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We analyze asymptotic properties of collective-rearrangement algorithms being a class of dense packing algorithms. Traditionally, they transform finite systems of (possibly overlapping) particles into non-overlapping configurations by collective rearrangement of particles in finitely many steps. We consider the convergence of such algorithms for not necessarily finite input data, which means that the configuration of particles in any bounded sampling window remains unchanged after finitely many rearrangement steps. More precisely, we derive sufficient conditions implying the convergence of such algorithms when a stationary process of particles is used as input. We also provide numerical results and present an application in computational materials science.
Hirsch, Christian 1 ; Gaiselmann, Gerd 1 ; Schmidt, Volker 1
@article{PS_2015__19__236_0, author = {Hirsch, Christian and Gaiselmann, Gerd and Schmidt, Volker}, title = {Asymptotic {Properties} of {Collective-Rearrangement} {Algorithms}}, journal = {ESAIM: Probability and Statistics}, pages = {236--250}, publisher = {EDP-Sciences}, volume = {19}, year = {2015}, doi = {10.1051/ps/2014026}, mrnumber = {3394491}, zbl = {1348.60028}, language = {en}, url = {http://geodesic.mathdoc.fr/articles/10.1051/ps/2014026/} }
TY - JOUR AU - Hirsch, Christian AU - Gaiselmann, Gerd AU - Schmidt, Volker TI - Asymptotic Properties of Collective-Rearrangement Algorithms JO - ESAIM: Probability and Statistics PY - 2015 SP - 236 EP - 250 VL - 19 PB - EDP-Sciences UR - http://geodesic.mathdoc.fr/articles/10.1051/ps/2014026/ DO - 10.1051/ps/2014026 LA - en ID - PS_2015__19__236_0 ER -
%0 Journal Article %A Hirsch, Christian %A Gaiselmann, Gerd %A Schmidt, Volker %T Asymptotic Properties of Collective-Rearrangement Algorithms %J ESAIM: Probability and Statistics %D 2015 %P 236-250 %V 19 %I EDP-Sciences %U http://geodesic.mathdoc.fr/articles/10.1051/ps/2014026/ %R 10.1051/ps/2014026 %G en %F PS_2015__19__236_0
Hirsch, Christian; Gaiselmann, Gerd; Schmidt, Volker. Asymptotic Properties of Collective-Rearrangement Algorithms. ESAIM: Probability and Statistics, Tome 19 (2015), pp. 236-250. doi: 10.1051/ps/2014026
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