LLL and stochastic sandpile models
April 07, 2018 Β· Declared Dead Β· π IACR Cryptology ePrint Archive
"No code URL or promise found in abstract"
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Authors
Jintai Ding, Seungki Kim, Tsuyoshi Takagi, Yuntao Wang
arXiv ID
1804.03285
Category
math.NT
Cross-listed
cond-mat.stat-mech,
cs.CR
Citations
2
Venue
IACR Cryptology ePrint Archive
Last Checked
4 months ago
Abstract
Theaimofthepresentpaperistosuggestthatstatisticalphysicsprovides the correct language to understand the practical behavior of the LLL algorithm, most of which are left unexplained to this day. To this end, we propose sandpile models that imitate LLL with compelling accuracy, and prove for these models some of the most desired statements regarding LLL. We also formulate a few conjectures that formally capture our heuristics and would serve as milestones for further development of the theory.
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