Anomalous Radiative Transfer in Heterogeneous Media

Author:

Tommasi Federico1ORCID,Pattelli Lorenzo23ORCID,Cavalieri Stefano1ORCID,Fini Lorenzo1ORCID,Paolucci Michela1ORCID,Pini Ernesto13ORCID,Sassaroli Angelo4ORCID,Martelli Fabrizio1ORCID

Affiliation:

1. Dipartimento di Fisica e Astronomia Università degli Studi di Firenze via Giovanni Sansone 1 Sesto Fiorentino 50019 Italy

2. Istituto Nazionale di Ricerca Metrologica (INRiM) Str. delle Cacce 91 Turin 10135 Italy

3. European Laboratory for Non‐linear Spectroscopy (LENS) via Nello Carrara 1 Sesto Fiorentino 50019 Italy

4. Department of Biomedical Engineering Tufts University 4 Colby Street Medford Massachusetts 02155 USA

Abstract

AbstractMonte Carlo (MC) simulations are the gold standard for describing various transport phenomena and have largely contributed to the understanding of these processes. However, while their implementation for classical transport governed by exponential step‐length distributions is well‐established, widely accepted approaches are still lacking for the more general class of anomalous transport phenomena. In this work, a set of rules for performing MC simulations in anomalous diffusion media is identified, which is also applicable in the case of finite‐size geometries and/or heterogeneous inclusions. The results are presented in the context of radiative transfer, however their implications extend to all types of anomalous transport. The proposed set of rules exhibits full compatibility with the pathlength invariance property for random trajectories, and with the important radiometric concept of fluence. Additionally, it reveals the counter‐intuitive possibility of introducing interfaces between independent subdomains with identical properties, which arise from the fact that non‐exponential step‐length distributions have a “memory” that can in principle be reset when traversing a boundary. These results have far‐reaching consequences not just for the physical interpretation of the corrections required to handle these discontinuities, but also for their experimental verification, due to their expected effects on the observable pathlength distributions.

Funder

National Institutes of Health

Nvidia

Publisher

Wiley

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