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Never underestimate a droid: deep learning for turbulence

Never underestimate a droid: deep learning for turbulence

by Sanjana Curtis | Jan 2, 2020 | Daily Paper Summaries

Can we teach a machine to reproduce the physics of turbulence? An exploration of using deep learning to simulate magnetohydrodynamic turbulence!

Here be dragons: Mapping the Mass Gap

Here be dragons: Mapping the Mass Gap

by Sanjana Curtis | Dec 5, 2019 | Daily Paper Summaries

The ‘mass gap’ is a mass range bereft of any observed neutron stars or black holes. What can gravitational waves tell us about possible inhabitants of this terra incognita?

How to Glo up: Black Hole-Neutron Star Mergers

How to Glo up: Black Hole-Neutron Star Mergers

by Sanjana Curtis | Oct 22, 2019 | Daily Paper Summaries

What does the merger of a neutron star with a black hole look like? Here’s a systematic study of how neutron star properties affect the electromagnetic emission from the merger.

A new site for the s-process?

A new site for the s-process?

by Sanjana Curtis | Jul 10, 2019 | Daily Paper Summaries

We know everything there is to know about the s-process, right? RIGHT?!

Avoiding a (thermonuclear) supernova

by Sanjana Curtis | Apr 16, 2019 | Daily Paper Summaries

Discovery of a circumstellar nebula with a hot central star – product of a white dwarf merger?

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