Quantum Science and Engineering at Cornell
Cornell’s Ithaca campus is home to a broad range of investigations into the quantum-mechanical nature of our world and universe, as well as the study of how to harness effects that are uniquely quantum mechanical for producing new technology in computing, communication, and sensing.
This website serves as a central source of information about who is working on quantum science and engineering at Cornell, what research areas we cover, and what quantum-related events are taking place.
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News and Breakthroughs
MOCVD system to drive exploration of next-gen nitride materials
A laboratory upgrade at Cornell will help forge new directions for nitride semiconductors – materials best known for enabling LEDs and 5G communications – by expanding the capabilities of nitrides to support technologies such as quantum computers and next generation radiofrequency and power devices.
The upgrade includes the installation of a custom-built, metal-organic chemical vapor deposition (MOCVD) system in Duffield Hall. The system works by injecting vapors of carefully designed chemicals, known as precursors, onto a heated substrate, where the materials react and form ultra-thin crystalline layers. This process, known as epitaxial growth, allows researchers to build semiconductor structures with atomic-level precision and performance.
MOCVD has been used to grow the traditional family of nitride semiconductors – gallium nitride, aluminum nitride and indium nitride – that revolutionized energy-efficient lighting and high-frequency electronics.
Programmable optical chip merges photons to change color
Cornell researchers have built a programmable optical chip that can change the color of light by merging photons, without requiring a new chip for new colors.
This form of nonlinear photonics could potentially be used for classical and quantum communications networks, all-optical signal processing and computation, spectroscopy and sensing.
“Previously, for each combination of colors you wanted to produce, you needed to fabricate a new device with a different design,” said Peter McMahon, associate professor of applied and engineering physics in Cornell Engineering, who led the project. “We now have a sort of universal device that lets you do any conversions you want, reprogrammably.”
The findings were published Oct. 8 in Nature. The paper’s first author is Ryotatsu Yanagimoto, a former postdoctoral researcher in the McMahon Lab and visiting scientist from NTT Research.
‘Bottling’ human intuition for AI-led materials discovery
Many properties of the world’s most advanced materials are beyond the reach of quantitative modeling. Understanding them also requires a human expert’s reasoning and intuition, which can’t be replicated by even the most powerful artificial intelligence, mixed with fortuitous accident, according to Eun-Ah Kim, the Hans A. Bethe Professor of physics in the College of Arts and Sciences and director of the Cornell-led National Science Foundation AI-Materials Institute.
Kim and collaborators have developed a machine-learning model that encapsulates and quantifies the valuable intuition of human experts in the quest to discover new quantum materials. The model, Materials Expert-Artificial Intelligence (ME-AI), “bottles” this intuition into descriptors that predict the functional property of a material. The team used the method to solve a quantum materials problem.
If you’re working on quantum research at Cornell and would like to contribute material to this website, please email quantum@cornell.edu.