Deducing effective light transport parameters in optically thin systems
Authors: Mazzamuto G., Pattelli L., Toninelli C., Wiersma D.
Autors Affiliation: European Laboratory for Non-linear Spectroscopy (LENS), Università di Firenze, 50019 Sesto Fiorentino (FI), Italy;
CNR-INO, Istituto Nazionale di Ottica, Via N. Carrara 1, 50019 Sesto Fiorentino (FI), Italy;
QSTAR, Largo Enrico Fermi 2, 50125 Firenze, Italy;
Department of Physics, Università di Firenze, 50019 Sesto Fiorentino (FI), Italy
Abstract: We present an extensive Monte Carlo study on light transport in optically thin slabs, addressing both axial and transverse propagation. We systematically characterize diffusive transport in this intermediate scattering regime, notably in terms of the spatial variance of the transmitted/reflected profile. Focusing on late, multiply scattered light, we test the validity of the prediction cast by diffusion theory that the spatial variance should grow independently of absorption and, to a first approximation, of the sample thickness and refractive index contrast. Based on a large set of simulated data, we build a freely available look-up table routine enabling reliable and precise determination of the microscopic transport parameters starting from robust observables which are independent from absolute intensity measurements. We also present the Monte Carlo software package that was developed for the purpose of this study.
Journal/Review: NEW JOURNAL OF PHYSICS
Volume: 18 Pages from: 023036 to: 023036
More Information: We wish to thank M Burresi for fruitful discussions. This work is financially supported by the European Network of Excellence Nanophotonics for Energy Efficiency and the ERC through the Advanced Grant PhotBots, project reference 291349 funded under FP7-IDEAS-ERC. CT and GM acknowledge support from the MIUR program Atom-based Nanotechnology and from the Ente Cassa di Risparmio di Firenze with the project GRANCASSA.KeyWords: diffusion; turbid media; photon migration; light propagation in tissues; Monte Carlo simulationsDOI: 10.1088/1367-2630/18/2/023036Citations: 6data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2020-05-24References taken from IsiWeb of Knowledge: (subscribers only)Connecting to view paper tab on IsiWeb: Click hereConnecting to view citations from IsiWeb: Click here