Evaluating Parameter Transfer in FALQON Across Graph Families

Abstract

We evaluate FALQON parameter transfer for Max-Cut, transferring sequences from small donors ($n \in \{8,10,12\}$) to 14-node recipients. Using 3-regular and Erdős-Rényi families, we show that transfer success is dictated by the recipient graph, not the donor. Transfer excels for dense recipients -- achieving high approximation ratios regardless of the donor -- but remains challenging in sparse cross-family cases. Crucially, performance is highly resilient to donor size, with 8-node donors matching larger instances. Thus, cheap small graphs can provide robust parameters for larger targets, significantly reducing the measurement overhead of the feedback loop.