I study quantum algorithms for optimization and simulation, with a focus on their performance and computational complexity.
I work with USRA’s Research Institute for Advanced Computer Science and the Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center. I received my Ph.D. in computer science from Columbia University.
Research Interests
Quantum optimization
QAOA, the quantum alternating operator ansatz, and constrained combinatorial problems.
Algorithms & Complexity
Algorithm design and analysis, approximation guarantees, state preparation, and the prospects for quantum advantage.
Quantum simulation
Algorithms and circuit primitives for scientific computing and simulating physical systems, from quantum chemistry to high energy physics.
Selected publications
-
Quantum Approximation Complexity of Classical Optimization Problems
A framework for quantum approximation guarantees, with conditional separations between quantum and classical algorithms.
-
From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
The quantum alternating operator ansatz extends QAOA to a wider range of operators and constrained problems.
-
Challenges and Opportunities in Quantum Optimization
A field-wide review of quantum optimization, its building blocks, benchmarks, and open questions.
-
On the representation of Boolean and real functions as Hamiltonians for quantum computing
A toolkit for constructing Hamiltonians that represent Boolean and real-valued functions.
-
Quantum Approximate Optimization Algorithm for MaxCut: A Fermionic View
Analytical results for QAOA on MaxCut, including a fermionic treatment of ring graphs and parameter setting.
-
Improving Quantum Approximate Optimization by Noise-Directed Adaptive Remapping
An adaptive remapping strategy that uses knowledge of device noise to guide quantum optimization.
-
Quantum Approximate Optimization via Noise-Directed Adaptive Warm-Starting
A noise-aware warm-starting approach that uses hardware noise as a resource for quantum optimization.
-
Primitive Quantum Gates for Dihedral Gauge Theories
Efficient quantum circuits for the Fourier transform and group operations needed to simulate dihedral lattice gauge theories.
Background
I received my Ph.D. in computer science from Columbia University in 2018, working in theoretical computer science and quantum computing. My advisers were Joseph F. Traub, Alfred V. Aho, and Anargyros Papageorgiou. My dissertation, Quantum Algorithms for Scientific Computing and Approximate Optimization, is freely available on arXiv. I joined NASA QuAIL and USRA’s Research Institute for Advanced Computer Science (RIACS) in spring 2018.
Before my Ph.D., I received a master’s degree in computer science from Columbia, an honours degree in theoretical physics from the University of Melbourne, and a bachelor’s degree in engineering physics from the University of British Columbia. My honours thesis studied fault-tolerant quantum computation. I also worked in software and hardware engineering, specializing in embedded systems and performance optimization.
My broader interests include the mathematical foundations of quantum physics and computation, and the ways science and technology can improve people’s lives. I am a founding member of Q4Climate, an initiative exploring quantum computing and climate change.
Contact
New York, NY
We are often looking for research interns in quantum computing and related areas. See the Feynman Quantum Academy for application details.