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Kenneth Merz, PhD, of Cleveland Clinic's Center for Computational Life Sciences, and a research team are testing quantum computing鈥檚 abilities in chemistry through integrating machine learning and quantum circuits. Chemistry is one of the areas where quantum computing shows the most potential because of the technology鈥檚 ability to predict an unlimited number of possible outcomes. To determine quantum computing's ability to perform complex chemical calculations, Dr. Merz and Hongni Jin, PhD, decided to test its ability to simulate proton affinity, a fundamental chemical process that is critical to life. Dr. Merz and Dr. Jin focused on using machine learning applications on quantum hardware. This is a critical advantage over other quantum research which relies on simulators to mimic a quantum computer鈥檚 abilities. In this study, published in the Journal of Chemical Theory and Computation, the team was able to demonstrate the capabilities of quantum machine learning by creating a

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The Dark Energy Spectroscopic Instrument used millions of galaxies and quasars to build the largest 3D map of our universe to date. Combining the DESI data with other experiments shows signs that the impact of dark energy may be weakening over time 鈥� and the standard model of how the universe works may need an update.

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A new data release from the Dark Energy Spectroscopic Instrument is now available for researchers to explore. The collection contains information on 18.7 million galaxies, quasars, and stars 鈥� the largest dataset of its kind ever shared.

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A workshop led by scientists at the Department of Energy鈥檚 Oak Ridge National Laboratory sketched a road map toward a longtime goal: development of autonomous, or self-driving, next-generation research laboratories.Scientists have dreamed for generations of high-tech laboratories operated via robotics at the push of a button.

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Using the Frontier supercomputer at the Department of Energy鈥檚 Oak Ridge National Laboratory, researchers have developed a new technique that predicts nuclear properties in record detail.

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Researchers have developed a new optical computing material from photon-avalanching nanoparticles. The breakthrough offers a path toward realizing smaller, faster components for next-generation computers.

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In real life, mutants can arise when their DNA changes to give them an advantage over the rest of the population. A team from the University of Michigan has used simulations on the Pittsburgh Supercomputing Center鈥檚 Neocortex system to find out why beneficial mutants rarely come to dominate real organisms.

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Electronics and Telecommunications Research Institute (ETRI) announced that it has developed an accelerator system-on-chip (SoC) named 鈥楰-AB21鈥�. The accelerator chip developed by the researchers measures 77mm x 67mm, and is fabricated through the 12-nanometer process.

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Los Alamos National Laboratory partners with OpenAI to advance national security

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With its Aurora exascale supercomputer, Argonne National Laboratory is providing researchers with a powerful tool to accelerate discoveries across many fields, including biology, chemistry and AI for science.

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As part of the Aurora Early Science Program, an Argonne team is using the lab鈥檚 new Aurora exascale supercomputer and AI tools to perform simulations of the universe that aim to shed light on dark matter and dark energy.

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Neuromorphic computing鈥攁 field that applies principles of neuroscience to computing systems to mimic the brain鈥檚 function and structure鈥攏eeds to scale up if it is to effectively compete with current computing methods. In a review published Jan. 22 in the journal Nature, 23 researchers, including two from the University of California San Diego, present a detailed roadmap of what needs to happen to reach that goal.

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Computer scientists at the University of California San Diego have developed a groundbreaking method for generating highly realistic computer-generated images of fluid dynamics, in elements such as smoke. This research, conducted by the UC San Diego Center for Visual Computing, was presented at the prestigious SIGGRAPH Asia 2024 conference, where it received a Best Paper Honorable Mention for its contributions to computer graphics and physics-based simulation.

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At the Department of Energy鈥檚 Office of Science, 2024 brought big accomplishments enabled by decades of work as well as advances that are establishing the foundations for future research. From Nobel Prizes to a new exascale computer, the DOE鈥檚 Office of Science is leading the way.

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A team of interns from the Pittsburgh Supercomputing Center has been selected to represent the U.S. next year at a student competition at the International Supercomputing Conference (ISC25) in Hamburg, Germany, in June 2025.

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As the year comes to a close, the U.S. Department of Energy鈥檚 Argonne National Laboratory reviews some of its most notable achievements of 2024.

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Nuclear scientists used a new theoretical approach to calculate a value essential for unraveling the three-dimensional motion of quarks within a proton. The researchers obtained a significantly more accurate picture of these internal building blocks鈥� transverse motion. The work will aid in calculations of 3D motion of quarks and gluons in future collider experiments.

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The universe just got a whole lot bigger 鈥� or at least in the world of computer simulations, that is.In early November, researchers at the Department of Energy鈥檚 Argonne National Laboratory used the fastest supercomputer on the planet to run the largest astrophysical simulation of the universe ever conducted.

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This year鈥檚 Association for Computing Machinery鈥檚 Gordon Bell Prize in supercomputing goes to researchers led by the University of Melbourne who used the Frontier supercomputer to conduct a quantum molecular dynamics simulation 1,000 times greater in size and speed than any previous simulation of its kind.The team also includes researchers from AMD, QDX, and the Department of Energy鈥檚 Oak Ridge National Laboratory.

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The 2024 Gordon Bell Prize for Climate Modelling has been awarded to a team of researchers led by the King Abdullah University of Science and Technology, or KAUST, Saudi Arabia, who used the Frontier supercomputer to develop an exascale climate emulator with radically enhanced resolution but without the computational expense and data storage requirements of state-of-the-art climate models.