9 papers
Warm-Starting MaxCut Relaxation via Low-Depth Quantum Approximate Optimization Algorithm
Bao G. Bach, Ilya Safro, Filip B. Maciejewski
Quantum optimization has attracted growing interest as quantum hardware continues to improve, yet state-of-the-art classical solvers remain a formidable benchmark for practical uti…
Efficient Compilation for Shuttling Trapped-Ion Machines via the Position Graph Architectural Abstraction
Bao Bach, Ilya Safro, Ed Younis
With the growth of quantum platforms for gate-based quantum computation, compilation holds a crucial role in deciding the success of the implementation. While there has been rich r…
Quantum Hypergraph Partitioning
Cameron Ibrahim, Bao G. Bach, Jad Salem +4
Quantum optimization algorithms are inherently probabilistic, yet they are most often used to search for a single high-quality solution. In this paper, we instead study hypergraph…
Scaling Qubit Mapping and Routing With Position Graph Abstraction and Memoization
Brent Russon, Bao Bach, Ed Younis +1
Scalable qubit mapping and routing remain major bottlenecks in quantum compilation, especially for Trapped-Ion Quantum Charge-Coupled device (TI-QCCD) architectures, where qubit in…
Reductions of QAOA Induced by Classical Symmetries: Theoretical Insights and Practical Implications
Boris Tsvelikhovskiy, Bao Bach, Jose Falla +1
The performance of the Quantum Approximate Optimization Algorithm (QAOA) is closely tied to the structure of the dynamical Lie algebra (DLA) generated by its Hamiltonians, which de…
Learning Cut Distributions with Quantum Optimization
Bao Bach, Cameron Ibrahim, Reuben Tate +3
Many combinatorial optimization problems admit a maximin fairness variant, where the aim is to find a distribution over possible solutions which maximizes an expected worst-case ou…