Isaac Newton’s groundbreaking scientific productivity while isolated from
the spread of bubonic plague is legendary. University of California San
Diego physicists can now claim a stake in the annals of pandemic-driven
science.
A team of UC San Diego researchers and colleagues at Purdue University has
now simulated the foundation of new types of artificial intelligence
computing devices that mimic brain functions, an achievement that resulted
from the COVID-19 pandemic lockdown. By combining new supercomputing
materials with specialized oxides, the researchers successfully demonstrated
the backbone of networks of circuits and devices that mirror the
connectivity of neurons and synapses in biologically based neural networks.
The simulations are described in the Proceedings of the National Academy of
Sciences (PNAS).
As bandwidth demands on today’s computers and other devices reach their
technological limit, scientists are working towards a future in which new
materials can be orchestrated to mimic the speed and precision of
animal-like nervous systems. Neuromorphic computing based on quantum
materials, which display quantum-mechanics-based properties, allow
scientists the ability to move beyond the limits of traditional
semiconductor materials. This advanced versatility opens the door to new-age
devices that are far more flexible with lower energy demands than today’s
devices. Some of these efforts are being led by Department of Physics
Assistant Professor Alex Frañó and other researchers in UC San Diego’s
Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C), a
Department of Energy-supported Energy Frontier Research Center.
“In the past 50 years we’ve seen incredible technological achievements that
resulted in computers that were progressively smaller and faster—but even
these devices have limits for data storage and energy consumption,” said
Frañó, who served as one of the PNAS paper’s authors, along with former UC
San Diego chancellor, UC president and physicist Robert Dynes. “Neuromorphic
computing is inspired by the emergent processes of the millions of neurons,
axons and dendrites that are connected all over our body in an extremely
complex nervous system.”
As experimental physicists, Frañó and Dynes are typically busy in their
laboratories using state-of-the-art instruments to explore new materials.
But with the onset of the pandemic, Frañó and his colleagues were forced
into isolation with concerns about how they would keep their research moving
forward. They eventually came to the realization that they could advance
their science from the perspective of simulations of quantum materials.
“This is a pandemic paper,” said Frañó. “My co-authors and I decided to
study this issue from a more theoretical perspective so we sat down and
started having weekly (Zoom-based) meetings. Eventually the idea developed
and took off.”
The researchers’ innovation was based on joining two types of quantum
substances—superconducting materials based on copper oxide and metal
insulator transition materials that are based on nickel oxide. They created
basic “loop devices” that could be precisely controlled at the nano-scale
with helium and hydrogen, reflecting the way neurons and synapses are
connected. Adding more of these devices that link and exchange information
with each other, the simulations showed that eventually they would allow the
creation of an array of networked devices that display emergent properties
like an animal’s brain.
Like the brain, neuromorphic devices are being designed to enhance
connections that are more important than others, similar to the way synapses
weigh more important messages than others.
“It’s surprising that when you start to put in more loops, you start to see
behavior that you did not expect,” said Frañó. “From this paper we can
imagine doing this with six, 20 or a hundred of these devices—then it gets
exponentially rich from there. Ultimately the goal is to create a very large
and complex network of these devices that will have the ability to learn and
adapt.”
With eased pandemic restrictions, Frañó and his colleagues are back in the
laboratory, testing the theoretical simulations described in the PNAS paper
with real-world instruments.
Reference:
Goteti US, Zaluzhnyy IA, Ramanathan S, Dynes RC, Frano A. Low-temperature
emergent neuromorphic networks with correlated oxide devices. PNAS.
2021;118(35).
doi: 10.1073/pnas.2103934118