Spectral Homogenization of the Radiative Transfer Equation via Low-Rank Tensor Train Decomposition

• URL: http://arxiv.org/abs/2602.17708v1
• Date: Thu, 12 Feb 2026 22:41:39 GMT
• Title: Spectral Homogenization of the Radiative Transfer Equation via Low-Rank Tensor Train Decomposition
• Abstract summary: Radiative transfer in absorbing-scattering media requires solving a transport equation across a spectral domain with 105 - 106 molecular absorption lines.<n>We show that the Young-measure homogenization framework produces solution tensors I that admit low-rank tensor-train decompositions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Radiative transfer in absorbing-scattering media requires solving a transport equation across a spectral domain with 10^5 - 10^6 molecular absorption lines. Line-by-line (LBL) computation is prohibitively expensive, while existing approximations sacrifice spectral fidelity. We show that the Young-measure homogenization framework produces solution tensors I that admit low-rank tensor-train (TT) decompositions whose bond dimensions remain bounded as the spectral resolution Ns increases. Using molecular line parameters from the HITRAN database for H2O and CO2, we demonstrate that: (i) the TT rank saturates at r = 8 (at tolerance e = 10^-6) from Ns = 16 to 4096, independent of single-scattering albedo, Henyey-Greenstein asymmetry, temperature, and pressure; (ii) quantized tensor-train (QTT) representations achieve sub-linear storage scaling; (iii) in a controlled comparison using identical opacity data and transport solver, the homogenized approach achieves over an order of magnitude lower L2 error than the correlated-k distribution at equal cost; and (iv) for atomic plasma opacity (aluminum at 60 eV, TOPS database), the TT rank saturates at r = 15 with fundamentally different spectral structure (bound-bound and bound-free transitions spanning 12 decades of dynamic range), confirming that rank boundedness is a property of the transport equation rather than any particular opacity source. These results establish that the spectral complexity of radiative transfer has a finite effective rank exploitable by tensor decomposition, complementing the spatial-angular compression achieved by existing TT and dynamical low-rank approaches.

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