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SVP / Heuristic · quantum · minimal sieve-list space

Search problems in cryptography: from fingerprinting to lattice sieving

Thijs Laarhoven

Technische Universiteit Eindhoven 2016

PublishedSource checked
Time bound
20.297454 n + o(n)
Space bound
(4/3)n/2+o(n)
Source / version date
16 Feb 2016
Cost scale
2c n + o(n)
Computation model
GaussSieve; bounded-memory filter parameters
Coherent classical access
RAM-like quantumly addressable classical memory
Quantum workspace
Quantum search workspace; see Section 14.1

Assumptions and source notes

GaussSieve alternative at unchanged list space.

Source location

Section 14.2.10, pp. 186–187
Version: TU/e thesis public catalogue date 16 February 2016

Selected earlier references

Selected sources cited by this paper.

  1. Finding shortest lattice vectors faster using quantum search

    Thijs Laarhoven · Michele Mosca · Joop van de Pol · 2015

    Extends the quantum-search complexity analysis. Chapter 14, introductory references [LMvdP15]

  2. New directions in nearest neighbor searching with applications to lattice sieving

    Anja Becker · Léo Ducas · Nicolas Gama · Thijs Laarhoven · 2016

    Quantum filtering builds on the classical locality-sensitive filters. Sections 13 and 14.2.10; reference [BDGL16]

Primary source ↗

@phdthesis{laarhoven-thesis-2016,
  author = {Thijs Laarhoven},
  title = {{Search problems in cryptography: from fingerprinting to lattice sieving}},
  school = {Technische Universiteit Eindhoven},
  year = {2016},
  url = {https://research.tue.nl/en/publications/search-problems-in-cryptography-from-fingerprinting-to-lattice-si/},
  keywords = {SVP, quantum sieving, nearest neighbors},
  cr_date = {2016-02-16},
  cr_status = {published},
  cr_venue = {Technische Universiteit Eindhoven},
  cr_author_ids = {thijs-laarhoven}
}