Abstract
Counting problems aim to count the number of solutions for a given input, for example, counting the number of variable assignments that satisfy a Boolean formula. Sampling problems aim to produce a random object from a desired distribution, for example, producing a variable assignment drawn uniformly at random from all assignments that satisfy a Boolean formula. The problems of counting and sampling of graph structures on different types of graphs have been studied for decades for their great importance in areas like complexity theory and statistical physics. For many graph structures such as independent sets and acyclic orientations, it is widely believed that no exact or approximate (with an arbitrarily small error) polynomial-time algorithms on general graphs exist. Therefore, the research community studies various types of graphs, aiming either to design a polynomial-time counting or sampling algorithm for such inputs, or to prove a corresponding inapproximability result. Chordal graphs have been studied widely in both AI and theoretical computer science, but their study from the counting perspective has been relatively limited. Previous works showed that some graph structures can be counted in polynomial time on chordal graphs, when their counting on general graphs is provably computationally hard. The main objective of this thesis is to design and analyze counting and sampling algorithms for several well-known graph structures, including independent sets and different types of graph orientations, on chordal graphs. Our contributions can be described from two perspectives: evaluating the performances of some well-known sampling techniques, such as Markov chain Monte Carlo, on chordal graphs; and showing that the chordality does make those counting problems polynomial-time solvable.
Library of Congress Subject Headings
Graph theory; Graph algorithms; Perfect graphs; Polynomials
Publication Date
4-28-2022
Document Type
Dissertation
Student Type
Graduate
Degree Name
Computing and Information Sciences (Ph.D.)
Department, Program, or Center
Computer Science (GCCIS)
Advisor
Ivona Bezakova
Advisor/Committee Member
Edith Hemaspaandra
Advisor/Committee Member
Carlos R. Rivero
Recommended Citation
Sun, Wenbo, "Efficient Sampling and Counting of Graph Structures related to Chordal Graphs" (2022). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11271
Campus
RIT – Main Campus
Plan Codes
COMPIS-PHD