25 citations · 25 across the 6 of their papers we have counts for
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Circuit Synthesis for Variational Quantum Algorithms: The Depth of Algebra and Geometry
Boris Tsvelikhovskiy
The analysis of Hamiltonian Variational Ansätze centers on three fundamental questions: which states are exactly reachable from a given initial state, what native control depth suf…
The Expressive Power of Constrained QAOA: What You Might Have MISsed
Boris Tsvelikhovskiy, Bao Bach, Ilya Safro
Feasibility-preserving mixer Hamiltonians offer an attractive alternative to penalty encodings for constrained quantum optimization, yet how enforcing constraints alters the state…
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…
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…
Provable avoidance of barren plateaus for the Quantum Approximate Optimization Algorithm with Grover mixers
Boris Tsvelikhovskiy, Matthew Nuyten, Bojko N. Bakalov
We analyze the dynamical Lie algebras (DLAs) associated with the Grover-mixer variant of the Quantum Approximate Optimization Algorithm (GM-QAOA). When the initial state is the uni…
Equivariant QAOA and the Duel of the Mixers
Boris Tsvelikhovskiy, Ilya Safro, Yuri Alexeev
Constructing an optimal mixer for Quantum Approximate Optimization Algorithm (QAOA) Hamiltonian is crucial for enhancing the performance of QAOA in solving combinatorial optimizati…
Symmetries and Dimension Reduction in Quantum Approximate Optimization Algorithm
Boris Tsvelikhovskiy, Ilya Safro, Yuri Alexeev
In this paper, the Quantum Approximate Optimization Algorithm (QAOA) is analyzed by leveraging symmetries inherent in problem Hamiltonians. We focus on the generalized formulation…