3D simulations find that the convective Urca process reduces mixing efficiency near the convective boundary in a simmering white dwarf but does not restrict the overall size of the convection zone, with the A=23 pair having the largest effect.
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GPU-accelerated iterative Poisson solvers for self-gravity are implemented and tested in Astaroth, achieving convergence and timing performance comparable to existing methods while supporting production-scale astrophysical runs.
3D simulations show the convective Urca process substantially reduces the convection zone size in a simmering white dwarf, though convection extends past the Urca shell.
The ECA-NM hybrid optimization produces chemical-diffusive models that reproduce major flame and detonation properties from detailed chemistry while cutting global error by four orders of magnitude and computational cost by two orders relative to genetic algorithms.
citing papers explorer
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Simulating the Convective Urca Process with Multiple Urca Pairs in a Simmering White Dwarf
3D simulations find that the convective Urca process reduces mixing efficiency near the convective boundary in a simmering white dwarf but does not restrict the overall size of the convection zone, with the A=23 pair having the largest effect.
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Iterative Poisson Solvers for Self-gravity with the GPU Code Astaroth
GPU-accelerated iterative Poisson solvers for self-gravity are implemented and tested in Astaroth, achieving convergence and timing performance comparable to existing methods while supporting production-scale astrophysical runs.
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On the Importance of the Convective Urca Process in 3D Simulations of a Simmering White Dwarf
3D simulations show the convective Urca process substantially reduces the convection zone size in a simmering white dwarf, though convection extends past the Urca shell.
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An efficient method based on the evolutionary center algorithm for optimizing chemical-diffusive models for flame acceleration and DDT
The ECA-NM hybrid optimization produces chemical-diffusive models that reproduce major flame and detonation properties from detailed chemistry while cutting global error by four orders of magnitude and computational cost by two orders relative to genetic algorithms.