This dataset accompanies the paper Fast Surgery for Quantum LDPC Codes (2025) and consolidates the simulation results from all three CSV files provided by the authors on Zenodo (record 17220908).
It provides empirical data used to benchmark the performance of lattice-surgery-based fault-tolerant operations for quantum LDPC codes under different noise configurations.
Dataset contents
Column
Type
Description
shots
int64
Number of Monte Carlo simulation shots performed
failures
int64
Number of failed logical operations during simulation
task_id
string
Unique identifier for the simulation task
core_seconds
float64
Total compute time used for the simulation
metadata
JSON
Configuration details of the simulation, including noise rate p, number of rounds, error sector, chosen decoder, and its hyperparameters (decoder_kwargs)
All three CSVs published by the authors have been merged and converted to a unified Parquet format. The structure preserves the full fidelity of the original data while enabling efficient querying and analysis using libraries like Polars, PyArrow, or DuckDB.
