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
Title
Approximate counting, phase transitions and geometry of polynomials
Published
2019-08-01
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
EECS-2019-110
Type
Text
Extent
118 p
Archive
The Engineering Library
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