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Aaron Dubrow is the science and technology writer for the Texas Advanced Computing Center. He previously was a public affairs specialist at the U.S. National Science Foundation, where he was responsible for communications and media relations for NSF's Computing and Information Science and Engineering (CISE) Directorate, as well as creating and implementing strategic communications plans in support of the agency's $1 billion computing research portfolio. Aaron has extensive experience writing and developing print, video, multimedia and social media content for scientific organizations and publications. He contributes regularly to the Huffington Post and Futurity and is a leading voice in explaining the value of high performance computing and modern data platforms for science, society and industry to lay audiences.

Surveying Deepest Space to Understand Dark Energy

Surveying Deepest Space to Understand Dark Energy

HETDEX is the first major experiment to search for dark energy. It uses the giant Hobby-Eberly Telescope at McDonald Observatory and a set of spectrographs to map the three-dimensional positions of one million galaxies.

Two decades ago, Saul Perlmutter, Brian Schmidt, and Adam Reiss shocked the world when they published research showing not only that the Universe was expanding, but that the expansion was occurring at an accelerating rate. The discovery came as a complete surprise even to the astronomers themselves, and netted them a Nobel Prize in 2011.

Improving Brain Imaging with Deep Learning

Improving Brain Imaging with Deep Learning

An image showing the side by side versions of electron microscope captures. Credit: Salk Institute

Textbook descriptions of brain cells make neurons look simple: a long spine-like central axon with branching dendrites. Taken individually, these might be easy to identify and map, but in an actual brain, they're more like a knotty pile of octopi, with hundreds of limbs intertwined. This makes understanding how they behave and interact a major challenge for neuroscientists.

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Rethinking Brain-Inspired Computing from the Atom Up

Rethinking Brain-Inspired Computing from the Atom Up

If you wanted to deliver a package across the street and avoid being hit by a car, you could program a powerful computer to do it, equipped with sensors and hardware capable of running multiple differential equations to track the movement and speed of each car. But a young child would be capable of doing the same task with little effort, says Alex Demkov, professor of physics at The University of Texas at Austin.

UT Austin Launches Institute to Harness the Data Revolution

UT Austin Launches Institute to Harness the Data Revolution

Research from UT Austin professors and TRIPODS members Alex Dimakis and Eric Price shows that it is possible to learn a deep generative model that dreams images of human faces (right panel), trained by observing only occluded images (left panel). The middle panel shows a previous approach for solving this problem, that fails. [Figure from: AmbientGAN: Generative models from lossy measurements, by A. Bora, E. Price and A.G. Dimakis, ICLR 2018.]

Advances in machine learning are announced every day, but efforts to fundamentally rethink the core algorithms of AI are rare.

Twisted Physics: Magic Angle Graphene Produces Switchable Superconductivity

Twisted Physics: Magic Angle Graphene Produces Switchable Superconductivity

When the two layers of bilayer graphene are twisted relative to each other by 1.1 degrees -- dubbed the "magic angle" -- electrons behave in a strange and extraordinary way. The effect was first theorized by UT Austin physics professor Allan MacDonald and postdoctoral researcher Rafi Bistritzer. Illustration credit: David Steadman/University of Texas at Austin.

Last year, scientists demonstrated that twisted bilayer graphene — a material made of two atom-thin sheets of carbon with a slight twist — can exhibit alternating superconducting and insulating regions. Now, a new study in the journal Nature by scientists from Spain, the U.S., China and Japan shows that superconductivity can be turned on or off with a small voltage change, increasing its usefulness for electronic devices.