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	<updated>2026-07-29T09:41:21Z</updated>
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	<entry>
		<id>https://en.formulasearchengine.com/w/index.php?title=P-stable_group&amp;diff=27800</id>
		<title>P-stable group</title>
		<link rel="alternate" type="text/html" href="https://en.formulasearchengine.com/w/index.php?title=P-stable_group&amp;diff=27800"/>
		<updated>2013-02-11T00:20:07Z</updated>

		<summary type="html">&lt;p&gt;71.67.103.134: /* Definitions */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;A &#039;&#039;&#039;kinetic smallest enclosing disk&#039;&#039;&#039; data structure is a [[kinetic data structure]] that maintains the [[Smallest circle problem|smallest enclosing disk]] of a set of moving points.&lt;br /&gt;
&lt;br /&gt;
== 2D ==&lt;br /&gt;
In 2 dimensions, the best known kinetic smallest enclosing disk data structure uses the farthest point delaunay triangulation of the point set to maintain the smallest enclosing disk.&amp;lt;ref name=&amp;quot;DEGS10&amp;quot; /&amp;gt; The farthest-point [[Delaunay triangulation]] is the [[Duality (projective geometry)|dual]] of the [[Voronoi diagram#Higher-order Voronoi diagrams|farthest-point Voronoi diagram]]. It is known that if the farthest-point delaunay triangulation of a point set contains an acute triangle, the [[circumcircle]] of this triangle is the smallest enclosing disk. Otherwise, the smallest enclosing disk has the diameter of the point set as its diameter. Thus, by maintaining the [[kinetic diameter]] of the point set, the farthest-point delaunay triangulation, and whether or not the farthest-point delaunay triangulation has an acute triangle, the smallest enclosing disk can be maintained.&lt;br /&gt;
This data structure is responsive and compact, but not local or efficient:&amp;lt;ref name=&amp;quot;DEGS10&amp;quot; /&amp;gt;&lt;br /&gt;
* &#039;&#039;&#039;[[Kinetic data structure#Performance|Responsiveness]]:&#039;&#039;&#039; This data structure requires &amp;lt;math&amp;gt;O(\log^2 n)&amp;lt;/math&amp;gt; time to process each certificate failure, and thus is responsive.&lt;br /&gt;
* &#039;&#039;&#039;[[Kinetic data structure#Performance|Locality]]:&#039;&#039;&#039; A point can be involved in &amp;lt;math&amp;gt;\Theta(n)&amp;lt;/math&amp;gt; certificates. Therefore, this data structure is not local.&lt;br /&gt;
* &#039;&#039;&#039;[[Kinetic data structure#Performance|Compactness]]:&#039;&#039;&#039; This data structure requires O(n) certificates total, and thus is compact.&lt;br /&gt;
* &#039;&#039;&#039;[[Kinetic data structure#Performance|Efficiency]]:&#039;&#039;&#039; This data structure has &amp;lt;math&amp;gt;O(n^{3+\epsilon})&amp;lt;/math&amp;gt; events total.(for all &amp;lt;math&amp;gt;\epsilon&amp;gt;0&amp;lt;/math&amp;gt; The best known lower bound on the number of changes to the smallest enclosing disk is &amp;lt;math&amp;gt;\Omega(n^2)&amp;lt;/math&amp;gt;. Thus the efficiency of this data structure, the ratio of total events to external events, is &amp;lt;math&amp;gt;O(n^{1+\epsilon})&amp;lt;/math&amp;gt;.&lt;br /&gt;
The existence of kinetic data structure that has &amp;lt;math&amp;gt;o(n^{3+\epsilon})&amp;lt;/math&amp;gt; events is an open problem.&amp;lt;ref name=&amp;quot;DEGS10&amp;quot; /&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Approximate 2D ==&lt;br /&gt;
The smallest enclosing disk of a set of n moving points can be [[Approximation_algorithm#Epsilon_terms|ε-approximated]] by a kinetic data structure that processes &amp;lt;math&amp;gt;O(1/\epsilon^{5/2})&amp;lt;/math&amp;gt; events and requires &amp;lt;math&amp;gt;O((n/\sqrt{\epsilon})\log n)&amp;lt;/math&amp;gt; time total.&amp;lt;ref name=&amp;quot;AH01&amp;quot; /&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Higher dimensions ==&lt;br /&gt;
In dimensions higher than 2, efficiently maintaining the smallest enclosing sphere of a set of moving points is an open problem.&amp;lt;ref name=&amp;quot;DEGS10&amp;quot; /&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
{{Reflist| refs=&lt;br /&gt;
&amp;lt;ref name =&amp;quot;DEGS10&amp;quot;&amp;gt;&lt;br /&gt;
Erik D. Demaine, Sarah Eisenstat, Leonidas J. Guibas, André Schulz, Kinetic Minimum Spanning Circle, 2010. [http://www.ams.sunysb.edu/~jsbm/fwcg10/papers/25.pdf]&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&amp;lt;ref name=&amp;quot;AH01&amp;quot;&amp;gt;&lt;br /&gt;
Pankaj K. Agarwal and Sariel Hal-Peled. Maintaining approximate extent measures of moving points. In SODA &#039;01: Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms, pages 148–157, Philadelphia, PA, USA, 2001. Society for Industrial and Applied Mathematics.&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
}}&lt;br /&gt;
&lt;br /&gt;
[[Category:Kinetic data structures]]&lt;br /&gt;
[[Category:Computational geometry]]&lt;/div&gt;</summary>
		<author><name>71.67.103.134</name></author>
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	<entry>
		<id>https://en.formulasearchengine.com/w/index.php?title=Mathematical_formulation_of_quantum_mechanics&amp;diff=220271</id>
		<title>Mathematical formulation of quantum mechanics</title>
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		<updated>2012-08-30T11:38:53Z</updated>

		<summary type="html">&lt;p&gt;71.67.113.0: /* The &amp;quot;new quantum theory&amp;quot; */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;br /&gt;
&lt;br /&gt;
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