On the Lattice Smoothing Parameter Problem
  The smoothing parameter $\eta_{\epsilon}(\mathcal{L})$ of a Euclidean lattice $\mathcal{L}$, introduced by Micciancio and Regev (FOCS'04; SICOMP'07), is (informally) the smallest amount of Gaussian noise that "smooths out" the discrete structure of $\mathcal{L}$ (up to error $\epsilon$). It plays a central role in the best known worst-case/average-case reductions for lattice problems, a wealth of lattice-based cryptographic constructions, and (implicitly) the tightest known transference theorems for fundamental lattice quantities.   In this work we initiate a study of the complexity of approximating the smoothing parameter to within a factor $\gamma$, denoted $\gamma$-${\rm GapSPP}$. We show that (for $\epsilon = 1/{\rm poly}(n)$): $(2+o(1))$-${\rm GapSPP} \in {\rm AM}$, via a Gaussian analogue of the classic Goldreich-Goldwasser protocol (STOC'98); $(1+o(1))$-${\rm GapSPP} \in {\rm coAM}$, via a careful application of the Goldwasser-Sipser (STOC'86) set size lower bound protocol to thin spherical shells; $(2+o(1))$-${\rm GapSPP} \in {\rm SZK} \subseteq {\rm AM} \cap {\rm coAM}$ (where ${\rm SZK}$ is the class of problems having statistical zero-knowledge proofs), by constructing a suitable instance-dependent commitment scheme (for a slightly worse $o(1)$-term); $(1+o(1))$-${\rm GapSPP}$ can be solved in deterministic $2^{O(n)} {\rm polylog}(1/\epsilon)$ time and $2^{O(n)}$ space.   As an application, we demonstrate a tighter worst-case to average-case reduction for basing cryptography on the worst-case hardness of the ${\rm GapSPP}$ problem, with $\tilde{O}(\sqrt{n})$ smaller approximation factor than the ${\rm GapSVP}$ problem.   Central to our results are two novel, and nearly tight, characterizations of the magnitude of discrete Gaussian sums. 
Kai-Min Chung, Daniel Dadush, Feng-Hao Liu, Chris Peikert
cs.CC