A Generalized Linear Transport Model for Spatially-Correlated Stochastic Media
Anthony B. Davis, Feng Xu

TL;DR
This paper introduces a generalized linear transport model for stochastic media with long-range correlations, replacing exponential attenuation with a power-law form, and develops analytical and numerical methods to study its properties and implications.
Contribution
It formulates a new transport model with power-law attenuation, derives foundational equations, and develops numerical solutions, extending classical theory to media with long-range correlations.
Findings
Power-law attenuation generalizes exponential decay in transport.
Monte Carlo simulations confirm scaling laws for transmittance.
Model exhibits violation of angular reciprocity for finite parameter a.
Abstract
We formulate a new model for transport in stochastic media with long-range spatial correlations where exponential attenuation (controlling the propagation part of the transport) becomes power law. Direct transmission over optical distance , for fixed physical distance , thus becomes , with standard exponential decay recovered when . Atmospheric turbulence phenomenology for fluctuating optical properties rationalizes this switch. Foundational equations for this generalized transport model are stated in integral form for spatial dimensions. A deterministic numerical solution is developed in using Markov Chain formalism, verified with Monte Carlo, and used to investigate internal radiation fields. Standard two-stream theory, where diffusion is exact, is recovered when . Differential diffusion equations are not presently…
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