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Publications (10 of 12) Show all publications
Bo, S., Lim, S. H. & Eichhorn, R. (2019). Functionals in stochastic thermodynamics: how to interpret stochastic integrals. Journal of Statistical Mechanics: Theory and Experiment, Article ID 084005.
Open this publication in new window or tab >>Functionals in stochastic thermodynamics: how to interpret stochastic integrals
2019 (English)In: Journal of Statistical Mechanics: Theory and Experiment, E-ISSN 1742-5468, article id 084005Article in journal (Refereed) Published
Abstract [en]

In stochastic thermodynamics standard concepts from macroscopic thermodynamics, such as heat, work, and entropy production, are generalized to small fluctuating systems by defining them on a trajectory-wise level. In Langevin systems with continuous state-space such definitions involve stochastic integrals along system trajectories, whose specific values depend on the discretization rule used to evaluate them (i.e. the 'interpretation' of the noise terms in the integral). Via a systematic mathematical investigation of this apparent dilemma, we corroborate the widely used standard interpretation of heat-and work-like functionals as Stratonovich integrals. We furthermore recapitulate the anomalies that are known to occur for entropy production in the presence of temperature gradients.

Keywords
stochastic thermodynamics, stochastic particle dynamics, stochastic processes, coarse-graining
National Category
Mechanical Engineering Mathematics
Identifiers
urn:nbn:se:su:diva-173196 (URN)10.1088/1742-5468/ab3111 (DOI)000481926600001 ()
Available from: 2019-09-17 Created: 2019-09-17 Last updated: 2024-07-04Bibliographically approved
Dabelow, L., Bo, S. & Eichhorn, R. (2019). Irreversibility in Active Matter Systems: Fluctuation Theorem and Mutual Information. Physical Review X, 9(2), Article ID 021009.
Open this publication in new window or tab >>Irreversibility in Active Matter Systems: Fluctuation Theorem and Mutual Information
2019 (English)In: Physical Review X, E-ISSN 2160-3308, Vol. 9, no 2, article id 021009Article in journal (Refereed) Published
Abstract [en]

We consider a Brownian particle which, in addition to being in contact with a thermal bath, is driven by fluctuating forces which stem from active processes in the system, such as self-propulsion or collisions with other active particles. These active fluctuations do not fulfill a fluctuation-dissipation relation and therefore play the role of a nonequilibrium environment, which keeps the system permanently out of thermal equilibrium even in the absence of external forces. We investigate how the out-of-equilibrium character of the active matter system and the associated irreversibility is reflected in the trajectories of the Brownian particle. Specifically, we analyze the log ratio of path probabilities for observing a certain particle trajectory forward in time versus observing its time-reversed twin trajectory. For passive Brownian motion, it is well known that this path probability ratio quantifies irreversibility in terms of entropy production. For active Brownian motion, we show that in addition to the usual entropy produced in the thermal environment, the path probability ratio contains a contribution to irreversibility from mutual information production between the particle trajectory and the history of the nonequilibrium environment. The resulting irreversibility measure fulfills an integral fluctuation theorem and a secondlaw-like relation. When deriving and discussing these relations, we keep in mind that the active fluctuations can occur either due to a suspension of active particles pushing around a passive colloid or due to active self-propulsion of the particle itself; we point out the similarities and differences between these two situations. We obtain explicit expressions for active fluctuations modeled by an Ornstein-Uhlenbeck process. Finally, we illustrate our general results by analyzing a Brownian particle which is trapped in a static or moving harmonic potential.

Keywords
Statistical Physics
National Category
Physical Sciences
Identifiers
urn:nbn:se:su:diva-168330 (URN)10.1103/PhysRevX.9.021009 (DOI)000464753500001 ()
Available from: 2019-05-22 Created: 2019-05-22 Last updated: 2024-01-17Bibliographically approved
Bo, S., Schmidt, F., Eichhorn, R. & Volpe, G. (2019). Measurement of anomalous diffusion using recurrent neural networks. Physical review. E, 100(1), Article ID 010102.
Open this publication in new window or tab >>Measurement of anomalous diffusion using recurrent neural networks
2019 (English)In: Physical review. E, ISSN 2470-0045, E-ISSN 2470-0053, Vol. 100, no 1, article id 010102Article in journal (Refereed) Published
Abstract [en]

Anomalous diffusion occurs in many physical and biological phenomena, when the growth of the mean squared displacement (MSD) with time has an exponent different from one. We show that recurrent neural networks (RNNs) can efficiently characterize anomalous diffusion by determining the exponent from a single short trajectory, outperforming the standard estimation based on the MSD when the available data points are limited, as is often the case in experiments. Furthermore, the RNNs can handle more complex tasks where there are no standard approaches, such as determining the anomalous diffusion exponent from a trajectory sampled at irregular times, and estimating the switching time and anomalous diffusion exponents of an intermittent system that switches between different kinds of anomalous diffusion. We validate our method on experimental data obtained from subdiffusive colloids trapped in speckle light fields and superdiffusive microswimmers.

National Category
Physical Sciences Mathematics
Identifiers
urn:nbn:se:su:diva-171662 (URN)10.1103/PhysRevE.100.010102 (DOI)000476695300001 ()
Available from: 2019-08-21 Created: 2019-08-21 Last updated: 2022-02-26Bibliographically approved
Del Giudice, M., Bo, S., Grigolon, S. & Bosia, C. (2018). On the role of extrinsic noise in microRNA-mediated bimodal gene expression. PloS Computational Biology, 14(4), Article ID e1006063.
Open this publication in new window or tab >>On the role of extrinsic noise in microRNA-mediated bimodal gene expression
2018 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 14, no 4, article id e1006063Article in journal (Refereed) Published
Abstract [en]

Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Bimodal distributions of gene expression levels provide experimental evidence of phenotypic differentiation, where the modes of the distribution often correspond to different physiological states of the system. We theoretically address the presence of bimodal phenotypes in the context of microRNA (miRNA)-mediated regulation. MiRNAs are small noncoding RNA molecules that downregulate the expression of their target mRNAs. The nature of this interaction is titrative and induces a threshold effect: below a given target transcription rate almost no mRNAs are free and available for translation. We investigate the effect of extrinsic noise on the system by introducing a fluctuating miRNA-transcription rate. We find that the presence of extrinsic noise favours the presence of bimodal target distributions which can be observed for a wider range of parameters compared to the case with intrinsic noise only and for lower miRNA-target interaction strength. Our results suggest that combining threshold-inducing interactions with extrinsic noise provides a simple and robust mechanism for obtaining bimodal populations without requiring fine tuning. Furthermore, we characterise the protein distribution's dependence on protein half-life.

National Category
Biological Sciences
Identifiers
urn:nbn:se:su:diva-157822 (URN)10.1371/journal.pcbi.1006063 (DOI)000432169600015 ()29664903 (PubMedID)
Available from: 2018-06-26 Created: 2018-06-26 Last updated: 2022-03-23Bibliographically approved
Del Giudice, M., Bosia, C., Grigolon, S. & Bo, S. (2018). Stochastic sequestration dynamics: a minimal model with extrinsic noise for bimodal distributions and competitors correlation. Scientific Reports, 8, Article ID 10387.
Open this publication in new window or tab >>Stochastic sequestration dynamics: a minimal model with extrinsic noise for bimodal distributions and competitors correlation
2018 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 8, article id 10387Article in journal (Refereed) Published
Abstract [en]

Many biological processes are known to be based on molecular sequestration. This kind of dynamics involves two types of molecular species, namely targets and sequestrants, that bind to form a complex. In the simple framework of mass-action law, key features of these systems appear to be threshold-like profiles of the amounts of free molecules as a function of the parameters determining their possible maximum abundance. However, biochemical processes are probabilistic and take place in stochastically fluctuating environments. How these different sources of noise affect the final outcome of the network is not completely characterised yet. In this paper we specifically investigate the effects induced by a source of extrinsic noise onto a minimal stochastic model of molecular sequestration. We analytically show how bimodal distributions of the targets can appear and characterise them as a result of noise filtering mediated by the threshold response. We then address the correlations between target species induced by the sequestrant and discuss how extrinsic noise can turn the negative correlation caused by competition into a positive one. Finally, we consider the more complex scenario of competitive inhibition for enzymatic kinetics and discuss the relevance of our findings with respect to applications.

National Category
Biochemistry Molecular Biology
Identifiers
urn:nbn:se:su:diva-159110 (URN)10.1038/s41598-018-28647-9 (DOI)000438024500019 ()29991682 (PubMedID)2-s2.0-85049864216 (Scopus ID)
Available from: 2018-08-31 Created: 2018-08-31 Last updated: 2025-02-20Bibliographically approved
Bo, S. & Eichhorn, R. (2017). Driven Anisotropic Diffusion at Boundaries: Noise Rectification and Particle Sorting. Physical Review Letters, 119(6), Article ID 060603.
Open this publication in new window or tab >>Driven Anisotropic Diffusion at Boundaries: Noise Rectification and Particle Sorting
2017 (English)In: Physical Review Letters, ISSN 0031-9007, E-ISSN 1079-7114, Vol. 119, no 6, article id 060603Article in journal (Refereed) Published
Abstract [en]

We study the diffusive dynamics of a Brownian particle in the proximity of a flat surface under nonequilibrium conditions, which are created by an anisotropic thermal environment with different temperatures being active along distinct spatial directions. By presenting the exact time-dependent solution of the Fokker-Planck equation for this problem, we demonstrate that the interplay between anisotropic diffusion and hard-core interaction with the plain wall rectifies the thermal fluctuations and induces directed particle transport parallel to the surface, without any deterministic forces being applied in that direction. Based on current micromanipulation technologies, we suggest a concrete experimental setup to observe this novel noise-induced transport mechanism. We furthermore show that it is sensitive to particle characteristics, such that this setup can be used for sorting particles of different sizes.

National Category
Physical Sciences
Identifiers
urn:nbn:se:su:diva-147093 (URN)10.1103/PhysRevLett.119.060603 (DOI)000407445800002 ()
Available from: 2017-10-12 Created: 2017-10-12 Last updated: 2022-02-28Bibliographically approved
Argun, A., Soni, J., Dabelow, L., Bo, S., Pesce, G., Eichhorn, R. & Volpe, G. (2017). Experimental realization of a minimal microscopic heat engine. Physical review. E, 96(5), Article ID 052106.
Open this publication in new window or tab >>Experimental realization of a minimal microscopic heat engine
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2017 (English)In: Physical review. E, ISSN 2470-0045, E-ISSN 2470-0053, Vol. 96, no 5, article id 052106Article in journal (Refereed) Published
Abstract [en]

Microscopic heat engines are microscale systems that convert energy flows between heat reservoirs into work or systematic motion. We have experimentally realized a minimal microscopic heat engine. It consists of a colloidal Brownian particle optically trapped in an elliptical potential well and simultaneously coupled to two heat baths at different temperatures acting along perpendicular directions. For a generic arrangement of the principal directions of the baths and the potential, the symmetry of the system is broken, such that the heat flow drives a systematic gyrating motion of the particle around the potential minimum. Using the experimentally measured trajectories, we quantify the gyrating motion of the particle, the resulting torque that it exerts on the potential, and the associated heat flow between the heat baths. We find excellent agreement between the experimental results and the theoretical predictions.

National Category
Physical Sciences
Identifiers
urn:nbn:se:su:diva-149987 (URN)10.1103/PhysRevE.96.052106 (DOI)000414423500002 ()
Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2022-02-28Bibliographically approved
Bo, S. & Celani, A. (2017). Multiple-scale stochastic processes: Decimation, averaging and beyond. Physics reports, 670, 1-59
Open this publication in new window or tab >>Multiple-scale stochastic processes: Decimation, averaging and beyond
2017 (English)In: Physics reports, ISSN 0370-1573, E-ISSN 1873-6270, Vol. 670, p. 1-59Article, review/survey (Refereed) Published
Abstract [en]

The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This has provided fruitful applications for established stochastic methods and motivated further developments. These systems often involve processes taking place on widely separated time scales. For an efficient modeling one usually focuses on the slower degrees of freedom and it is of great importance to accurately eliminate the fast variables in a controlled fashion, carefully accounting for their net effect on the slower dynamics. This procedure in general requires to perform two different operations: decimation and coarse-graining. We introduce the asymptotic methods that form the basis of this procedure and discuss their application to a series of physical, biological and chemical examples. We then turn our attention to functionals of the stochastic trajectories such as residence times, counting statistics, fluxes, entropy production, etc. which have been increasingly studied in recent years. For such functionals, the elimination of the fast degrees of freedom can present additional difficulties and naive procedures can lead to blatantly inconsistent results. Homogenization techniques for functionals are less covered in the literature and we will pedagogically present them here, as natural extensions of the ones employed for the trajectories. We will also discuss recent applications of these techniques to the thermodynamics of small systems and their interpretation in terms of information-theoretic concepts.

Keywords
Markov processes, Diffusive processes, Multiscale methods, Irreversibility, Stochastic functionals
National Category
Physical Sciences
Identifiers
urn:nbn:se:su:diva-141431 (URN)10.1016/j.physrep.2016.12.003 (DOI)000394409200001 ()
Available from: 2017-04-04 Created: 2017-04-04 Last updated: 2022-02-28Bibliographically approved
Aurell, E. & Bo, S. (2017). Steady diffusion in a drift field: A comparison of large-deviation techniques and multiple-scale analysis. Physical review. E, 96(3), Article ID 032140.
Open this publication in new window or tab >>Steady diffusion in a drift field: A comparison of large-deviation techniques and multiple-scale analysis
2017 (English)In: Physical review. E, ISSN 2470-0045, E-ISSN 2470-0053, Vol. 96, no 3, article id 032140Article in journal (Refereed) Published
Abstract [en]

A particle with internal unobserved states diffusing in a force field will generally display effective advection-diffusion. The drift velocity is proportional to the mobility averaged over the internal states, or effective mobility, while the effective diffusion has two terms. One is of the equilibrium type and satisfies an Einstein relation with the effective mobility while the other is quadratic in the applied force. In this contribution we present two new methods to obtain these results, on the one hand using large deviation techniques and on the other by a multiple-scale analysis, and compare the two. We consider both systems with discrete internal states and continuous internal states. We show that the auxiliary equations in the multiple-scale analysis can also be derived in second-order perturbation theory in a large deviation theory of a generating function (discrete internal states) or generating functional (continuous internal states). We discuss that measuring the two components of the effective diffusion give a way to determine kinetic rates from only first and second moments of the displacement in steady state.

Keywords
Brownian motion, Diffusion, Non-equilibrium fluctuations, Large deviation & rare event statistics, Markovian processes, Biological physics, Statistical physics
National Category
Physical Sciences Mathematics
Identifiers
urn:nbn:se:su:diva-148073 (URN)10.1103/PhysRevE.96.032140 (DOI)000411991200001 ()
Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2022-02-28Bibliographically approved
Bo, S. & Celani, A. (2016). Detecting Concentration Changes with Cooperative Receptors. Journal of statistical physics, 162(5), 1365-1382
Open this publication in new window or tab >>Detecting Concentration Changes with Cooperative Receptors
2016 (English)In: Journal of statistical physics, ISSN 0022-4715, E-ISSN 1572-9613, Vol. 162, no 5, p. 1365-1382Article in journal (Refereed) Published
Abstract [en]

Cells constantly need to monitor the state of the environment to detect changes and timely respond. The detection of concentration changes of a ligand by a set of receptors can be cast as a problem of hypothesis testing, and the cell viewed as a Neyman-Pearson detector. Within this framework, we investigate the role of receptor cooperativity in improving the cell's ability to detect changes. We find that cooperativity decreases the probability of missing an occurred change. This becomes especially beneficial when difficult detections have to be made. Concerning the influence of cooperativity on how fast a desired detection power is achieved, we find in general that there is an optimal value at finite levels of cooperation, even though easy discrimination tasks can be performed more rapidly by noncooperative receptors.

Keywords
Sensing, Cooperativity, Hypothesis testing, Stochastic processes
National Category
Physical Sciences
Identifiers
urn:nbn:se:su:diva-128526 (URN)10.1007/s10955-015-1354-2 (DOI)000371088000014 ()
Available from: 2016-04-06 Created: 2016-03-30 Last updated: 2022-02-23Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-2738-867x

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