Associate Professor Xu Yi at the University of Virginia is exploring the use of quantum optical technology to overcome challenges in quantum computing. Funded by a National Science Foundation Career Award, Yi is leveraging the properties of light, or photons, to increase scalability and maintain reliability in quantum computing. This could revolutionize fields like drug development, potentially reducing the time and cost of creating new pharmaceuticals.
Current quantum computing leaders like IBM, Rigetti, and Google (not all companies), use superconducting circuits for quantum information, but Yi’s approach could reduce errors and increase scalability. His work builds on photonic quantum computing developed by UVA physics professor Oliver Pfister.
Quantum Computing: The Promise and Challenges
Quantum computing, a technology still in its early stages, holds the potential to revolutionize various fields. However, it faces significant challenges in terms of scalability and error resilience. Scalability refers to the ability to handle larger tasks without slowing down, while resilience involves maintaining reliability even under adverse conditions. Associate Professor Xu Yi from the University of Virginia’s Charles L. Brown Department of Electrical and Computer Engineering has received a National Science Foundation Career Award to explore the use of quantum optical technology to address these issues.
Quantum Insights from a Nobel Laureate
Richard Feynman, a Caltech professor and 1965 Nobel Prize laureate in physics, emphasized the importance of quantum mechanics in simulating nature. He, along with many researchers including Xu Yi, believed that certain problems could not be solved without mastering quantum computing. Traditional computing, due to its relatively small computing capability, can only measure parts of a problem and make educated guesses about the rest. In contrast, quantum computing has the potential to analyze enormous data sets, such as the myriad possibilities of chemical interactions within a human body system, in a short time.
Applied Quantum Computing in Drug Development
One practical application of quantum computing is in drug development. Currently, it takes more than a decade to develop a new drug due to the complexity of predicting how drug molecules will behave and interact with atoms in the body. This interaction is quantum mechanical in nature. Once quantum computing is scaled up, it could potentially solve this problem using quantum mechanical simulations that encompass the whole problem, not just a part of it. This could lead to faster and more efficient drug development, possibly reducing research and development spending and increasing pharmaceutical availability, thereby impacting health equity.
Current State of Quantum Computing
Despite recent advancements like quantum-computing-friendly hardware and advanced algorithms, quantum computing is still considered emergent. Two major problems need to be solved: increasing scalability and maintaining stability at scale. Current quantum computing leaders like IBM and Google use superconducting circuits as processors to manipulate and store quantum information. However, the metal materials used for constructing these components are prone to errors in computations. Scaling quantum computing with semiconductor technology has been slow due to these challenges.
Leveraging the Power of Light in Quantum Computing
To address these issues, Xu Yi aims to leverage the properties of light, specifically photons, to reduce the number of physical components needed for quantum operations. His work uses optical components that can each support hundreds of thousands of wavelength messages, significantly reducing opportunities for error while offering a vehicle for scaling.
From Tabletop to Chip Scale: The Evolution of Photonic Quantum Computing
Photonic quantum computing, which was first developed at UVA by physics professor Oliver Pfister more than a decade ago, involves using different wave colors in quantum mechanics. Pfister has shown he can entangle up to 3,000 different photonic qubits together. However, entanglement is only the first step. With Yi’s help, Pfister’s 3,000-qubit prototype has the potential to surpass IBM’s top computational qubits number of 1,121. The challenge now is to reduce all the photonic mechanical equipment from a tabletop to the size of a chip, which would decrease the margin of error.
A Quantum Leap in Healthcare
Once Yi can prove the same entanglement capability at the chip scale that Pfister proved at the tabletop scale, he will start controlling the wavelengths for computations and then expand and scale. This could potentially pave the way for human chemistry and whole-system biological simulations, marking a significant leap in healthcare.
