It draws an analogy to natural phenomena and systems, such as amoeba maze solving and electricity's path of least resistance, to illustrate how a network might naturally resolve into an acyclic spanning tree. This comparison suggests an inherent design towards an "expensive" spanning tree where cheaper paths are gradually exhausted.

Further exploration is suggested through modifying simulations to better mimic real-world financial behaviors, particularly focusing on how nodes manage lightning funds. A hypothetical scenario is presented where a node's decision-making process regarding payment methods (lightning versus fiat) is influenced by its current balance of lightning funds. This model proposes thresholds that determine the proportion of payments made via lightning, aiming to avoid depleting lightning balances to maintain participation benefits in the network.

This discussion raises concerns about the strategic management of lightning funds within the network, emphasizing the importance of developing models that reflect realistic financial activities and decisions. By adjusting simulation parameters to account for varying balances and payment preferences, the aim is to achieve a more sustainable and strategically advantageous network operation, potentially enhancing the understanding and efficiency of payment channels in decentralized networks.