Robust local testability of tensor products of LDPC codes

  • Authors:
  • Irit Dinur;Madhu Sudan;Avi Wigderson

  • Affiliations:
  • Hebrew University, Jerusalem, Israel;Massachusetts Institute of Technology, Cambridge, MA;Institute for Advanced Study, Princeton, NJ

  • Venue:
  • APPROX'06/RANDOM'06 Proceedings of the 9th international conference on Approximation Algorithms for Combinatorial Optimization Problems, and 10th international conference on Randomization and Computation
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Given two binary linear codes R and C, their tensor product R⊗C consists of all matrices with rows in R and columns in C. We analyze the “robustness” of the following test for this code (suggested by Ben-Sasson and Sudan [6]): Pick a random row (or column) and check if the received word is in R (or C). Robustness of the test implies that if a matrix M is far from R⊗C, then a significant fraction of the rows (or columns) of M are far from codewords of R (or C). We show that this test is robust, provided one of the codes is what we refer to as smooth. We show that expander codes and locally-testable codes are smooth. This complements recent examples of P. Valiant [13] and Coppersmith and Rudra [9] of codes whose tensor product is not robustly testable.