Sept. 11, 2020
The world's largest digital camera can spot a golf ball from 15 miles away.
When the Vera C. Rubin Observatory, formerly named the LSST, begins observations in 2023, its SUV-size camera will be able to capture complete panoramas of the southern sky every few nights. And that requires a new type of camera never seen before.
The imaging sensors for the world's largest digital camera have captured the first-ever 3,200-megapixel images by teams at the Department of Energy's SLAC National Accelerator Laboratory and Lawrence Livermore. Once this array of sensors is installed in the camera at SLAC and delivered to the Rubin Observatory in Chile, it will contribute to the observatory's 10-year Legacy Survey of Space and Time.
This survey will serve as a catalog of billions of galaxies and astrophysical objects, essentially creating "the largest astronomical movie of all time" and unlock the mysteries of the universe.
The assembly of the sensors in the camera's focal plane was completed in January, and the first images were used to test it.
"The focal plane will produce the images for the LSST, so it's the capable and sensitive eye of the Rubin Observatory," said Vincent Riot, LSST camera project manager and Lawrence Livermore engineer.
The atomic nucleus is the small, dense region consisting of protons and neutrons at the center of an atom. Protons and neutrons are bound together to form a nucleus by the nuclear force. But precisely what keeps them bound within the nucleus and even where they are within the nucleus remains a puzzle for nuclear scientists.
In an effort to figure out the answers, scientists at Lawrence Livermore National Laboratory and collaborators leveraged data to determine how nucleons (neutrons and protons) arrange themselves in the nucleus.
They found that for several cornerstone nuclei, a tiny fraction of the protons and neutrons possess most of the overall energy that keeps them bound in nuclei, generally 50 percent more than expected from standard theoretical treatments.
The study also made new predictions for the “neutron skin” — a region where extra neutrons pile up — of several neutron-rich nuclei. These predictions are firmly associated with how enormous neutron stars grow and what elements are likely synthesized in neutron star mergers.
Given the growing number of end-use applications for shape-memory materials, it is hardly surprising that a number of researchers have developed their own polymer-based alternatives.
A research team from Lawrence Livermore National Laboratory has used Direct Ink Writing 3D printing to create silicone structures that can recover from compression. The silicone could have future applications in ‘wearable protective padding’ capable of being activated under certain temperature conditions.
Lawrence Livermore has implemented its direct ink writing technique in a number of other recent projects. This includes its latest breakthrough into 3D-printed glass and a modified approach to create aerospace-grade carbon fiber composites.
With approximately 14 million new cases of cancer and close to 10 million deaths every year, it is difficult to say that the battle against cancer is close to being won. Experts consider that, once cancer spreads, or metastasizes, from one place in the body to another, the chances of survival decrease to 10 percent, making this the deadliest feature of the disease.
Up until now, advances in the management of systemic metastasis have been scarce, but scientists from the Lawrence Livermore National Laboratory developed a unique approach that they believe will help clinicians and researchers anticipate the spread of cancer within individual patients.
By pairing 3D bioprinting technology and advanced computational flow simulations, a team of experts believes they have laid the foundation for developing a predictive capability to understand tumor cell attachment to blood vessels, the first step in secondary tumor formation during cancer metastasis.
The new approach trains computational models on biological processes and provides insights into how and why cancer cells metastasize in certain areas of the vasculature. Using a custom-built extrusion-based bioprinter, Lab researchers 3D printed living human brain vasculature and paired it with advanced computational simulations to address the physics involved in cancer spreading via metastasis.
The company driving wafer-scale computing for artificial intelligence (AI) and machine learning applications, Cerebras, has announced a number of system wins in the last 12 months. At Lawrence Livermore, the Cerebras CS-1 machine was recently integrated into the National Nuclear Security Administration’s Lassen supercomputer, the unclassified companion system to Sierra.
Powered by the world’s largest computer chip, the CS-1/Lassen union creates a new type of cluster. The work that Livermore is doing on Lassen is predominantly a combination of high performance computing plus AI, where they integrate simulation training and inference for physics material science, optimization of fusion applications and drug development.
Livermore scientists are terming this new style of computing “cognitive simulation.”
“While Moore’s Law is not yet dead, we can see that it’s slowing down. The historic cadence of hardware improvements has slowed or even ceased, but the demand for computing has not,” said Chief Technology Officer for Livermore Computing Bronis de Supinski, who led the CS-1 procurement effort. “We need new answers for how to improve our ability to meet our mission requirements and to respond to ever-increasing computational requirements. Cognitive simulation is an approach that we believe could drive continued exponential capability improvements, and a system-level heterogeneous approach based on novel architectures such as the Cerebras CS-1 are an important part of achieving those improvements.”