苹果测试工程师的日常
https://mp.weixin.qq.com/s/IdSmmJI2npQeRORRHHAScQ 解决格上的近似最短向量问题(Approximate Shortest Vector Problems in Lattices, 简称Lattice Problems)以及与之等价的带错误学习问题(Learning with Errors,简称LWE)是经典的算法难题,……陈一镭的工作提出了一个全新的量子算法来解决LWE以及与之等价的格问题。这项工作仍在同行评议中。如果被验证为正确,将为这个悬而未决的问题给…
Note: Update on April 18: Step 9 of the algorithm contains a bug, which I don’t know how to fix. See Section 3.5.9 (Page 37) for details. I sincerely thank Hongxun Wu and (independently) Thomas Vidick for finding the bug today. Now the claim of showing a polynomial time quantum algorithm for solving LWE with polynomial modulus-noise ratios does not hold. I leave the rest of the paper as it is (added a clarification of an operation in Step 8) as a hope that ideas like Complex Gaussian and windowed QFT may find other applications in quantum computation, or tackle LWE in other ways.


反转了(
https://eprint.iacr.org/2024/555
 
 
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