Research

Pitt faculty are working to solve some of the hardest quantum problems: Students work with Professor Kaushik Seshadreesan on designing new quantum communication protocols, and with Professor Nathan Youngblood on exploring optoelectronic materials. 

As part of Pitt Quantum strategic planning, a sub-committee was formed to discuss “Hard Problems” within STEM disciplines that could benefit from the impact of the Second Quantum Revolution. Faculty across DSAS, SCI and SSOE identified interesting, hard, and impactful problems, that would eventually be impacted by future quantum technologies. To see the original and full version transcript from that effort, titled Quantum Hard Problems Summary , please download the file here.   

Quantum Science and Engineering and, specifically, quantum information science is multi-disciplinary and Pitt leverages expertise across our schools ( DSAS,  SSoE, SCI ). We perform research in computing to design and control hardware that interacts with qubits, and develop error correction schemas (e.g., Michael Hatridge,  Sergey Frolov,  Jeremy Levy, Susan Fullerton , Alex Jones , Nathan Youngblood), communications to connect quantum devices and communicate quantum information over quantum networks (e.g., Kaushik Seshadressean), sensing, to lower detection limits and move into new sensing regimes (e.g., Thomas Purdy, Gurudev Dutt , Sunil Saxena, Sean Garrett-Roe, Heng Ban, David Waldeck , Kevin Chen , Stephen House,   James McKone ),  materials, to drive the discovery of physical and chemical phenomena and provide the basis for cutting-edge technologies (e.g., Jill Millstone , Jennifer Laaser, Xin Gui, Wes Transue,  David Snoke ), simulations to design solutions to problems that are not possible to solve on existing “classical” computers (e.g., Peyman Givi, David Pekker, Juan José Mendoza Arenas, Xulong Tang, Ken Jordan, John Keith, Sangyeop Lee), and philosophy and education to explore the Everett interpretation of quantum theory and reduce difficulties in learning physics (e.g., David Wallace, Chandralekha Singh).

The faculty identified key opportunities for current and future research.  In summary, that for Quantum computers to be successful in their quest to solve certain problems significantly faster than traditional classical computers, they will need to have enough qubits, quantum coherence, and error correction. While the popular press has been tracking the race to quantum computing in terms of the number of qubits, with Google, IBM, IonQ, and other companies demonstrating processors with over a hundred qubits, quantum coherence and error correction are essential to address too.  For high-precision quantum sensing hard problems include the creation of entangled states deployed to detect interesting phenomena. As an example, the use of entangled photon pairs in backscattering problems could produce transformative impacts on optical sensing.  Additionally, incorporating quantum effects in Atomic-scale microscopy may create entangled electron sources, or create advanced detectors that operate on quantum principles to improve the resolution of existing microscopies.    Quantum Biology was also discussed in this context and explores quantum coherent oscillations of electron spins in the radical pair reactions that underlie the magneto reception in migratory birds and butterflies. Simulations leveraging quantum computers can help us better understand the world, and can be used to better understand Chemistry and Materials Science.  Others that solve differential equations and non-equilibrium dynamics have broad application in engineering and computer science.   

Recent research awards: