6 citations · 10 across the 6 of their papers we have counts for
6 papers
Efficient Estimation of Reduced QAOA Expressibility on Acyclic Graphs
Bao Bach, Boris Tsvelikhovskiy, Jose Falla +1
Classically equivalent formulations of an optimization problem need not lead to equivalent quantum algorithms. For MaxCut, fixing the value of a single vertex removes a simple glob…
Constrained Counterdiabatic Quantum Approximate Optimization Algorithm for Portfolio Optimization
Jose Falla, Ilya Safro
We introduce a counterdiabatic (CD) extension of the Quantum Approximate Optimization Algorithm (QAOA) for constrained portfolio optimization. By incorporating approximate adiabati…
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…
MLQAOA: Graph Learning Accelerated Hybrid Quantum-Classical Multilevel QAOA
Bao Bach, Jose Falla, Ilya Safro
Learning the problem structure at multiple levels of coarseness to inform the decomposition-based hybrid quantum-classical combinatorial optimization solvers is a promising approac…
Graph Representation Learning for Parameter Transferability in Quantum Approximate Optimization Algorithm
Jose Falla, Quinn Langfitt, Yuri Alexeev +1
The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. O…
Similarity-Based Parameter Transferability in the Quantum Approximate Optimization Algorithm
Alexey Galda, Eesh Gupta, Jose Falla +4
The quantum approximate optimization algorithm (QAOA) is one of the most promising candidates for achieving quantum advantage through quantum-enhanced combinatorial optimization. A…