# Topological Analysis of Bitcoin's Lightning Network

arXiv: https://arxiv.org/abs/1901.04972 · HTML: https://mlsanity.com/paper/1901.04972/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jan 2019.

## Built on by (most cited first, 5 of 5)

- [Channel Balance Interpolation in the Lightning Network via Machine Learning](https://mlsanity.com/paper/2405.12087/) (2024)
- [DyFEn: Agent-Based Fee Setting in Payment Channel Networks](https://mlsanity.com/paper/2210.08197/) (2022)
- [Benchmarking GNNs Using Lightning Network Data](https://mlsanity.com/paper/2407.07916/) (2024)
- [Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning](https://mlsanity.com/paper/2411.17353/) (2024)
- [Predicting Channel Closures in the Lightning Network with Machine Learning](https://mlsanity.com/paper/2605.12759/) (2026)

## Abstract (arXiv)

Bitcoin's Lightning Network (LN) is a scalability solution for Bitcoin allowing transactions to be issued with negligible fees and settled instantly at scale. In order to use LN, funds need to be locked in payment channels on the Bitcoin blockchain (Layer-1) for subsequent use in LN (Layer-2). LN is comprised of many payment channels forming a payment channel network. LN's promise is that relatively few payment channels already enable anyone to efficiently, securely and privately route payments across the whole network. In this paper, we quantify the structural properties of LN and argue that LN's current topological properties can be ameliorated in order to improve the security of LN, enabling it to reach its true potential.