---
license: cc-by-4.0
language:
  - en
pretty_name: Lightning Network Gossip Channel Closure Dataset
size_categories:
  - 100K<n<1M
tags:
  - lightning-network
  - bitcoin
  - temporal-graph
  - link-classification
configs:
  - config_name: default
    data_files:
      - split: full
        path: tgbl-ln_edgelist.csv
---

# Lightning Network Gossip — Channel Closure Dataset

Daily snapshots of the Lightning Network (LN) collected from gossip messages
between **2022-06-09** and **2024-10-14**. Used in the paper *Predicting
Channel Closures in the Lightning Network with Machine Learning* (Antonelli
et al., 2026; [arXiv:2605.12759](https://arxiv.org/abs/2605.12759)) and
consumed by the
[ln-channel-closure-prediction](https://github.com/AmbossTech/ln-channel-closure-prediction)
codebase.

## Schema (one row per gossip event)

| Column | Description |
|---|---|
| `chan_id` | Lightning channel identifier (`block:tx_idx:vout`). |
| `transaction_id`, `transaction_vout` | Funding transaction reference. |
| `last_update` | Last gossip update timestamp (ms). |
| `capacity` | Channel capacity (sat). |
| `src`, `dst` | Endpoint public keys (hex). |
| `src_*`, `dst_*` | Per-direction routing policy: time-lock delta, htlc bounds, fee base/rate, disabled flag, max-htlc, last-update timestamp. |
| `channel_status` | `OPEN` / `CLOSED`. |
| `closing_info` | `OPEN` / `MUTUAL` / `FORCED` / `LOCAL_CLOSED` / `PENALTY_CLOSED`. |
| `src_alias`, `dst_alias`, `src_implementation`, `dst_implementation` | Endpoint metadata. |
| `gossip_ts` | Event observation timestamp (ms). |
| `ts`, `height`, `block_avg_fee_rate` | On-chain funding metadata. |

## Statistics

- **Events:** 693 277.
- **Unique nodes:** 36 170.
- **Class distribution at prediction time** (over open edges):
  open ≈83 %, mutual ≈9 %, forced ≈8 %.

## Notes on the initial snapshot

The first day (2022-06-09) carries the entire pre-existing LN state as a
single batch of artificial "openings" — about 38 % of the rows. The
benchmark's `warm_start` mode initialises from these events without using
them for training/eval.

## License

Dataset is released under **CC-BY-4.0**. The underlying gossip messages are
public by design.

## Citation

```bibtex
@misc{antonelli2026predicting,
  title={Predicting Channel Closures in the Lightning Network with Machine Learning},
  author={Simone Antonelli and Vincent Davis and Harrison Rush and Anthony Potdevin and Jesse Shrader and Vikash Singh and Emanuele Rossi},
  year={2026},
  eprint={2605.12759},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://arxiv.org/abs/2605.12759}
}
```