Quantum algorithm to solve function inversion with time–space trade-off

2017 ◽  
Vol 16 (7) ◽  
Author(s):  
WanQing Wu ◽  
HuanGuo Zhang
Keyword(s):  
Quantum Algorithm ◽  
Trade Off ◽  
Time Space

A Time-Space Trade-Off for Triangulations of Points in the Plane

2017 ◽  
pp. 3-12 ◽  
Author(s):  
Hee-Kap Ahn ◽  
Nicola Baraldo ◽  
Eunjin Oh ◽  
Francesco Silvestri
Keyword(s):  
Trade Off ◽  
Time Space

scholarly journals A time–space trade-off for computing the k-visibility region of a point in a polygon

2019 ◽  
Vol 789 ◽  
pp. 13-21 ◽  
Author(s):  
Yeganeh Bahoo ◽  
Bahareh Banyassady ◽  
Prosenjit K. Bose ◽  
Stephane Durocher ◽  
Wolfgang Mulzer
Keyword(s):  
Trade Off ◽  
Time Space

A Time-Space Trade-Off

1978 ◽  
Vol 25 (3) ◽  
pp. 509-515 ◽  
Author(s):  
Nicholas Pippenger
Keyword(s):  
Trade Off ◽  
Time Space

scholarly journals On Ajtai’s Lower Bound Technique for R-way Branching Programs and the Hamming Distance Problem

2000 ◽  
Vol 7 (11) ◽  
Author(s):  
Jakob Pagter
Keyword(s):  
Lower Bound ◽  
Hamming Distance ◽  
Linear Time ◽  
Program Model ◽  
Branching Programs ◽  
Original Proof ◽  
Trade Off ◽  
Time Space ◽  
Distance Problem ◽  
With Memory

In this report we study the proof employed by Miklos Ajtai<br />[Determinism versus Non-Determinism for Linear Time RAMs<br />with Memory Restrictions, 31st Symposium on Theory of <br />Computation (STOC), 1999] when proving a non-trivial lower bound<br />in a general model of computation for the Hamming Distance<br />problem: given n elements: decide whether any two of them have<br />"small" Hamming distance. Specifically, Ajtai was able to show<br />that any R-way branching program deciding this problem using<br />time O(n) must use space Omega(n lg n).<br />We generalize Ajtai's original proof allowing us to prove a<br />time-space trade-off for deciding the Hamming Distance problem<br /> in the R-way branching program model for time between n<br />and alpha n lg n / lg lg n, for some suitable 0 < alpha < 1. In particular we prove<br />that if space is O(n^(1−epsilon)), then time is Omega(n lg n / lg lg n).

A Time-Space Trade-off for the Shortest Path Tree in a Simple Polygon

2018 ◽  
Vol 29 (03) ◽  
pp. 391-402
Author(s):  
Pardis Kavand ◽  
Ali Mohades
Keyword(s):  
Shortest Path ◽  
Simple Polygon ◽  
Shortest Path Tree ◽  
Trade Off ◽  
Time Space

A [Formula: see text]-workspace algorithm may use a workspace of [Formula: see text] words which can be read and written, in addition to their input, which is provided as a read-only array of [Formula: see text] items. We present a [Formula: see text]-workspace algorithm for constructing the shortest path tree of a simple polygon [Formula: see text] with [Formula: see text] vertices, with respect to a given point inside the polygon in [Formula: see text] time, where [Formula: see text] is the time for computing the visibility polygon of a given point inside a simple polygon with [Formula: see text] additional words of space.

scholarly journals A New Balanced Subdivision of a Simple Polygon for Time-Space Trade-Off Algorithms

Algorithmica ◽  
2019 ◽  
Vol 81 (7) ◽  
pp. 2829-2856
Author(s):  
Eunjin Oh ◽  
Hee-Kap Ahn
Keyword(s):  
Simple Polygon ◽  
Trade Off ◽  
Time Space
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