Image Details

Choose export citation format:

diffhydro: Inverse Multiphysics Modeling and Embedded Machine Learning in Astrophysical Flows

  • Authors: Benjamin Horowitz, Zarija Lukić, Kentaro Nagamine, Yuri Oku

Benjamin Horowitz et al 2026 The Astrophysical Journal 1012 .

  • Provider: AAS Journals

Caption: Figure 14.

Various optimizations in 2563 boxes including nongravitational source terms, shown at selected times (code units) chosen to highlight the dominant stages of the dynamics. Top row (turbulence + cooling): midplane slice of the instantaneous, normalized radiative cooling rate in a run initialized with turbulent ICs and evolved with driven turbulence plus heating/cooling; cooling is initially diffuse but rapidly localizes into a filamentary network coincident with compressive structures. Middle and bottom rows (forced turbulence): volume rendering and projection of density from the driven-turbulence run, illustrating the growth of a high-contrast density web maintained by the interplay of stochastic forcing and thermal instability. Three-dimensional volume renderings and animations are available at doi:10.5281/zenodo.22731680 and https://github.com/bhorowitz/DiffHydro_public/.

Other Images in This Article

Show More

Copyright and Terms & Conditions

Additional terms of reuse