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Quantum Speedup for Some Geometric 3SUM-Hard Problems and Beyond (2404.04535v1)

Published 6 Apr 2024 in cs.CG and cs.DS

Abstract: The classical 3SUM conjecture states that the class of 3SUM-hard problems does not admit a truly subquadratic $O(n{2-\delta})$-time algorithm, where $\delta >0$, in classical computing. The geometric 3SUM-hard problems have widely been studied in computational geometry and recently, these problems have been examined under the quantum computing model. For example, Ambainis and Larka [TQC'20] designed a quantum algorithm that can solve many geometric 3SUM-hard problems in $O(n{1+o(1)})$-time, whereas Buhrman [ITCS'22] investigated lower bounds under quantum 3SUM conjecture that claims there does not exist any sublinear $O(n{1-\delta})$-time quantum algorithm for the 3SUM problem. The main idea of Ambainis and Larka is to formulate a 3SUM-hard problem as a search problem, where one needs to find a point with a certain property over a set of regions determined by a line arrangement in the plane. The quantum speed-up then comes from the application of the well-known quantum search technique called Grover search over all regions. This paper further generalizes the technique of Ambainis and Larka for some 3SUM-hard problems when a solution may not necessarily correspond to a single point or the search regions do not immediately correspond to the subdivision determined by a line arrangement. Given a set of $n$ points and a positive number $q$, we design $O(n{1+o(1)})$-time quantum algorithms to determine whether there exists a triangle among these points with an area at most $q$ or a unit disk that contains at least $q$ points. We also give an $O(n{1+o(1)})$-time quantum algorithm to determine whether a given set of intervals can be translated so that it becomes contained in another set of given intervals and discuss further generalizations.

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References (20)
  1. A. Ambainis and N. Larka. Quantum algorithms for computational geometry problems, 2020.
  2. B. Aronov and S. Har-Peled. On approximating the depth and related problems. SIAM J. Comput., 38(3):899–921, 2008.
  3. G. Barequet and S. Har-Peled. Polygon containment and translational min-Hausdorff-distance between segment sets are 3sum-hard. Int. J. Comput. Geom. Appl., 11(4):465–474, 2001.
  4. Quantum amplitude amplification and estimation. Contemporary Mathematics, 305:53–74, 2002.
  5. Limits of quantum speed-ups for computational geometry and other problems: Fine-grained complexity via quantum walks. In Proc. of the 13th Innovations in Theoretical Computer Science Conference (ITCS), volume 215 of LIPIcs, pages 31:1–31:12. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022.
  6. The power of geometric duality. BIT Numerical Mathematics, 25(1):76–90, 1985.
  7. K. L. Clarkson. New applications of random sampling in computational geometry. Discret. Comput. Geom., 2:195–222, 1987.
  8. H. Edelsbrunner and L. J. Guibas. Topologically sweeping an arrangement. J. Comput. Syst. Sci., 38(1):165–194, 1989.
  9. Graphics in flatland: A case study. In Computational Geometry: Theory and Applications, volume 1. 1983.
  10. D. Eppstein. Graph-theoretic solutions to computational geometry problems. In C. Paul and M. Habib, editors, Proceedings of the 35th International Workshop on Graph-Theoretic Concepts in Computer Science (WG), pages 1–16, 2009.
  11. Finding a maximum clique in a disk graph. In E. W. Chambers and J. Gudmundsson, editors, Proceedings of the 39th International Symposium on Computational Geometry (SoCG), volume 258 of LIPIcs, pages 30:1–30:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023.
  12. A. Gajentaan and M. H. Overmars. On a class of o(n2)superscript𝑛2(n^{2})( italic_n start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT ) problems in computational geometry. Computational geometry, 5(3):165–185, 1995.
  13. A. Gajentaan and M. H. Overmars. On a class of o⁢(n2)𝑜superscript𝑛2o(n^{2})italic_o ( italic_n start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT ) problems in computational geometry. Comput. Geom., 45(4):140–152, 2012.
  14. L. K. Grover. A fast quantum mechanical algorithm for database search. In Proceedings of the twenty-eighth annual ACM symposium on Theory of computing, pages 212–219, 1996.
  15. L. K. Grover. A framework for fast quantum mechanical algorithms. In Proceedings of the 13th Annual ACM Symposium on the Theory of Computing (STOC), pages 53–62. ACM, 1998.
  16. D. Halperin and M. Sharir. Arrangements. In Handbook of discrete and computational geometry, pages 723–762. Chapman and Hall/CRC, 2017.
  17. D. Haussler and E. Welzl. Epsilon-nets and simplex range queries. In Proceedings of the Second Annual ACM SIGACT/SIGGRAPH Symposium on Computational Geometry, pages 61–71. ACM, 1986.
  18. Computational geometry algorithms and applications. Spinger, 2008.
  19. E. Ruci. Cutting a Polygon with a Line. PhD thesis, Carleton University, 2008.
  20. H. Wang. A simple algorithm for computing the zone of a line in an arrangement of lines. In Symposium on Simplicity in Algorithms (SOSA), pages 79–86. SIAM, 2022.
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Authors (3)
  1. J. Mark Keil (12 papers)
  2. Fraser McLeod (1 paper)
  3. Debajyoti Mondal (45 papers)
Citations (1)

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