Whither quantum advantage? New classical lower bounds for Max-Cut on large-girth 3-regular graphs
quant-ph, cond-mat.dis-nn, math.CO
Submitted: 2026-10-12
Updated: 2026-10-12
Comments: 5 pages, 3 figures, 1 table
Code: https://github.com/shivangrawat/viral-tree-maxcut
License: http://creativecommons.org/licenses/by/4.0/
The gist: Every 3-regular graph of girth at least g has a cut containing at least a fraction M g of its edges, and the best rigorous bounds at large girth are 0.912 g to infinityM g 0.92386.
Abstract
Every 3-regular graph of girth at least g has a cut containing at least a fraction M g of its edges, and the best rigorous bounds at large girth are 0.912 g to infinityM g 0.92386. Lower bounds on M g follow from the performance of local algorithms: on a graph of girth g 2p+2 a depth- p local algorithm sees the same tree around every edge, so its expected cut fraction on that tree bounds M g from below. We apply this strategy to the Variational Iterative Rotation Algorithm (VIRAL), a classical local algorithm, and evaluate it on the depth- p tree for every even depth up to p=32. The resulting bounds exceed those recently obtained from the Quantum Approximate Optimization Algorithm (QAOA) for every p 4, by 0.005 to 0.011, and they extend the range of girths covered from g=36 to g=66. Notably, at g=66 we obtain M 66 0.9127 at 99.99999% confidence level, which raises the asymptotic lower bound from 0.912 to 0.9127.
Sources
- Lower bounding the MaxCut of high girth 3-regular graphs using the QAOA
- RSB bounds on the maximum cut
- An explicit vector algorithm for high-girth MaxCut
- A Quantum Approximate Optimization Algorithm
- The Quantum Approximate Optimization Algorithm at High Depth for MaxCut on Large-Girth Regular Graphs and the Sherrington-Kirkpatrick Model
- Classical and Quantum Bounded Depth Approximation Algorithms
- Classical algorithms and quantum limitations for maximum cut on high-girth graphs
- Variational Iterative Rotation Algorithm: Combinatorial Optimization with Classical Kicked Tops
- Absence of quantum advantage for approximate spin glass optimization
- Provable Classical and Quantum Local Algorithms for Max- k-Cut and Quantum Advantage at Moderate Girth
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