# Cyclic Group Projection for Enumerating Quasi-Cyclic Codes Trapping Sets

arXiv: https://arxiv.org/abs/2401.14810 · HTML: https://mlsanity.com/paper/2401.14810/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 21 references that are in the map.
- First posted on arXiv 26 Jan 2024.

## Builds on (most cited first, 4 of 4)

- [Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models](https://mlsanity.com/paper/1605.07252/) (2016)
- [Six Lectures on Linearized Neural Networks](https://mlsanity.com/paper/2308.13431/) (2023)
- [Perturb-and-max-product: Sampling and learning in discrete energy-based models](https://mlsanity.com/paper/2111.02458/) (2021)
- [Spherical and Hyperbolic Toric Topology-Based Codes On Graph Embedding for Ising MRF Models: Classical and Quantum Topology Machine Learning](https://mlsanity.com/paper/2307.15778/) (2023)

## Built on by (most cited first, 1 of 1)

- [Kohn-Sham Spectral Embedding on Sparse Graphs at the Nishimori Temperature for Image Classification](https://mlsanity.com/paper/2607.28428/) (2026)

## Abstract (arXiv)

This paper introduces a novel approach to enumerate and assess Trapping sets in quasi-cyclic codes, those with circulant sizes that are non-prime numbers. Leveraging the quasi-cyclic properties, the method employs a tabular technique to streamline the importance sampling step for estimating the pseudo-codeword weight of Trapping sets. The presented methodology draws on the mathematical framework established in the provided theorem, which elucidates the behavior of projection and lifting transformations on pseudo-codewords