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Bruot N.,University of Cambridge | Damet L.,University of Cambridge | Kotar J.,University of Cambridge | Cicuta P.,University of Cambridge | And 2 more authors.
Physical Review Letters | Year: 2011

A two-state oscillator in a viscous liquid is composed of a micron-scale particle whose intrinsic dynamics is defined by linear potentials that undergo configuration-coupled transitions and is externally driven by a piecewise constant periodic force of varying amplitude and frequency. This elementary example of "active matter" has the minimal elements that allow us to study synchronization in the presence of thermal fluctuations. Experiments reveal the presence of synchronized states (and Arnol'd tongues), which we explain using analytical and numerical calculations. The system maintains synchronization by adjusting the phase between the bead and the clock. We discuss the relevance of this model to synchronization in real-world systems, including the role of thermal noise. © 2011 American Physical Society. Source


Bruot N.,University of Cambridge | Kotar J.,University of Cambridge | De Lillo F.,University of Turin | De Lillo F.,University of Genoa | And 4 more authors.
Physical Review Letters | Year: 2012

Motile cilia are highly conserved structures in the evolution of organisms, generating the transport of fluid by periodic beating, through remarkably organized behavior in space and time. It is not known how these spatiotemporal patterns emerge and what sets their properties. Individual cilia are nonequilibrium systems with many degrees of freedom. However, their description can be represented by simpler effective force laws that drive oscillations, and paralleled with nonlinear phase oscillators studied in physics. Here a synthetic model of two phase oscillators, where colloidal particles are driven by optical traps, proves the role of the average force profile in establishing the type and strength of synchronization. We find that highly curved potentials are required for synchronization in the presence of noise. The applicability of this approach to biological data is also illustrated by successfully mapping the behavior of cilia in the alga Chlamydomonas onto the coarse-grained model. © 2012 American Physical Society. Source


Grilli J.,University of Milan | Bassetti B.,University of Milan | Bassetti B.,National Institute of Nuclear Physics, Italy | Maslov S.,Brookhaven National Laboratory | And 2 more authors.
Nucleic Acids Research | Year: 2012

We propose and study a class-expansioninnovationloss model of genome evolution taking into account biological roles of genes and their constituent domains. In our model, numbers of genes in different functional categories are coupled to each other. For example, an increase in the number of metabolic enzymes in a genome is usually accompanied by addition of new transcription factors regulating these enzymes. Such coupling can be thought of as a proportional 'recipe' for genome composition of the type 'a spoonful of sugar for each egg yolk'. The model jointly reproduces two known empirical laws: the distribution of family sizes and the non-linear scaling of the number of genes in certain functional categories (e.g. transcription factors) with genome size. In addition, it allows us to derive a novel relation between the exponents characterizing these two scaling laws, establishing a direct quantitative connection between evolutionary and functional categories. It predicts that functional categories that grow faster-than-linearly with genome size to be characterized by flatter-than-average family size distributions. This relation is confirmed by our bioinformatics analysis of prokaryotic genomes. This proves that the joint quantitative trends of functional and evolutionary classes can be understood in terms of evolutionary growth with proportional recipes. © The Author(s) 2011. Published by Oxford University Press. Source


Javer A.,University of Cambridge | Long Z.,University of Minnesota | Nugent E.,University of Cambridge | Grisi M.,University of Cambridge | And 7 more authors.
Nature Communications | Year: 2013

In bacteria, chromosomal architecture shows strong spatial and temporal organization, and regulates key cellular functions, such as transcription. Tracking the motion of chromosomal loci at short timescales provides information related to both the physical state of the nucleo-protein complex and its local environment, independent of large-scale motions related to genome segregation. Here we investigate the short-time (0.1-10 s) dynamics of fluorescently labelled chromosomal loci in Escherichia coli at different growth rates. At these timescales, we observe for the first time a dependence of the loci's apparent diffusion on both their subcellular localization and chromosomal coordinate, and we provide evidence that the properties of the chromosome are similar in the tested growth conditions. Our results indicate that either non-equilibrium fluctuations due to enzyme activity or the organization of the genome as a polymer-protein complex vary as a function of the distance from the origin of replication. © 2013 Macmillan Publishers Limited. All rights reserved. Source


Rotondo P.,University of Milan | Cosentino Lagomarsino M.,CNRS Laboratory of Computational and Quantitative Biology | Viola G.,Chalmers University of Technology | Viola G.,RWTH Aachen
Physical Review Letters | Year: 2015

Using an approach inspired from spin glasses, we show that the multimode disordered Dicke model is equivalent to a quantum Hopfield network. We propose variational ground states for the system at zero temperature, which we conjecture to be exact in the thermodynamic limit. These ground states contain the information on the disordered qubit-photon couplings. These results lead to two intriguing physical implications. First, once the qubit-photon couplings can be engineered, it should be possible to build scalable pattern-storing systems whose dynamics is governed by quantum laws. Second, we argue with an example of how such Dicke quantum simulators might be used as a solver of "hard" combinatorial optimization problems. © 2015 American Physical Society. Source

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