Gaussian entanglement induced by an extended thermal environment

We study stationary entanglement among three harmonic oscillators which are dipole coupled to a one-dimensional or a three-dimensional bosonic environment. The analysis of the open-system dynamics is performed with generalized quantum Langevin equations which we solve exactly in Fourier representation. The focus lies on Gaussian bipartite and tripartite entanglement induced by the highly non-Markovian interaction mediated by the environment. This environment-induced interaction represents an effective many-parties interaction with a spatial long-range feature: a main finding is that the presence of a passive oscillator is detrimental for the stationary two-mode entanglement. Furthermore, our results strongly indicate that the environment-induced entanglement mechanism corresponds to uncontrolled feedback which is predominantly coherent at low temperatures and for moderate oscillator-environment coupling as compared to the oscillator frequency.Comment: 15 page, 6 figure

Real time optimization of the sterilization process in a canning industry

[Abstract] Sterilization process is aimed to inactivate potentially harmful microorganisms. To that purpose the packaged food is subject to a time/temperature profile. In the canning industry such profiles are chosen based on the experience of the operator. In the presence of perturbations, such as steam supply problems, operators must react and design new profiles which, in most of the cases, are too conservative and/or may lead to the batch rejection, either because of quality or safety reasons. In order to overcome this problem, we propose in this work a model based real time optimization (RTO) strategy. The model, which describes the different relevant aspects of the plant (retort/can temperature, color dynamics, microorganism lethality, energy consumption, etc.) is used to predict the behavior of the system. Plant measurements are taken periodically and, in the event of a perturbation, an optimization procedure is run to compute a new time/temperature profile based on the past measurements.[Resumen] El proceso de esterilización está dirigido a inactivar microorganismos potencialmente dañinos. A tal fin, los alimentos envasados están sujetos a un perfil de tiempo / temperatura. En la industria de la industria conservera, estos perfiles se eligen en función de la experiencia del operador. En presencia de perturbaciones, como problemas de suministro de vapor, los operadores deben reaccionar y diseñar nuevos perfiles que, en la mayoría de los casos, son demasiado conservadores y / o pueden provocar el rechazo del lote, ya sea por razones de calidad o seguridad. Para superar este problema, proponemos en este trabajo una estrategia de optimización en tiempo real (RTO) basada en un modelo. El modelo, que describe los diferentes aspectos relevantes de la planta (temperatura de réplica / lata, dinámica del color, letalidad de microorganismos, consumo de energía, etc.) se utiliza para predecir el comportamiento del sistema. Las mediciones de la planta se toman periódicamente y, en el caso de una perturbación, se ejecuta un procedimiento de optimización para calcular un nuevo perfil de tiempo / temperatura basado en las mediciones anteriores

Estimation of single-cell parameters from a distribution of bacterial size

1 póster presentado al Cell Size Regulation EMBO Workshop, 14-18 September 2016Funding project DPI2014-54085-JINPeer reviewe

Estimation of parameters in geotechnical backanalysis. II- Application to a tunnel excavation problem

A general statistical framework to perform backanalysis in geotechnical problems from field instrumentation has been presented in a companion paper. Here, an application to a real case involving the excavation of a tunnel in stiff overconsolidated clay is described. Both, extensometer and inclinometer measurements are used as input data and elastic moduli of the ground and the value of the K0 coefficient are estimated. The finite element method is used as the computational procedure to solve the direct problem, and has been coupled to the identification algorithm as described in the companion paper. In addition, a discussion on the reliability of the parameters identified is presented

Asymptotic Discord and Entanglement of Non-Resonant Harmonic Oscillators in an Equilibrium Environment

In this work, we calculate the exact asymptotic quantum correlations between two interacting non-resonant harmonic oscillators in a common Ohmic bath. We derive \emph{analytical formulas} for the covariances, fully describing any Gaussian stationary state of the system, and use them to study discord and entanglement in the strong and weak dissipation regimes. We discuss the rich structure of the discord of the stationary separable states arising in the strong dissipation regime. Also under strong dissipation, when the modes are not mechanically coupled, these may entangle only through their interaction with the \emph{common} environment. Interestingly enough, this stationary entanglement is only present within a \emph{finite band of frequencies} and increases with the dissipation rate. In addition, robust entanglement between \emph{detuned} oscillators is observed at low temperature.Comment: 4 pages, 5 figures. References updated. Some changes made. Submitte

Estimation of parameters in geotechnical backanalysis. I- Maximum likehood approach

The estimation of soil and rock parameters based on field instrumentation data is a common procedure in geomechanics. The use of system identification and optimization techniques allows the performance of this type of analyses in a more rational and objective manner. In this paper a probabilistic formulation for the backanalysis problem is presented. The procedure described involves the evaluation of the measurement covariance matrices, which are derived for some geotechnical instruments used in field instrumentation. The algorithm used to solve the mathematical problem of optimization is also presented, as well as its coupling to a finite element code. The algorithm requires the computation of the sensitivity matrix, which can be evaluated “exactly” in terms of the finite element method. Finally, a synthetic example, based on the excavation of a tunnel, is presented in which the elastic modulus E and the K0 parameter of the material are identified from measured displacements. The effect of the number of measurements and their error structure is also discussed

Parameter and variance estimation in geotechnical backanalysis using prior information

A probabilistic framework to perform inverse analysis of geotechnical problems is presented. The formulation allows the incorporation of existing prior information on the parameters in a consistent way. The method is based on the maximum likelihood approach that allows a straightforward introduction of the error structure of field measurements and prior information. The difficulty of ascribing definite values to the uncertainties associated with the various types of observations is overcome by including the corresponding variances in the set of parameters to be identified. The inverse analysis results in a minimization problem that is solved by coupling the optimization technique to the finite element method. Two examples are presented to illustrate the performance of the method. The first one corresponds to a synthetic case simulating the excavation of a tunnel. Young's modulus, K0 value and measurements variances are identified. The second case concerns the excavation of a large underground cavern in which again Young's modulus and K0 are identified. It is shown that introduction of prior information permits the estimation of parameters more consistent with all available informations that include not only monitored displacements but also results from in situ tests carried out during the site investigation stage

Inference of complex biological networks: distinguishability issues and optimization-based solutions

<p>Abstract</p> <p>Background</p> <p>The inference of biological networks from high-throughput data has received huge attention during the last decade and can be considered an important problem class in systems biology. However, it has been recognized that reliable network inference remains an unsolved problem. Most authors have identified lack of data and deficiencies in the inference algorithms as the main reasons for this situation.</p> <p>Results</p> <p>We claim that another major difficulty for solving these inference problems is the frequent lack of uniqueness of many of these networks, especially when prior assumptions have not been taken properly into account. Our contributions aid the distinguishability analysis of chemical reaction network (CRN) models with mass action dynamics. The novel methods are based on linear programming (LP), therefore they allow the efficient analysis of CRNs containing several hundred complexes and reactions. Using these new tools and also previously published ones to obtain the network structure of biological systems from the literature, we find that, often, a unique topology cannot be determined, even if the structure of the corresponding mathematical model is assumed to be known and all dynamical variables are measurable. In other words, certain mechanisms may remain undetected (or they are falsely detected) while the inferred model is fully consistent with the measured data. It is also shown that sparsity enforcing approaches for determining 'true' reaction structures are generally not enough without additional prior information.</p> <p>Conclusions</p> <p>The inference of biological networks can be an extremely challenging problem even in the utopian case of perfect experimental information. Unfortunately, the practical situation is often more complex than that, since the measurements are typically incomplete, noisy and sometimes dynamically not rich enough, introducing further obstacles to the structure/parameter estimation process. In this paper, we show how the structural uniqueness and identifiability of the models can be guaranteed by carefully adding extra constraints, and that these important properties can be checked through appropriate computation methods.</p