Ref HAL: inserm-02952457_v1
PMID 32958811
DOI: 10.1038/s41467-020-18455-z
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Résumé:

Genetic programs operating in a history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on standardized recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular, do not require cell-cell communication channels, and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed automated workflows that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.

Ref HAL: hal-02986282_v1
Ref Arxiv: 2005.06520
DOI: 10.1063/5.0015227
Ref. & Cit.: NASA ADS
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It has recently become possible to prepare ultrastable glassy materials characterised by structural relaxation times which vastly exceed the duration of any feasible experiment. Similarly, new algorithms have led to the production of ultrastable computer glasses. Is it possible to obtain a reliable estimate of a structural relaxation time that is too long to be measured? We review, organise, and critically discuss various methods to estimate very long relaxation times. We also perform computer simulations of three dimensional ultrastable hard spheres glasses to test and quantitatively compare some of these methods for a single model system. The various estimation methods disagree significantly and it is not yet clear how to accurately estimate extremely long relaxation times.

Ref HAL: hal-02986302_v1
PMID 32909772
Ref Arxiv: 2002.01317
DOI: 10.1103/PhysRevLett.125.085505
WoS: 000561724800007
Ref. & Cit.: NASA ADS
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2 Citations
Résumé:

We devise a generic strategy and simple numerical models for multi-component metallic glasses for which the swap Monte Carlo algorithm can produce highly stable equilibrium configurations equivalent to experimental systems cooled more than $10^7$ times slower than in conventional simulations. This paves the way for a deeper understanding of thermodynamic, dynamic, and mechanical properties of metallic glasses. As a first application, we extend configurational entropy measurements down to the experimental glass temperature, and demonstrate a qualitative evolution of the mechanical response of metallic glasses of increasing stability towards brittleness.

Ref HAL: hal-02986305_v1
PMID 32955295
Ref Arxiv: 1912.11510
DOI: 10.1103/PhysRevLett.125.108001
WoS: 000564051900012
Ref. & Cit.: NASA ADS
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15 Citations
Résumé:

Finite-dimensional signatures of spinodal criticality are notoriously difficult to come by. The dynamical transition of glass-forming liquids, first described by mode-coupling theory, is a spinodal instability preempted by thermally activated processes that also limit how close the instability can be approached. We combine numerical tools to directly observe vestiges of the spinodal criticality in finite-dimensional glass formers. We use the swap Monte Carlo algorithm to efficiently thermalise configurations beyond the mode-coupling crossover, and analyze their dynamics using a scheme to screen out activated processes, in spatial dimensions ranging from $d=3$ to $d=9$. We observe a strong softening of the mean-field square-root singularity in $d=3$ that is progressively restored as $d$ increases above $d=8$, in surprisingly good agreement with perturbation theory.

Ref HAL: hal-02925447_v1
Ref Arxiv: 2004.10555
DOI: 10.1103/PhysRevE.102.042129
WoS: WOS:000582805100002
Ref. & Cit.: NASA ADS
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We use computer simulations to investigate the extended phase diagram of a supercooled liquid linearly coupled to a quenched reference configuration. An extensive finite-size scaling analysis demonstrates the existence of a random-field Ising model (RFIM) critical point and of a first-order transition line, in agreement with field-theoretical approaches. The dynamics in the vicinity of this critical point resembles the peculiar activated scaling of RFIM-like systems, and the overlap autocorrelation displays a logarithmic stretching. Our study firmly establishes the RFIM criticality in three-dimensional supercooled liquids at equilibrium.

Ref HAL: hal-02925446_v1
Ref Arxiv: 2007.07625
DOI: 10.1063/5.0022614
WoS: WOS:000600047800001
Ref. & Cit.: NASA ADS
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Résumé:

The overlap, or similarity, between liquid configurations is at the core of the mean-field description of the glass transition, and remains a useful concept when studying three-dimensional glass-forming liquids. In liquids, however, the overlap involves a tolerance, typically of a fraction $a/\sigma$ of the inter-particle distance, associated with how precisely similar two configurations must be for belonging to the same physically relevant "state". Here, we systematically investigate the dependence of the overlap fluctuations and of the resulting phase diagram when the tolerance is varied over a large range. We show that while the location of the dynamical and thermodynamic glass transition (if present) are independent of $a/\sigma$, that of the critical point associated with a transition between a low- and a high-overlap phases in the presence of an applied source nontrivially depends on the value of $a/\sigma$. We rationalize our findings by using liquid-state theory and the hypernetted chain (HNC) approximation for correlation functions. In addition, we confirm the theoretical trends by studying a three-dimensional glass-former by computer simulations. We show in particular that a specific choice of $a/\sigma$ maximizes the temperature of the critical point, pushing it up in a liquid region where viscosity is low and computer investigations are easier due to a significantly faster equilibration.

Ref HAL: hal-02907400_v1
DOI: 10.1063/5.0004732
WoS: WOS:000526712200002
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We present an information-theoretic approach inspired by distributional clustering to assess the structural heterogeneity of particulate systems. Our method identifies communities of particles that share a similar local structure by harvesting the information hidden in the spatial variation of two- or three-body static correlations. This corresponds to an unsupervised machine learning approach that infers communities solely from the particle positions and their species. We apply this method to three models of supercooled liquids and find that it detects subtle forms of local order, as demonstrated by a comparison with the statistics of Voronoi cells. Finally, we analyze the time-dependent correlation between structural communities and particle mobility and show that our method captures relevant information about glassy dynamics.