Bringing Together Diverse Skill Sets
Our assembled and integrated research team builds on incredible expertise at LBNL, Harvard, ANL and UC Berkeley, spanning novel algorithm development for quantum chemistry applications, the computer science areas of software infrastructure, compiler development and graph-based schedule and layout optimization, and the applied mathematics areas of stochastic optimization and linear algebra. The team is focused on design and deliver novel algorithms, compiling techniques, and scheduling tools for chemical sciences that make optimal use of near-term quantum hardware with limited coherence times, and utilizing new mathematical approaches to achieve a near-optimal time-to-solution.
Miroslav Urbaneck (LBNL)
Bill Huggins (UC Berkeley)
Bryan O'Gorman (UC Berkeley)
Algorithm and Circuit Optimization
Marin Bukov (UC Berkeley)
In the area of compiler and scheduling optimization we are establishing a partnership with the NASA Quantum Artificial Intelligence Laboratory (QuAIL) team. Our team will work closely with ASCR Quantum Computing Testbeds, especially with the LBNL Advanced Quantum-Enabled Simulation team (AQuES). In the commercial space, the team is collaborating with the Google Quantum AI Lab, Rigetti, Bleximo, the Monroe trapped ion effort and the Quantum Nanoelectronics Laboratory (QNL) at UC Berkeley to test our algorithmic advancements and to integrate developed software tools.