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Welcome to Sapsan!

Sapsan is a pipeline for Machine Learning (ML) based turbulence modeling. While turbulence is important in a wide range of mediums, the pipeline primarily focuses on astrophysical application. With Sapsan, one can create their own custom models or use either conventional or physics-informed ML approaches for turbulence modeling included with the pipeline (estimators). For example, Sapsan features ML models in its set of tools to accurately capture the turbulent nature applicable to Core-Collapse Supernovae.

Purpose

Sapsan takes out all the hard work from data preparation and analysis in turbulence and astrophysical applications, leaving you focused on ML model design, layer by layer.

Website

Check out a website version with a few examples at sapsan.app. The interface is identical to the GUI of the local version of Sapsan, except lacking the ability to edit the model code on the fly and to use mlflow for tracking.

News and Publications

Physics-Informed Machine Learning for Modeling Turbulence in Supernovae
Astrophysical Journal (ApJ) - 2022

Sapsan: Framework for Supernovae Turbulence Modeling with Machine Learning
Journal of Open Source Software (JOSS) - November 26, 2021

Provectus Brings Machine Learning to Numerical Astrophysics, Helping Simulate Turbulence in Supernovae Models
Provectus IT Press Release - March 9, 2021

Machine Learning for Supernova Turbulence
Society for Industrial and Applied Mathematics (SIAM) News (CSE21) - March 4, 2021

License

Sapsan has a BSD-style license, as found in the LICENSE file.

© (or copyright) 2019. Triad National Security, LLC. All rights reserved. This program was produced under U.S. Government contract 89233218CNA000001 for Los Alamos National Laboratory (LANL), which is operated by Triad National Security, LLC for the U.S. Department of Energy/National Nuclear Security Administration. All rights in the program are reserved by Triad National Security, LLC, and the U.S. Department of Energy/National Nuclear Security Administration. The Government is granted for itself and others acting on its behalf a nonexclusive, paid-up, irrevocable worldwide license in this material to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so.