The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $148,832 Project Grant to The Trustees of Columbia University in the City of New York, operating as Columbia University, to develop fast, low-memory numerical methods for solving the radiative transfer equation. This three-year grant, under NSF's Mathematical and Physical Sciences program (CFDA 47.049), aims to overcome the computational challenges associated with the high dimensionality of the radiative transfer equation, which arises in applications such as medical imaging, astrophysics, weather, and climate modeling. The project will create discontinuous Galerkin spectral element methods and goal-oriented hp-adaptive mesh refinement techniques to enable efficient, high-fidelity simulations of the full radiative transfer equation. This work will also support inverse problem solutions and machine learning emulators to further enhance scientific understanding and modeling capabilities in these important application domains. The grant includes an interdisciplinary training component to develop expertise in mathematics and atmospheric science.
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