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A leading expert in quantum computing, Bert de Jong discusses why quantum computing matters, where it is today, and the potential of this emerging technology to change science.
Neural networks can be difficult to train and employ on large-scale science problems. That's why Berkeley Lab researchers are devising new training methods tailored to scientific machine learning.
The ECP-funded WarpX Project has spent the last six years creating a novel, highly parallel, and highly optimized single-source simulation code for modeling plasma-based particle colliders on cutting-edge exascale supercomputers.
A collaboration involving scientists and computing resources from Berkeley Lab will publicly release its most accurate earthquake simulations to date.
Berkeley Lab scientists used several machine learning techniques in a pipeline to segment and identify cryo-ET cell membrane structures.
The latest developments in computational oncology are giving medical researchers a glimpse into a future where they’ll be able to understand tumor progression via supercomputers and advanced mathematical algorithms.
Berkeley Lab's Advanced Quantum Testbed team demonstrates a three-qubit native quantum gate with high fidelity
This year, Lawrence Berkeley National Laboratory (Berkeley Lab) is celebrating yet another milestone: the 20th anniversary of the Luis W. Alvarez Fellowship in Computing Sciences.
The Sustainable Research Pathways (SRP) program has been connecting students from underrepresented communities and institutions to scientists and staff at Berkeley Lab for nearly a decade to facilitate research collaborations and bolster workforce development and diversity, equity, and inclusion.
Recently, Berkeley Lab researchers developed a continuum FHD model that efficiently harnesses the power of cutting-edge exascale supercomputers to simulate the transport phenomenai n fluid mixtures.
For World Quantum Day on April 14, Berkeley Lab’s Computing Sciences Area celebrated the interdisciplinary collaboration between the Advanced Quantum Testbed (AQT) at Berkeley Lab and the California-based contemporary visual artist Benjamin Arizmendi.
A leading expert in quantum computing, Bert de Jong discusses why quantum computing matters, where it is today, and the potential of this emerging technology to change science.
The International Symposium on Quality Electronic Design (ISQED’23) recognized researchers in Lawrence Berkeley National Laboratory’s (Berkeley Lab’s) Computer Architecture Group with a Best Paper Award for “An Area Efficient Superconducting Unary CNN Accelerator.”
SciData transforms data-driven discovery and understanding through the development and application of novel data science methods, technologies, and infrastructures with scientific partners.
The Applied Mathematics & Computational Research Division conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture, and high-performance software implementation.
The Center for Advanced Mathematics for Energy Research Applications (CAMERA) is an integrated, cross-disciplinary center aimed at inventing, developing, and delivering the fundamental new mathematics required to capitalize on experimental investigations at scientific facilities.
The Quantum Systems Accelerator is catalyzing national leadership in quantum information science to co-design the algorithms, quantum devices, and engineering solutions needed to deliver certified quantum advantage in Department of Energy scientific applications. Berkeley Lab leads the center. Sandia National Laboratories is the lead partner.
