Proves μ_n{γ(L)>T} ≤ C T^{-1} for n≥3, implying γ(L_n)=2^{o(n)} whp under Haar-Siegel measure, using Rogers's second-moment method via dyadic self-normalization.
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Quantum rejection sampling yields a quadratically faster discrete Gaussian sampler on lattices, enabling two improved versions of quantum dual attacks with trade-offs in speed and memory.
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A Uniform Random-Lattice Tail Bound for the SVP Kissing-Profile Parameter
Proves μ_n{γ(L)>T} ≤ C T^{-1} for n≥3, implying γ(L_n)=2^{o(n)} whp under Haar-Siegel measure, using Rogers's second-moment method via dyadic self-normalization.
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Quantum algorithm for Discrete Gaussian Sampling
Quantum rejection sampling yields a quadratically faster discrete Gaussian sampler on lattices, enabling two improved versions of quantum dual attacks with trade-offs in speed and memory.