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    Physicists Simulate Artificial Brain Networks With New Quantum Materials

    Similar to biology-based systems (left), complex emergent behaviors (which occur when individual components are integrated into a collaborative system) are also due to a neuromorphic network of quantum material-based devices. (Right). Credit: UCSD

    The pandemic blockage forces a new perspective on the design of futuristic AI-based computing devices.

    Isaac Newton’s groundbreaking scientific productivity, isolated from the epidemic of bubonic plague, is legendary. Physicists at the University of California, San Diego are now able to fund a pandemic-led science chronicle.

    A team of researchers at the University of California, San Diego and colleagues at Purdue University have simulated the basis of a new type of artificial intelligence computing device that mimics brain function. COVID-19 (New Coronavirus Infection) Blockade of pandemics. By combining new supercomputing materials with specialized oxides, researchers have succeeded in demonstrating the backbone of networks of circuits and devices that reflect the connectivity of neurons and synapses in biologically based neural networks. Did.

    For simulation, Minutes of the National Academy of Sciences (PNAS).

    As bandwidth demand for today’s computers and other devices reaches technical limits, scientists can adjust new materials to mimic the speed and accuracy of the animal-like nervous system for a future. It is working. Quantum material-based neuromorphic computing with properties based on quantum mechanics allows scientists to move beyond the limits of traditional semiconductor materials. This high degree of versatility opens the door to a new era of devices that are far more flexible and require less energy than today’s devices. Some of these efforts are with Alex Frañó, an assistant professor in the Faculty of Physics, and UC San Diego’s Quantum Materials (Q-MEEN-C) for energy-efficient neuromorphic computing, energy frontier research supported by the Energy Department. It is led by other researchers at the center.

    “In the last 50 years, we’ve seen amazing technological achievements that have led to smaller and faster computers, but even these devices have limited data storage and energy consumption,” says Frañó. .. PNAS The author of the treatise, former Prime Minister of the University of California, San Diego, President of the University of California, and physicist Robert Dyne’s. “Neuromorphic computing is inspired by the emergent processes of millions of neurons, axons, and dendrites that connect to our entire body in a highly complex nervous system.”

    As experimental physicists, Frañó and Dynes are usually busy in the laboratory exploring new materials using the latest equipment. However, with the outbreak of the pandemic, Flanho and his colleagues were forced to become isolated with concerns about how they would continue to advance their research. They finally realized that science could be advanced in terms of quantum material simulation.

    “This is a pandemic paper,” he said. Flanho. “My co-author and I decided to study this issue from a more theoretical point of view, so we sat down and started a weekly (zoom-based) meeting. Eventually, the idea evolved. And succeeded. “

    Researchers’ innovations were based on the combination of two types of quantum materials: copper oxide-based superconducting materials and nickel oxide-based metal-insulator transition materials. They created a basic “loop device” that could be precisely controlled on a nanoscale with helium and hydrogen, reflecting how neurons and synapses connect. With the addition of these devices that link and exchange information with each other, the simulation will ultimately allow the creation of an array of network devices that display emergent properties such as the animal’s brain. Shown.

    Like the brain, neuromorphic devices are designed to strengthen connections that are more important than other devices, just as synapses weight messages that are more important than other messages.

    “It’s amazing that when you start increasing the loops, you’ll see unexpected behavior,” says Frañó. “From this white paper, you can imagine doing this with 6, 20, or 100 of these devices, and from there you’ll be exponentially rich. The ultimate goal is to use these. It’s about creating a very large and complex network of devices that you can learn and adapt to. “

    Frañó and his colleagues returned to the lab as the pandemic restrictions were relaxed. PNAS Paper using real-world musical instruments.

    See: Uday S. Goteti, Ivan A. Zaluzhnyy, Shriram Ramanathan, Robert C. Dynes, Alex Frano, “Cold Emergency Neuromorphic Network with Correlated Oxide Devices,” August 25, 2021. Minutes of the National Academy of Sciences..
    DOI: 10.1073 / pnas.2103934118

    Authors of this treatise include Uday Goteti, Ivan Zaluzhnyy, Shriram Ramanathan, Robert Dynes, and Alex Frañó.

    This study was supported through Q-MEEN-C, which is funded by the Department of Basic Energy Sciences (DE-SC0019273), Department of Energy, US Department of Energy.

    Physicists Simulate Artificial Brain Networks With New Quantum Materials Source link Physicists Simulate Artificial Brain Networks With New Quantum Materials

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