‘Quantum Friction’ Slows Water Flow Through Carbon Nanotubes, Resolving Long-Standing Fluid Dynamics Mystery

Simons Foundation, February 2022

For 15 years, scientists have been baffled by the mysterious way water flows through the tiny passages of carbon nanotubes — pipes with walls that can be just one atom thick. The streams have confounded all theories of fluid dynamics; paradoxically, fluid passes more easily through narrower nanotubes, and in all nanotubes it moves with almost no friction. What friction there is has also defied explanation.

Introducing the Simons Foundation Presidential Lectures

Simons Foundation, January 2022

Beginning this year, the Simons Foundation invites mathematicians, scientists and science lovers in the New York City area to its relaunched weekly lecture series, the Simons Foundation Presidential Lectures. These curated, high-level lectures are free to attend, and feature leading scientists and mathematicians discussing their work at the frontiers of research. The lectures aim to foster discourse and drive discovery among the local research community.

SueYeon Chung and Alex Williams Join CCN as Project Leaders

Simons Foundation, January 2022

The Flatiron Institute is delighted to announce that SueYeon Chung and Alex Williams will join the Center for Computational Neuroscience (CCN) as associate research scientists and project leaders. In addition, they will have joint appointments as assistant professors with the NYU Center for Neural Science (CNS), further fostering between those pursuing theoretical work at the CCN and researchers at nearby institutions.

The Largest Suite of Cosmic Simulations for AI Training Is Now Free to Download; Already Spurring Discoveries

Simons Foundation, January 2022

Totaling 4,233 universe simulations, millions of galaxies and 350 terabytes of data, a new release from the CAMELS project is a treasure trove for cosmologists. CAMELS — which stands for Cosmology and Astrophysics with MachinE Learning Simulations — aims to use those simulations to train artificial intelligence models to decipher the universe’s properties.