arXiv subjects

Arnaud Buhot

Publications and source records attributed to Arnaud Buhot.

18 recordsLinked to original sources

arXiv2016

Polymer translocation through nano-pores in vibrating thin membranes

Polymer translocation is a promising strategy for the next-generation DNA sequencing technologies. The use of biological and synthetic nano-pores, however, still suffers from serious drawbacks. In particular, the width of the membrane layer can accommodate several bases at the same time, making difficult accurate sequencing applications. More recently, the use of graphene membranes has paved the way to new sequencing capabilities, with the possibility to measure transverse currents, among other advances. The reduced thickness of these new membranes poses new questions on the effect of deformability and vibrations of the membrane on the translocation process, two features which are not taken into account in the well-established theoretical frameworks. Here, we make a first step forward in this direction. We report numerical simulation work on a model system simple enough to allow gathering significant insight on the effect of these features on the average translocation time, with appropriate statistical significance. We have found that the interplay between thermal fluctuations and the deformability properties of the nano-pore play a crucial role in determining the process. We conclude by discussing new directions for further work.

cond-mat.soft↗

arXiv2005

Exact curvilinear diffusion coefficients in the repton model

The Rubinstein-Duke or repton model is one of the simplest lattice model of reptation for the diffusion of a polymer in a gel or a melt. Recently, a slightly modified model with hardcore interactions between the reptons has been introduced. The curvilinear diffusion coefficients of both models are exactly determined for all chain lengths. The case of periodic boundary conditions is also considered.

cond-mat.soft↗

arXiv2004

Hybridization Isotherms of DNA Microarrays and the Quantification of Mutation Studies

Background: Diagnostic DNA arrays for detection of point mutations as markers for cancer usually function in the presence of a large excess of wild type DNA. This excess can give rise to false positives due to competitive hybridization of the wild type target at the mutation spot. The analysis of the DNA array data is typically qualitative aiming to establish the presence or absence of a particular point mutation. Our theoretical approach yields methods for quantifying the analysis so as to obtain the ratio of concentrations of mutated and wild type DNA. Method: The theory is formulated in terms of the hybridization isotherms relating the hybridization fraction at the spot to the composition of the sample solutions at thermodynamic equilibrium. It focuses on samples containing an excess of single stranded DNA and on DNA arrays with low surface density of probes. The hybridization equilibrium constants can be obtained by the nearest neighbor method. Results: Two approaches allow us to obtain quantitative results from the DNA array data. In one the signal of the mutation spot is compared with that of the wild type spot. The implementation requires knowledge of the saturation intensity of the two spots. The second approach requires comparison of the intensity of the mutation spot at two different temperatures. In this case knowledge of the saturation signal is not always necessary. Conclusions: DNA arrays can be used to obtain quantitative results on the concentration ratio of mutated DNA to wild type DNA in studies of somatic point mutations.

q-bio.BM↗

arXiv2004

Cluster algorithm for non-additive hard-core mixtures

In this paper, we present a cluster algorithm for the numerical simulations of non-additive hard-core mixtures. This algorithm allows one to simulate and equilibrate systems with a number of particles two orders of magnitude larger than previous simulations. The phase separation for symmetric binary mixtures is studied for different non-additvities as well as for the Widom-Rowlinson model (B. Widom and J. S. Rowlinson, J. Chem. Phys. 52, 1670 (1970)) in two and three dimensions. The critical densities are determined from finite size scaling. The critical exponents for all the non-additivities are consistent with the Ising universality class.

cond-mat.soft↗

arXiv2003

Kovacs effect and fluctuation-dissipation relations in 1D kinetically constrained models

Strong and fragile glass relaxation behaviours are obtained simply changing the constraints of the kinetically constrained Ising chain from symmetric to purely asymmetric. We study the out-of-equilibrium dynamics of those two models focusing on the Kovacs effect and the fluctuation--dissipation relations. The Kovacs or memory effect, commonly observed in structural glasses, is present for both constraints but enhanced with the asymmetric ones. Most surprisingly, the related fluctuation-dissipation (FD) relations satisfy the FD theorem in both cases. This result strongly differs from the simple quenching procedure where the asymmetric model presents strong deviations from the FD theorem.

cond-mat.stat-mech↗

arXiv2002

Simple strong glass forming models: mean-field solution with activation

We introduce simple models, inspired by previous models for froths and covalent glasses, with trivial equilibrium properties but dynamical behaviour characteristic of strong glass forming systems. These models are also a generalization of backgammon or urn models to a non--constant number of particles, where entropic barriers are replaced by energy barriers, allowing for the existence of activated processes. We formulate a mean--field version of the models, which keeps most of the features of the finite dimensional ones, and solve analytically the out--of--equilibrium dynamics in the low temperature regime where activation plays an essential role.

cond-mat.stat-mech↗

arXiv2002

Fluctuation-dissipation relations in the activated regime of simple strong-glass models

We study the out-of-equilibrium fluctuation-dissipation (FD) relations in the low temperature, finite time, physical aging regime of two simple models with strong glass behaviour, the Fredrickson-Andersen model and the square-plaquette interaction model. We explicitly show the existence of unique, waiting-time independent dynamical FD relations. While in the Fredrickson-Andersen model the FD theorem is obeyed at all times, the plaquette model displays piecewise linear FD relations, similar to what is found in disordered mean-field models and in simulations of supercooled liquids, and despite the fact that its static properties are trivial. We discuss the wider implications of these results.

cond-mat.stat-mech↗

arXiv2002

Rigorous Bounds to Retarded Learning

We show that the lower bound to the critical fraction of data needed to infer (learn) the orientation of the anisotropy axis of a probability distribution, determined by Herschkowitz and Opper [Phys.Rev.Lett. 86, 2174 (2001)], is not always valid. If there is some structure in the data along the anisotropy axis, their analysis is incorrect, and learning is possible with much less data points.

cond-mat.dis-nn↗

arXiv2001

On the Extension Behavior of Helicogenic Polypeptides

The force laws governing the extension behavior of homopolypeptides are obtained from a phenomenological free energy capable of describing the helix-coil transition. Just above the melting temperature of the free chains, T*, the plot of force, f, vs. end-to-end distance, R, exhibits two plateaus associated with coexistence of helical and coil domains. The lower plateau is due to tension induced onset of helix-coil transition. The higher plateau corresponds to the melting of the helices by overextension. Just below T* the f-R plot exhibits only the upper plateau. The f-R plots, the helical fraction, the number of domains and their polydispersity are calculated for two models: In one the helical domains are viewed as rigid rods while in the second they are treated as worm like chains.

cond-mat.soft↗

arXiv2001

Crossover from Fragile to Strong Glassy Behaviour in Kinetically Constrained Systems

We show the existence of fragile-to-strong transitions in kinetically constrained systems by studying the equilibrium and out-of-equilibrium dynamics of a generic constrained Ising spin chain which interpolates between the symmetric and fully asymmetric cases. We find that for large but finite asymmetry the model displays a crossover from fragile to strong glassy behaviour at finite temperature, which is controlled by the asymmetry parameter. The relaxation in the fragile region presents stretched exponential behaviour, with a temperature dependent stretching exponent which is predicted. Our results are confirmed by numerical simulations.

cond-mat.stat-mech↗

arXiv2001

Glassy behaviour in a 3-state spin model

In this article we study a simple spin model which has a non-interacting Hamiltonian but constrained dynamics. The model, which is a simplification of a purely toplogical cellular model, displays glassy behaviour, involves activated processes and exhibits two-step relaxation. This is a consequence of the existence of annihilation-diffusion processes on two distinct time-scales, one temperature independent and the other an exponential function of inverse temperature. In fact, there are several such inter-coupled microscopic processes and great richness therein. Two versions of the model are considered, one with a single absorbing ground state and the other with a highly degenerate ground state. These display qualitatively similar but quantitatively distinct macroscopic behaviour and related, but different, microscopic behaviour.

cond-mat.dis-nn↗

arXiv2000

Storage Capacity of the Tilinglike Learning Algorithm

The storage capacity of an incremental learning algorithm for the parity machine, the Tilinglike Learning Algorithm, is analytically determined in the limit of a large number of hidden perceptrons. Different learning rules for the simple perceptron are investigated. The usual Gardner-Derrida one leads to a storage capacity close to the upper bound, which is independent of the learning algorithm considered.

cond-mat.dis-nn↗

arXiv2000

Reply to A. Louis Comment

Reply to A. Louis Comment: Fluid-solid phase-separation in hard-sphere mixtures is unrelated to bond-percolation

cond-mat.soft↗

arXiv1999

Storage capacity of a constructive learning algorithm

Upper and lower bounds for the typical storage capacity of a constructive algorithm, the Tilinglike Learning Algorithm for the Parity Machine [M. Biehl and M. Opper, Phys. Rev. A {\bf 44} 6888 (1991)], are determined in the asymptotic limit of large training set sizes. The properties of a perceptron with threshold, learning a training set of patterns having a biased distribution of targets, needed as an intermediate step in the capacity calculation, are determined analytically. The lower bound for the capacity, determined with a cavity method, is proportional to the number of hidden units. The upper bound, obtained with the hypothesis of replica symmetry, is close to the one predicted by Mitchinson and Durbin [Biol. Cyber. {\bf 60} 345 (1989)].

cond-mat.dis-nn↗

arXiv1998

Critical packing fraction at the phase separation transition in hard-core mixtures

In this paper, I relate the phase separation transition in binary hard-core mixtures in the limit of small size ratio to a bond percolation transition. It allows to estimate the critical packing fraction at the transition as a function of the size ratio and the composition of the mixture for different shapes of objects. The theoretical predictions are in excellent quantitative agreement with numerical simulations of binary parallel hard squares mixtures.

cond-mat.stat-mech↗

arXiv1998

Phase Separation in Two-Dimensional Additive Mixture

We study 2-dimensional binary mixtures of parallel squares as well as of disks. A recent cluster algorithm allows us to establish an entropic demixing transition between a homogeneously packed fluid phase and a demixed phase of a practically close-packed aggregate of large squares surrounded by a fluid of small squares.

cond-mat.soft↗

arXiv1998

Numerical Solution of Hard-Core Mixtures

We study the equilibrium phase diagram of binary mixtures of hard spheres as well as of parallel hard cubes. A superior cluster algorithm allows us to establish and to access the demixed phase for both systems and to investigate the subtle interplay between short-range depletion and long-range demixing.

cond-mat.stat-mech↗

arXiv1997

Phase transitions in optimal unsupervised learning

We determine the optimal performance of learning the orientation of the symmetry axis of a set of P = alpha N points that are uniformly distributed in all the directions but one on the N-dimensional sphere. The components along the symmetry breaking direction, of unitary vector B, are sampled from a mixture of two gaussians of variable separation and width. The typical optimal performance is measured through the overlap Ropt=B.J* where J* is the optimal guess of the symmetry breaking direction. Within this general scenario, the learning curves Ropt(alpha) may present first order transitions if the clusters are narrow enough. Close to these transitions, high performance states can be obtained through the minimization of the corresponding optimal potential, although these solutions are metastable, and therefore not learnable, within the usual bayesian scenario.

cond-mat.dis-nn↗