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arXiv · 1103.0509

MaNN: Multiple Artificial Neural Networks for modelling the Interstellar Medium

T. Grassi·E. Merlin·L. Piovan·U. Buonomo·C. Chiosi
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Abstract

Modelling the complex physics of the Interstellar Medium (ISM) in the context of large-scale numerical simulations is a challenging task. A number of methods have been proposed to embed a description of the ISM into different codes. We propose a new way to achieve this task: Artificial Neural Networks (ANNs). The ANN has been trained on a pre-compiled model database, and its predictions have been compared to the expected theoretical ones, finding good agreement both in static and in dynamical tests run using the Padova Tree-SPH code \textsc{EvoL}. A neural network can reproduce the details of the interstellar gas evolution, requiring limited computational resources. We suggest that such an algorithm can replace a real-time calculation of mass elements chemical evolution in hydrodynamical codes.

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T. Grassi, E. Merlin, L. Piovan, U. Buonomo, C. Chiosi. 2011-03-02. MaNN: Multiple Artificial Neural Networks for modelling the Interstellar Medium. https://arxiv.org/abs/1103.0509

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