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Our goal is find a faster discrete Gaussian sampling to solve $"SVP"$ problem in lattice:

A lattice is discrete subgroup of $R^n$ such that define as below:

let $\{b_1,\cdots ,b_n\}$ be a basis in $R^n$. Then $L:=\{a_1b_1+\cdots+a_nb_n | a_i \in Z\}$ is a lattice.

Shortest vector problem in $L$ is:

$SVP(L)$ = shortest non-zero $y\in L$.

This is a $NP-hard$ problem to solve. The best algorithm to improve approximation of this problem mentioned by "Discrete Gaussian Sampling". In this method, the TIME and SPACE computed $2^{n+ o(n)}$. What is the faster discrete Gaussian sampling?

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