Search results for " Integra"
showing 10 items of 2527 documents
Optical Probing (EOFM/TRI): A large set of complementary applications for ultimate VLSI
2013
International audience; Electro Optical Techniques (EOFM: Electro Optical Frequency Mapping and EOP: Electro Optical Probing) and Dynamic Light Emission Techniques (TRE: Time Resolved Emission and TRI: Time Resolved Imaging) are dynamic optical probing techniques widely used at IC level for design debug and defect localization purpose. They can pinpoint the origin of timing issue or logic fault in up to date CMOS devices. Each technique has its advantages and its drawbacks allowing a common set of applications and more specific ones. We have been involved in the development of the most advanced techniques related to EOFM and TRI on various devices (down to 28nm technology). What we can expe…
Characterization of thermo-optical 2×2 switch configurations made of Dielectric Loaded Surface Plasmon Polariton Waveguides for telecom routing archi…
2012
We report on the characterization of thermo-optic switch structures based on Dielectric Loaded Surface Plasmon Polariton Waveguide for high data bit rate transfer. Performances are extracted by Leakage Radiation Microscopy and compared to numerical results.
Stable proton exchanged waveguides in Lithium Tantalate
2008
alpha, beta(1), and kappa(2) phases are investigated for planar waveguide fabrication by proton exchange in congruent lithium tantalate. The effective indices of planar waveguide eigenmodes were monitored over time, revealing that the exchange process induces aging instabilities in all phases except alpha.
Colloidal lithography and Metal-Organic Chemical Vapor Deposition process integration to fabricate ZnO nanohole arrays
2010
A complete set up of optimal process conditions for an effective colloidal lithography/catalyst assisted MOCVD process integration is presented. It mainly focuses on the determination of the deposition temperature threshold for ZnO Metal-Organic Chemical Vapour Deposition (MOCVD) as well as the concentration of metal-organic silver (Ag) catalyst. Indeed, the optimization of such process parameters allows to tailor the ZnO film morphology in order to make the colloidal lithography/catalyst assisted MOCVD approach a valuable bottom up method to fabricate bi-dimensional ordered ZnO nanohole arrays. (C) 2010 Elsevier B.V. All rights reserved.
Explicit polynomial solutions of fourth order linear elliptic Partial Differential Equations for boundary based smooth surface generation
2011
We present an explicit polynomial solution method for surface generation. In this case the surface in question is characterized by some boundary configuration whereby the resulting surface conforms to a fourth order linear elliptic Partial Differential Equation, the Euler–Lagrange equation of a quadratic functional defined by a norm. In particular, the paper deals with surfaces generated as explicit Bézier polynomial solutions for the chosen Partial Differential Equation. To present the explicit solution methodologies adopted here we divide the Partial Differential Equations into two groups namely the orthogonal and the non-orthogonal cases. In order to demonstrate our methodology we discus…
A numerical approach to Blow-up issues for dispersive perturbations of Burgers' equation
2014
We provide a detailed numerical study of various issues pertaining to the dynamics of the Burgers equation perturbed by a weak dispersive term: blow-up in finite time versus global existence, nature of the blow-up, existence for "long" times, and the decomposition of the initial data into solitary waves plus radiation. We numerically construct solitons for fractionary Korteweg-de Vries equations.
Drilling Systems: Stability and Hidden Oscillations
2013
There are many mathematical models of drilling systems Despite, huge efforts in constructing models that would allow for precise analysis, drilling systems, still experience breakdowns. Due to complexity of systems, engineers mostly use numerical analysis, which may lead to unreliable results. Nowadays, advances in computer engineering allow for simulations of complex dynamical systems in order to obtain information on the behavior of their trajectories. However, this simple approach based on construction of trajectories using numerical integration of differential equations describing dynamical systems turned out to be quite limited for investigation of stability and oscillations of these s…
Iterative Reconstruction of Memory Kernels.
2017
In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations. In this article, we propose an iterative method for memory reconstruction from dynamical correlation functions. Compared to previously proposed noniterative techniques, it ensures by construction that the target correlation functions of the original fine-grained systems are reproduced accurately by the coarse-grained system, regardless of time step and disc…
Non-linear systems under parametric white noise input: digital simulation and response
2005
Abstract Monte Carlo technique is constituted of three steps. Therefore, improving such technique in practice means, improving the procedure used in one of the three following steps: (i) sample paths of the stochastic input process, (ii) calculation of the outputs corresponding to the generated input samples by using methods of classical dynamics and (iii) estimating statistics of the output process from sample outputs related to the previous step. For linear and non-linear systems driven by parametric impulsive inputs such as normal or non-normal white noises, a general integration method requires a considerable reduction of the integration step when the impulse occurs, treating the impuls…
A new strategy for effective learning in population Monte Carlo sampling
2016
In this work, we focus on advancing the theory and practice of a class of Monte Carlo methods, population Monte Carlo (PMC) sampling, for dealing with inference problems with static parameters. We devise a new method for efficient adaptive learning from past samples and weights to construct improved proposal functions. It is based on assuming that, at each iteration, there is an intermediate target and that this target is gradually getting closer to the true one. Computer simulations show and confirm the improvement of the proposed strategy compared to the traditional PMC method on a simple considered scenario.