Analyzing the quantum approximate optimization algorithm: ans\"atze, symmetries, and Lie algebras
Sujay Kazi, Mart\'in Larocca, Marco Farinati, Patrick J. Coles, M. Cerezo, Robert Zeier

TL;DR
This paper investigates the algebraic structures of different QAOA ansätze for max-cut problems, revealing their symmetries, Lie algebras, and implications for barren plateaus and classical simulability.
Contribution
It fully characterizes the Lie algebras of multi-angle QAOA ansätze across connected graphs and introduces a symmetry framework for analyzing variational quantum algorithms.
Findings
Lie algebras of multi-angle ansatz fall into six families
Large Lie algebra dimensions imply susceptibility to barren plateaus
Symmetry analysis suggests potential classical simulability of QAOA
Abstract
The Quantum Approximate Optimization Algorithm (QAOA) has been proposed as a method to obtain approximate solutions for combinatorial optimization tasks. In this work, we study the underlying algebraic properties of three QAOA ans\"atze for the maximum-cut (maxcut) problem on connected graphs, while focusing on the generated Lie algebras as well as their invariant subspaces. Specifically, we analyze the standard QAOA ansatz as well as the orbit and the multi-angle ans\"atze. We are able to fully characterize the Lie algebras of the multi-angle ansatz across arbitrary connected graphs, finding that they only fall into one of just six families. Besides the cycle and the path graphs, the Lie dimensions for every graph are exponentially large in the system size, meaning that multi-angle ans\"atze are extremely prone to exhibiting barren plateaus. Then, a similar quasi-graph-independent…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture
