Multiscale modeling of light absorption in tissues: limitations of classical homogenization approach.

International audienceIn biophotonics, the light absorption in a tissue is usually modeled by the Helmholtz equation with two constant parameters, the scattering coefficient and the absorption coefficient. This classic approximation of "haemoglobin diluted everywhere" (constant absorption coefficient) corresponds to the classical homogenization approach. The paper discusses the limitations of this approach. The scattering coefficient is supposed to be constant (equal to one) while the absorption coefficient is equal to zero everywhere except for a periodic set of thin parallel strips simulating the blood vessels, where it is a large parameter ω. The problem contains two other parameters which are small: ε, the ratio of the distance between the axes of vessels to the characteristic macroscopic size, and δ, the ratio of the thickness of thin vessels and the period. We construct asymptotic expansion in two cases: ε --> 0, ω --> ∞, δ --> 0, ωδ --> ∞, ε2ωδ --> 0 and ε --> 0, ω --> ∞, δ --> 0, ε2ωδ --> ∞, and and prove that in the first case the classical homogenization (averaging) of the differential equation is true while in the second case it is wrong. This result may be applied in the biomedical optics, for instance, in the modeling of the skin and cosmetics

Bloch wave homogenization of scalar elliptic operators

Periodic homogenization result for selfadjoint operators via Bloch wave method was obtained by Conca and Vanninathan in [12]. Even though the spectral tools used in [12] are not available in non-selfadjoint case, it is possible to recover the complete homogenization result of Murat and Tartar in the periodic case through the Bloch wave method. A dominant Bloch mode is introduced and plays the key role in the homogenization process. It is also established that the remainder does not contribute in the homogenization process. This requires separation of scales between the dominant Bloch mode and the rest. This separation is proved via a Poincaré-type inequality. Further, the proof of homogenization theorem of [12] is simplified

Topology-based denoising of chaos

In this article, we propose a denoising algorithm to denoise a time series y(i) = x(i) + e(i), where {x(i)} is a time series obtained from a time- T map of a uniformly hyperbolic or Anosov flow, and {e(i)} a uniformly bounded sequence of independent and identically distributed (i.i.d.) random variables. Making use of observations up to time n, we create an estimate of x(i) for i<n. We show under typical limiting behaviours of the orbit and the recurrence properties of x(i), the estimation error converges to zero as n tends to infinity with probability 1

Denoising signals corrupted by chaotic noise

We consider the problem of signal estimation where the observed time series is modeled as y(i) = x(i) + s(i) with {x(i)} being an orbit of a chaotic self-map on a compact subset of R-d and {s(i)} a sequence in R-d converging to zero. This model is motivated by experimental results in the literature where the ocean ambient noise and the ocean clutter are found to be chaotic. Making use of observations up to time n, we propose an estimate of s(i) for i < n and show that it approaches s(i) as n -> infinity for typical asymptotic behaviors of orbits. (C) 2010 Elsevier B.V. All rights reserved

HOMOGENIZATION OF STOKES SYSTEM USING BLOCH WAVES

International audienceIn this work, we study the Bloch wave homogenization for the Stokes system with periodic viscosity coefficient. In particular, we obtain the spectral interpretation of the homogenized tensor. The presence of the incompressibility constraint in the model raises new issues linking the homogenized tensor and the Bloch spectral data. The main difficulty is a lack of smoothness for the bottom of the Bloch spectrum, a phenomenon which is not present in the case of the elasticity system. This issue is solved in the present work, completing the homogenization process of the Stokes system via the Bloch wave method