Like art, there's something about science that loves play. It's the fun, as in fundamentals, that makes practical benefits possible.
The history of science is rife with stories of serendipitous discoveries, but finding the first antiproton is not one of them. When a Berkeley Lab team announced the observation of the antiproton 50 years ago, it was the culmination of a decades-long theoretical and experimental quest that included building the world's most powerful accelerator the Bevatron tailor-made to do the job.
Gluons glue quarks together to make protons, neutrons, and other particles, but they can also stick to themselves in short-lived glueballs. So says the Standard Model of Fundamental Particles and Fields. Trouble is, no one has ever seen a glueball. New theoretical developments suggest that at least some glueballs leave tell-tale tracks that may soon become visible in powerful electron-positron colliders.
Depictions of a single water molecule, one oxygen atom and two hydrogen atoms, resemble a big round face with two round ears. But for years a scientific controversy has raged over just how these Mickey Mouse shapes relate to one another in liquid water. A leading researcher combines years of theoretical and experimental work to point to the definitive answer.
Opening a debate on how best to discover the nature of the mysterious dark energy that accelerates the expansion of the universe the first installment of a new series featuring the world's leading experts on Type Ia supernovae, the brightest standard candles in the sky
The Parallel Processor
Advances in automatic sequencing created a dilemma when scientists at DOE's Joint Genome Institute found themselves overrun with data. The National Energy Research Scientific Computing Center (NERSC) came to the rescue with strategies for improving the reliability of data storage while making retrieval easier.
IBM's BlueGene/L takes the lead as the world's fastest computer, while vector supercomputers like Japan's Earth Simulator and the Cray X1 push the limits of scientific computing. So what are the best architectures for large-scale scientific applications? Berkeley Lab scientists evaluate high-performance computers to make "real world" assessments of leading supercomputers around the world.