Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 39 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 12 tok/s Pro
GPT-5 High 18 tok/s Pro
GPT-4o 91 tok/s Pro
Kimi K2 191 tok/s Pro
GPT OSS 120B 456 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

On the list decodability of rank-metric codes containing Gabidulin codes (2103.07547v1)

Published 12 Mar 2021 in cs.IT, math.CO, and math.IT

Abstract: Wachter-Zeh in [42], and later together with Raviv [31], proved that Gabidulin codes cannot be efficiently list decoded for any radius $\tau$, providing that $\tau$ is large enough. Also, they proved that there are infinitely many choices of the parameters for which Gabidulin codes cannot be efficiently list decoded at all. Subsequently, in [41] these results have been extended to the family of generalized Gabidulin codes and to further family of MRD-codes. In this paper, we provide bounds on the list size of rank-metric codes containing generalized Gabidulin codes in order to determine whether or not a polynomial-time list decoding algorithm exists. We detect several families of rank-metric codes containing a generalized Gabidulin code as subcode which cannot be efficiently list decoded for any radius large enough and families of rank-metric codes which cannot be efficiently list decoded. These results suggest that rank-metric codes which are $\mathbb{F}_{qm}$-linear or that contains a (power of) generalized Gabidulin code cannot be efficiently list decoded for large values of the radius.

Citations (1)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.