Data Science in the News

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Machine learning tool fills in the blanks for satellite light curves

Feb. 13, 2024 - 
When viewed from Earth, objects in space are seen at a specific brightness, called apparent magnitude. Over time, ground-based telescopes can track a specific object’s change in brightness. This time-dependent magnitude variation is known as an object’s light curve, and can allow astronomers to infer the object’s size, shape, material, location, and more. Monitoring the light curve of...

For better CT images, new deep learning tool helps fill in the blanks

Nov. 17, 2023 - 
At a hospital, an airport, or even an assembly line, computed tomography (CT) allows us to investigate the otherwise inaccessible interiors of objects without laying a finger on them. To perform CT, x-rays first shine through an object, interacting with the different materials and structures inside. Then, the x-rays emerge on the other side, casting a projection of their interactions onto a...

Lab partners with new Space Force Lab

Nov. 14, 2023 - 
LLNL subject matter experts have been selected by the U.S. Space Force to help stand up its newest Tools, Applications, and Processing (TAP) laboratory dedicated to advancing military space domain awareness (SDA). The Livermore team attended the October 26 kickoff in Colorado Springs of the SDA TAP lab’s Project Apollo technology accelerator, designed with an open framework to support and...

LLNL’s Kailkhura elevated to IEEE senior member

Nov. 8, 2023 - 
IEEE, the world’s largest technical professional organization, has elevated LLNL research staff member Bhavya Kailkhura to the grade of senior member within the organization. IEEE has more than 427,000 members in more than 190 countries, including engineers, scientists and allied professionals in the electrical and computer sciences, engineering and related disciplines. Just 10% of IEEE’s...

Explainable artificial intelligence can enhance scientific workflows

July 25, 2023 - 
As ML and AI tools become more widespread, a team of researchers in LLNL’s Computing and Physical and Life Sciences directorates are trying to provide a reasonable starting place for scientists who want to apply ML/AI, but don’t have the appropriate background. The team’s work grew out of a Laboratory Directed Research and Development project on feedstock materials optimization, which led to...

High-performance computing, AI and cognitive simulation helped LLNL conquer fusion ignition

June 21, 2023 - 
For hundreds of LLNL scientists on the design, experimental, and modeling and simulation teams behind inertial confinement fusion (ICF) experiments at the National Ignition Facility, the results of the now-famous Dec. 5, 2022, ignition shot didn’t come as a complete surprise. The “crystal ball” that gave them increased pre-shot confidence in a breakthrough involved a combination of detailed...

Consulting service infuses Lab projects with data science expertise

June 5, 2023 - 
A key advantage of LLNL’s culture of multidisciplinary teamwork is that domain scientists don’t need to be experts in everything. Physicists, chemists, biologists, materials engineers, climate scientists, computer scientists, and other researchers regularly work alongside specialists in other fields to tackle challenging problems. The rise of Big Data across the Lab has led to a demand for...

Patent applies machine learning to industrial control systems

May 8, 2023 - 
An industrial control system (ICS) is an automated network of devices that make up a complex industrial process. For example, a large-scale electrical grid may contain thousands of instruments, sensors, and controls that transfer and distribute power, along with computing systems that capture data transmitted across these devices. Monitoring the ICS network for new device connections, device...

Computing codes, simulations helped make ignition possible

April 6, 2023 - 
Harkening back to the genesis of LLNL’s inertial confinement fusion (ICF) program, codes have played an essential role in simulating the complex physical processes that take place in an ICF target and the facets of each experiment that must be nearly perfect. Many of these processes are too complicated, expensive, or even impossible to predict through experiments alone. With only a few...

Cognitive simulation supercharges scientific research

Jan. 10, 2023 - 
Computer modeling has been essential to scientific research for more than half a century—since the advent of computers sufficiently powerful to handle modeling’s computational load. Models simulate natural phenomena to aid scientists in understanding their underlying principles. Yet, while the most complex models running on supercomputers may contain millions of lines of code and generate...

Supercomputing’s critical role in the fusion ignition breakthrough

Dec. 21, 2022 - 
On December 5th, the research team at LLNL's National Ignition Facility (NIF) achieved a historic win in energy science: for the first time ever, more energy was produced by an artificial fusion reaction than was consumed—3.15 megajoules produced versus 2.05 megajoules in laser energy to cause the reaction. High-performance computing was key to this breakthrough (called ignition), and HPCwire...

National Ignition Facility achieves fusion ignition

Dec. 13, 2022 - 
The U.S. Department of Energy (DOE) and DOE’s National Nuclear Security Administration (NNSA) today announced the achievement of fusion ignition at LLNL—a major scientific breakthrough decades in the making that will pave the way for advancements in national defense and the future of clean power. On Dec. 5, a team at LLNL’s National Ignition Facility (NIF) conducted the first controlled...

LLNL researchers win HPCwire award for applying cognitive simulation to ICF

Nov. 17, 2022 - 
The high performance computing publication HPCwire announced LLNL as the winner of its Editor’s Choice award for Best Use of HPC in Energy for applying cognitive simulation (CogSim) methods to inertial confinement fusion (ICF) research. The award was presented at the largest supercomputing conference in the world: the 2022 International Conference for High Performance Computing, Networking...

Understanding the universe with applied statistics (VIDEO)

Nov. 17, 2022 - 
In a new video posted to the Lab’s YouTube channel, statistician Amanda Muyskens describes MuyGPs, her team’s innovative and computationally efficient Gaussian Process hyperparameter estimation method for large data. The method has been applied to space-based image classification and released for open-source use in the Python package MuyGPyS. MuyGPs will help astronomers and astrophysicists...

Scientific discovery for stockpile stewardship

Sept. 27, 2022 - 
Among the significant scientific discoveries that have helped ensure the reliability of the nation’s nuclear stockpile is the advancement of cognitive simulation. In cognitive simulation, researchers are developing AI/ML algorithms and software to retrain part of this model on the experimental data itself. The result is a model that “knows the best of both worlds,” says Brian Spears, a...

S&TR cover story: The ACES in our hand

Sept. 20, 2022 - 
Uranium enrichment is central to providing fuel to nuclear reactors, even those intended only for power generation. With minor modifications, however, this process can be altered to yield highly enriched uranium for use in nuclear weapons. The world’s need for nuclear fuel coexists with an ever-present danger—that a nonnuclear weapons nation-state possessing enrichment technology could...

Lab researchers win top award for machine learning-based approach to ICF experiments

Aug. 4, 2022 - 
The IEEE Nuclear and Plasma Sciences Society (NPSS) announced an LLNL team as the winner of its 2022 Transactions on Plasma Science Best Paper Award for their work applying machine learning to inertial confinement fusion (ICF) experiments. In the paper, lead author Kelli Humbird and co-authors propose a novel technique for calibrating ICF experiments by combining machine learning with...

Assured and robust…or bust

June 30, 2022 - 
The consequences of a machine learning (ML) error that presents irrelevant advertisements to a group of social media users may seem relatively minor. However, this opacity, combined with the fact that ML systems are nascent and imperfect, makes trusting their accuracy difficult in mission-critical situations, such as recognizing life-or-death risks to military personnel or advancing materials...

CASC team wins best paper at visualization symposium

May 25, 2022 - 
A research team from LLNL’s Center for Applied Scientific Computing won Best Paper at the 15th IEEE Pacific Visualization Symposium (PacificVis), which was held virtually on April 11–14. Computer scientists Harsh Bhatia, Peer-Timo Bremer, and Peter Lindstrom collaborated with University of Utah colleagues Duong Hoang, Nate Morrical, and Valerio Pascucci on “AMM: Adaptive Multilinear Meshes.”...

Winter hackathon meets WiDS datathon

March 9, 2022 - 
Sponsored by the DSI, LLNL’s winter hackathon took place on February 16–17. Hackathons are 24-hour events that encourage collaborative programming and creative problem solving. In addition to traditional hacking, the hackathon included a special datathon competition in anticipation of the Women in Data Science (WiDS) conference on March 7. Hackathon and datathon participants presented their...