LDR | | 00000nam u2200205 4500 |
001 | | 000000433757 |
005 | | 20200226102726 |
008 | | 200131s2019 ||||||||||||||||| ||eng d |
020 | |
▼a 9781392428795 |
035 | |
▼a (MiAaPQ)AAI22588517 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 004 |
100 | 1 |
▼a Liu, Jingcheng. |
245 | 10 |
▼a Approximate Counting, Phase Transitions and Geometry of Polynomials. |
260 | |
▼a [S.l.]:
▼b University of California, Berkeley.,
▼c 2019. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
300 | |
▼a 117 p. |
500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-06, Section: B. |
500 | |
▼a Advisor: Sinclair, Alistair. |
502 | 1 |
▼a Thesis (Ph.D.)--University of California, Berkeley, 2019. |
506 | |
▼a This item must not be sold to any third party vendors. |
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▼a In classical statistical physics, a phase transition is understood by studying the geometry (the zero-set) of an associated polynomial (the partition function). In this thesis, we will show that one can exploit this notion of phase transitions algorithmically, and conversely exploit the analysis of algorithms to understand phase transitions. As applications, we give efficient deterministic approximation algorithms (FPTAS) for counting $q$-colorings, and for computing the partition function of the Ising model. |
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▼a School code: 0028. |
650 | 4 |
▼a Computer science. |
690 | |
▼a 0984 |
710 | 20 |
▼a University of California, Berkeley.
▼b Electrical Engineering & Computer Sciences. |
773 | 0 |
▼t Dissertations Abstracts International
▼g 81-06B. |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0028 |
791 | |
▼a Ph.D. |
792 | |
▼a 2019 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15493097
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 202002
▼f 2020 |
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▼a ***1008102 |
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▼a E-BOOK |