Their research will focus on brain-inspired (neuromorphic) computing systems comprised of quantum devices operating at cryogenic (below -450 °F) temperatures.
Satyavolu Papa Rao, associate VP for research and adjunct professor of nanoscience, and Nathaniel Cady, professor of nanobioscience, will use the funding.
They’ll conduct research and development of such neuromorphic computing systems that mimic the functioning elements of a human brain. Rao and Cady will conduct their research in SUNY Poly’s 300mm wafer-fabrication facility using the same tool platforms on which advanced computer chips are built, the school said.
This research can accelerate the development of “large scale, fab-friendly superconducting optoelectronic systems (harnessing both superconductivity and light) that could compute 30,000 times faster than the human brain, but at the same level of energy efficiency.”
About the research
The research team led by Papa Rao will work to address current “bottlenecks” in all-electronic implementations of neuromorphic computing by research and development of the “critical elements” of superconducting optoelectronics at the 300mm scale.
The brain-inspired infrastructure will use “ultra-fast, extremely energy efficient” Josephson junctions, which consist of two superconducting materials and a thin non-superconducting material in between. The Josephson junctions will need to be combined with silicon-based infrared photon (light) emitters, which generate light pulses that allow a given neuron to communicate with many downstream neurons.
This arrangement mimics how the human brain works by sending and receiving ultra-short electrical pulses that it uses to store and process information simultaneously, per the release.
Contact Reinhardt at ereinhardt@cnybj.com
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