Timechain-level modeling and analysis of the bitcoin lightning network

The Lightning Network (LN) serves as a critical scaling solution for Bitcoin, enabling high-throughput, low-latency transactions through off-chain channels. Despite its potential, modeling the LN presents significant challenges due to its dynamic topology, decentralized nature, and the complexity of its interactions with the underlying blockchain. In this work, we propose a novel timechain-level approach to modeling the Lightning Network. The model explicitly accounts for base layer events, both in terms of timing and protocol behavior. To demonstrate the effectiveness of this approach, we propose an open-source implementation of the model and present a use case focused on pathfinding and routing failures. Our analysis highlights operational inefficiencies and bottlenecks that reduce transaction reliability and success rates in the LN. The findings emphasize the need for robust algorithms and strategies to improve network resilience, offering a pathway to enhance the scalability and functionality of the LN. This study contributes to the growing body of research aimed at optimizing off-chain payment networks and aligns with broader efforts to improve Bitcoin's scalability and usability.