November 2016   |   Particle Physics

HEPCloud formation

To handle troves of high-energy physics data, Fermilab researchers and others are turning to high-performance computing labs, academic grids and the commercial cloud.

Special Report
November 2016

Machine-learning curve

An Oak Ridge-led pilot project is devising automated computational tools to collect key data from medical records and deliver the right cancer treatment at the right time.

October 2016

Digital rock physics

High-performance computing informs predictions on subsurface carbon dioxide, water resources systems and oil and gas production.

Special Report
October 2016

Cancer’s search engine

The Department of Energy collaborates with the National Cancer Institute to apply supercomputing number-crunching power to cancer research.

Science Highlights

June 2016

Predicting turbulence in fusion plasmas

Data from experiments and advanced codes combine with supercomputing muscle to help explain a half-century-old mystery.

Developing practical fusion energy has been impeded for decades by high heat loss from magnetically confined plasmas. Researchers from MIT, University of California at San Diego and General Atomics captured the dynamics of plasma turbulence linked to heat loss on unprecedented scales. Pictured here is the inside of the Alcator C-Mod tokamak, the inset depicting plasma turbulence simulations that show long wavelength blobs coexisting with short wavelength streamers – small, finger-like structures that comprise the turbulence in the core of the experimental plasmas.

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