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Data Management Platform Strengthens Wildland Fire Science
As we face the threat of more frequent and more severe wildfires under climate change, Berkeley Lab researchers are building a managed data platform to help scientists better understand and predict wildland fire hazards, risks, and behaviors. Read More »
Innovation Transforms Quantum Processing of Image-Based Scientific Data
The Quantum Pixel Representation Framework created by Berkeley Lab scientists offers a more efficient way to apply quantum computing to large and complex scientific image analysis problems. Read More »
Breakthrough in Quantum Universal Gate Sets: A High-Fidelity iToffoli Gate
Researchers at Berkeley Lab demonstrated the first 3-qubit high-fidelity iToffoli native gate in a superconducting quantum information processor and in a single step. This demonstration adds a novel easy-to-implement native three-qubit logic gate for universal quantum computing. Read More »
Computer Models Show Role of Climate Change in Intense 2020 Hurricane Season
A computer modeling study of the historic 2020 North Atlantic hurricane season found that human-induced climate change played a major role. Read More »
New Encoder-Decoder Overcomes Limitations in Scientific Machine Learning
Thanks to recent improvements in machine and deep learning, computer vision has contributed to the advancement of everything from self-driving cars and traffic flow analysis to cancer detection and medical imaging. Using deep learning semantic segmentation, a method that labels each pixel of an image, computers have surpassed humans in solving classic image classification, detection, and segmentation problems. Despite many advancements, there is an increasing need for powerful, user-friendly… Read More »
San Francisco and Berkeley Lab Team Up on Pioneering Climate Study
Berkeley Lab computational resources are helping the City and County of San Francisco adapt to the Bay Area's changing climate and the extreme storms it is expected to bring. Read More »
Osni Marques Takes on New Role with Exascale Computing Project
Osni Marques, a staff scientist in the Applied Math and Computational Research Division, has been tapped to lead the Training & Productivity effort within the Exascale Computing Project. Read More »
Computational Analysis Enables Breakthrough in Biomolecular Dynamics
A new study with data analyses from Berkeley Lab computational researchers helps broaden the physical understanding of biomolecular assembly. Read More »
CCSE’s Hannah Klion Selected for 2022 Rising Stars
Hannah Klion, a postdoctoral researcher in the Center for Computational Sciences and Engineering, has been selected to be part of this year's Rising Stars conference. Read More »
Lindsay Bassman Awarded Prestigious Marie Curie Fellowship
AMCR’s Lindsay Bassman has been awarded one of Europe’s most competitive and prestigious postdoctoral fellowships — the Marie Skłodowska-Curie Actions — to continue her work in quantum thermodynamics. Read More »
Advancing New Battery Design with Deep Learning
A team of researchers from Berkeley Lab and UC Irvine has developed deep-learning algorithms designed to automate the quality control and assessment of new battery designs for electric cars. Read More »
Michael Mahoney Tapped to Lead the Machine Learning and Analytics Group
Berkeley Lab’s Scientific Data Division recently appointed Michael Mahoney to lead its Machine Learning and Analytics Group.
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Berkeley Lab Computing Resources Enable Deeper Understanding of Supernovae Explosions
An international research team recently made history by recording the earliest post-explosion detection of a Type Ia supernova, using cosmological models developed at Berkeley Lab and supercomputing resources at NERSC. Read More »
HYPPO: Leveraging Prediction Uncertainty to Optimize Deep Learning Models for Science
With a growing need for optimization tools that can enhance deep learning models and their training to improve predictive capabilities and accelerate time-consuming computer simulations, a Berkeley Lab team developed HYPPO, an open-source software tool for hyperparameter optimization of deep neural networks. Read More »
Open Sourced Control Hardware for Quantum Computers
To make engineering quantum hardware more accessible, the Advance Quantum Testbed has open-sourced a new electronics control and measurement system for superconducting quantum processors. Read More »
Cutting Through the Noise
Berkeley Lab’s AMCR and Physics divisions joined forces to create a new approach to quantum error mitigation - "noise estimation circuits" - that could help make quantum computing’s theoretical potential a reality. Read More »
AMCRD’s Sherry Li Part of Team Honored by SIAM for Best Paper
AMCRD's Sherry Li is co-author on a paper being honored with the 2022 SIAM Activity Group on Supercomputing Best Paper Prize. Read More »
SIMCoV Models Cell-by-Cell Spread of Respiratory Infections
Berkeley Lab computational research scientist Steve Hofmeyr is part of a team that developed SimCoV, which can provide a 3D simulation of a portion of the lung and model the ways in which COVID-19 and other viral infections spread in the lungs. Read More »
Berkeley Lab’s FasTensor Provides Pain-Free Big Data Analysis
With FasTensor, researchers in Berkeley Lab’s Scientific Data Management Group developed an open source tool to help its users efficiently process and analyze their massive datasets. Read More »
