Quadratic exact-size and linear approximate-size random generation of planar graphs

This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Eric Fusy [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2005

Schlagwörter:	planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc]

Übergeordnetes Werk:	In: Discrete Mathematics & Theoretical Computer Science - Discrete Mathematics & Theoretical Computer Science, 2004, (2005), Proceedings
Übergeordnetes Werk:	year:2005 ; number:Proceedings

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.46298/dmtcs.3362

Katalog-ID:	DOAJ028957709

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520			\|a This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$.
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matchkey_str	article:13658050:2005----::udaieatienlnaapoiaeieadmeea
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publishDate	2005
allfields	10.46298/dmtcs.3362 doi (DE-627)DOAJ028957709 (DE-599)DOAJ7fdcffec73b146ec98bb1273e4209197 DE-627 ger DE-627 rakwb eng QA1-939 Eric Fusy verfasserin aut Quadratic exact-size and linear approximate-size random generation of planar graphs 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$. planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] Mathematics In Discrete Mathematics & Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science, 2004 (2005), Proceedings (DE-627)239019105 (DE-600)1412155-4 13658050 nnns year:2005 number:Proceedings https://doi.org/10.46298/dmtcs.3362 kostenfrei https://doaj.org/article/7fdcffec73b146ec98bb1273e4209197 kostenfrei https://dmtcs.episciences.org/3362/pdf kostenfrei https://doaj.org/toc/1365-8050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2005 Proceedings
spelling	10.46298/dmtcs.3362 doi (DE-627)DOAJ028957709 (DE-599)DOAJ7fdcffec73b146ec98bb1273e4209197 DE-627 ger DE-627 rakwb eng QA1-939 Eric Fusy verfasserin aut Quadratic exact-size and linear approximate-size random generation of planar graphs 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$. planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] Mathematics In Discrete Mathematics & Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science, 2004 (2005), Proceedings (DE-627)239019105 (DE-600)1412155-4 13658050 nnns year:2005 number:Proceedings https://doi.org/10.46298/dmtcs.3362 kostenfrei https://doaj.org/article/7fdcffec73b146ec98bb1273e4209197 kostenfrei https://dmtcs.episciences.org/3362/pdf kostenfrei https://doaj.org/toc/1365-8050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2005 Proceedings
allfields_unstemmed	10.46298/dmtcs.3362 doi (DE-627)DOAJ028957709 (DE-599)DOAJ7fdcffec73b146ec98bb1273e4209197 DE-627 ger DE-627 rakwb eng QA1-939 Eric Fusy verfasserin aut Quadratic exact-size and linear approximate-size random generation of planar graphs 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$. planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] Mathematics In Discrete Mathematics & Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science, 2004 (2005), Proceedings (DE-627)239019105 (DE-600)1412155-4 13658050 nnns year:2005 number:Proceedings https://doi.org/10.46298/dmtcs.3362 kostenfrei https://doaj.org/article/7fdcffec73b146ec98bb1273e4209197 kostenfrei https://dmtcs.episciences.org/3362/pdf kostenfrei https://doaj.org/toc/1365-8050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2005 Proceedings
allfieldsGer	10.46298/dmtcs.3362 doi (DE-627)DOAJ028957709 (DE-599)DOAJ7fdcffec73b146ec98bb1273e4209197 DE-627 ger DE-627 rakwb eng QA1-939 Eric Fusy verfasserin aut Quadratic exact-size and linear approximate-size random generation of planar graphs 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$. planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] Mathematics In Discrete Mathematics & Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science, 2004 (2005), Proceedings (DE-627)239019105 (DE-600)1412155-4 13658050 nnns year:2005 number:Proceedings https://doi.org/10.46298/dmtcs.3362 kostenfrei https://doaj.org/article/7fdcffec73b146ec98bb1273e4209197 kostenfrei https://dmtcs.episciences.org/3362/pdf kostenfrei https://doaj.org/toc/1365-8050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2005 Proceedings
allfieldsSound	10.46298/dmtcs.3362 doi (DE-627)DOAJ028957709 (DE-599)DOAJ7fdcffec73b146ec98bb1273e4209197 DE-627 ger DE-627 rakwb eng QA1-939 Eric Fusy verfasserin aut Quadratic exact-size and linear approximate-size random generation of planar graphs 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$. planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] Mathematics In Discrete Mathematics & Theoretical Computer Science Discrete Mathematics & Theoretical Computer Science, 2004 (2005), Proceedings (DE-627)239019105 (DE-600)1412155-4 13658050 nnns year:2005 number:Proceedings https://doi.org/10.46298/dmtcs.3362 kostenfrei https://doaj.org/article/7fdcffec73b146ec98bb1273e4209197 kostenfrei https://dmtcs.episciences.org/3362/pdf kostenfrei https://doaj.org/toc/1365-8050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2005 Proceedings
language	English
source	In Discrete Mathematics & Theoretical Computer Science (2005), Proceedings year:2005 number:Proceedings
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topic_facet	planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] Mathematics
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author	Eric Fusy
spellingShingle	Eric Fusy misc QA1-939 misc planar graphs misc boltzmann samplers misc rejection sampling misc [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] misc [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] misc [math.math-co] mathematics [math]/combinatorics [math.co] misc [info.info-cg] computer science [cs]/computational geometry [cs.cg] misc [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] misc Mathematics Quadratic exact-size and linear approximate-size random generation of planar graphs
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topic_title	QA1-939 Quadratic exact-size and linear approximate-size random generation of planar graphs planar graphs boltzmann samplers rejection sampling [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] [math.math-co] mathematics [math]/combinatorics [math.co] [info.info-cg] computer science [cs]/computational geometry [cs.cg] [info.info-hc] computer science [cs]/human-computer interaction [cs.hc]
topic	misc QA1-939 misc planar graphs misc boltzmann samplers misc rejection sampling misc [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] misc [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] misc [math.math-co] mathematics [math]/combinatorics [math.co] misc [info.info-cg] computer science [cs]/computational geometry [cs.cg] misc [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] misc Mathematics
topic_unstemmed	misc QA1-939 misc planar graphs misc boltzmann samplers misc rejection sampling misc [info.info-ds] computer science [cs]/data structures and algorithms [cs.ds] misc [info.info-dm] computer science [cs]/discrete mathematics [cs.dm] misc [math.math-co] mathematics [math]/combinatorics [math.co] misc [info.info-cg] computer science [cs]/computational geometry [cs.cg] misc [info.info-hc] computer science [cs]/human-computer interaction [cs.hc] misc Mathematics
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title	Quadratic exact-size and linear approximate-size random generation of planar graphs
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title_full	Quadratic exact-size and linear approximate-size random generation of planar graphs
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title_sort	quadratic exact-size and linear approximate-size random generation of planar graphs
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title_auth	Quadratic exact-size and linear approximate-size random generation of planar graphs
abstract	This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$.
abstractGer	This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$.
abstract_unstemmed	This extended abstract introduces a new algorithm for the random generation of labelled planar graphs. Its principles rely on Boltzmann samplers as recently developed by Duchon, Flajolet, Louchard, and Schaeffer. It combines the Boltzmann framework, a judicious use of rejection, a new combinatorial bijection found by Fusy, Poulalhon and Schaeffer, as well as a precise analytic description of the generating functions counting planar graphs, which was recently obtained by Giménez and Noy. This gives rise to an extremely efficient algorithm for the random generation of planar graphs. There is a preprocessing step of some fixed small cost. Then, for each generation, the time complexity is quadratic for exact-size uniform sampling and linear for approximate-size sampling. This greatly improves on the best previously known time complexity for exact-size uniform sampling of planar graphs with $n$ vertices, which was a little over $\mathcal{O}(n^7)$.
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container_issue	Proceedings
title_short	Quadratic exact-size and linear approximate-size random generation of planar graphs
url	https://doi.org/10.46298/dmtcs.3362 https://doaj.org/article/7fdcffec73b146ec98bb1273e4209197 https://dmtcs.episciences.org/3362/pdf https://doaj.org/toc/1365-8050
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doi_str	10.46298/dmtcs.3362
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up_date	2024-07-03T20:21:17.172Z
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