaptive organism is the set of detectable, accessible, and controllable states in its environment. We analyze its role in the thermodynamic functioning of information ratchets-a form of autonomous Maxwellian Demon capable of exploiting fluctuations in an external information reservoir to harvest useful work from a thermal bath. This establishes a quantitative paradigm for understanding how adaptive agents leverage structured thermal environments for their own thermodynamic benefit. General ratchets behave as memoryful communication channels, interacting with their environment sequentially and storing results to an output. The bulk of thermal ratchets analyzed to date, however, assume memoryless environments that generate input signals without temporal correlations. Employing computational mechanics and a new information-processing Second Law of Thermodynamics (IPSL) we remove these restrictions, analyzing general finite-state ratchets interacting with structured environments that generate correlated input signals. On the one hand, we demonstrate that a ratchet need not have memory to exploit an uncorrelated environment. On the other, and more appropriate to biological adaptation, we show that a ratchet must have memory to most effectively leverage structure and correlation in its environment. The lesson is that to optimally harvest work a ratchet's memory must reflect the input generator's memory. Finally, we investigate achieving the IPSL bounds on the amount of work a ratchet can extract from its environment, discovering that finite-state, optimal ratchets are unable to reach these bounds. In contrast, we show that infinite-state ratchets can go well beyond these bounds by utilizing their own infinite "negentropy". We conclude with an outline of the collective thermodynamics of information-ratchet swarms.

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Thermodynamics of information processing based on enzyme kinetics: An exactly solvable model of an information pump

Cited by 17 publications

References 66 publications

Biochemical Machines for the Interconversion of Mutual Information and Work

Biochemical Machines for the Interconversion of Mutual Information and Work

Autonomous conversion of information to work in quantum dots

Leveraging Environmental Correlations: The Thermodynamics of Requisite Variety

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