LLL and stochastic sandpile models

April 07, 2018 Β· Declared Dead Β· πŸ› IACR Cryptology ePrint Archive

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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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