Max-Cut
A classic NP-hard combinatorial optimization problem in graph theory. The goal is to partition the vertices of a graph into two sets so that the sum of the weights of the edges crossing between the two sets is maximized.
Timeline (last 90 days)
The paper proves the speedup mainly for three classes of instances: formulas with many biased variables, semi-random 2-CNF formulas, and Max-Cut on regular expander graphs and stochastic block model graphs.
The paper applies the algorithm to the Max-Cut problem on graphs generated by regular expander graphs and stochastic block models, and likewise obtains an exponential speedup.
A Max-Cut instance on each graph can be naturally transformed into a Max 2-SAT instance, where each edge corresponds to a clause requiring the two endpoints to belong to different parts.
vq-logics-opt/bsb_solver.py implements ballistic simulated bifurcation (bSB), a classical algorithm inspired by quantum adiabatic evolution, which outperforms standard greedy heuristics on Max-Cut and QUBO problems.
All Facts (4)
The paper proves the speedup mainly for three classes of instances: formulas with many biased variables, semi-random 2-CNF formulas, and Max-Cut on regular expander graphs and stochastic block model graphs.
50%UnverifiedThe paper applies the algorithm to the Max-Cut problem on graphs generated by regular expander graphs and stochastic block models, and likewise obtains an exponential speedup.
50%UnverifiedA Max-Cut instance on each graph can be naturally transformed into a Max 2-SAT instance, where each edge corresponds to a clause requiring the two endpoints to belong to different parts.
50%Unverifiedvq-logics-opt/bsb_solver.py implements ballistic simulated bifurcation (bSB), a classical algorithm inspired by quantum adiabatic evolution, which outperforms standard greedy heuristics on Max-Cut and QUBO problems.
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