Quantum Computing with Multi-Level Quantum Systems
Quantum processors with of order a few hundred qubits based on superconducting circuitry have demonstrated computing power on par with the most advanced classical supercomputers for certain problems. Currently, most quantum processors operate two-level quantum systems, or qubits. The computational power of these near-term devices can be further boosted by leveraging multi-level approaches to encode quantum information in the larger and more connected Hilbert space of d-level systems (or qudits). In my talk, I will describe our work to realize qudit-based quantum computing platforms built from superconducting circuits and our techniques for characterizing and maximizing their performance.
Noah Goss is a 5th year Physics Ph. D. student with the Quantum Nanoelectronics Laboratory and Advanced Quantum Testbed groups of Professor Irfan Siddiqi at the University of California, Berkeley and Lawrence Berkeley National Laboratory and a Kavli Energy NanoScience Institute graduate student fellow. Noah received his B.A. from Columbia University in 2019. Noah’s graduate research at Berkeley focuses broadly on the device physics of superconducting quantum computers, with a specific emphasis on qudits.
Reversible Nanocomposite by Programming Amorphous Polymer Conformation Under Nanoconfinement
Nanoconfinements are utilized to program how polymers entangle and disentangle as chain clusters to engineer pseudo bonds with tunable strength, multivalency, and directionality. When amorphous polymers are grafted to nanoparticles that are one magnitude larger in size than individual polymers, programming grafted chain conformations can “synthesize” high-performance nanocomposites with moduli of ≈25GPa and a circular lifecycle without forming and/or breaking chemical bonds. These nanocomposites dissipate external stresses by disentangling and stretching grafted polymers up to ≈98% of their contour length, analogous to that of folded proteins; use both polymers and nanoparticles for load bearing; and exhibit a non-linear dependence on composition throughout the microscopic, nanoscopic, and single-particle levels.
Tiffany Chen is a Chemistry PhD candidate in Ting Xu's group, working on synthesis and characterization of polymer grafted nanoparticles (PGNPs). She received her B.S. in Chemistry at UC San Diego in 2017 where she worked for Michael Sailor on surface modification of porous silicon nanomaterials for sensor application. Her research focuses on understanding the chain conformation of grafted polymers under nanoconfinement by using their mechanical properties as readout. Knowledge gain will lead to new design principles for functional composites with tunable properties.