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SVP / Classical · ℓ∞ norm

Improved algorithms for the Shortest Vector Problem and the Closest Vector Problem in the infinity norm

Divesh Aggarwal · Priyanka Mukhopadhyay

ISAAC 2018

PublishedSource checked
Time bound
22.82 n + o(n)
Space bound
22.82 n + o(n)
Source / version date
15 May 2018
Comparison variant
Classical · ℓ∞ norm
Cost scale
2c n + o(n)
Norm
ℓ∞
Success guarantee
At least 1/2
Computation model
Classical; polynomial input-size factors suppressed

Assumptions and source notes

Exact ℓ∞-SVP using the birthday variant, with γ = 0.67 and ξ = 0.868. The coefficient was checked in v2; the row conservatively uses that version’s 15 May 2018 arXiv date rather than assuming it was already in v1 on 8 January. It is not a Euclidean-SVP coefficient.

Source location

Theorem 3.2 and its explicit parameter specialization, PDF p. 17
Version: arXiv:1801.02358v2, 15 May 2018

Selected earlier references

Selected sources cited by this paper.

  1. A sieve algorithm for the shortest lattice vector problem

    Miklós Ajtai · Ravi Kumar · Dandapani Sivakumar · 2001

    modifies randomized sieving for the infinity norm Abstract and §1.2.1; reference [4]

Primary source ↗

@inproceedings{aggarwal-mukhopadhyay-2018-infinity,
  author = {Divesh Aggarwal and Priyanka Mukhopadhyay},
  title = {{Improved algorithms for the Shortest Vector Problem and the Closest Vector Problem in the infinity norm}},
  booktitle = {29th International Symposium on Algorithms and Computation (ISAAC 2018)},
  year = {2018},
  url = {https://arxiv.org/abs/1801.02358},
  cr_date = {2018-01-08},
  cr_date_precision = {day},
  cr_status = {published},
  cr_venue = {ISAAC 2018},
  cr_author_ids = {divesh-aggarwal; priyanka-mukhopadhyay},
  note = {arXiv:1801.02358; checked version v2, 15 May 2018}
}