166 research outputs found
Spanning trees in sparse expanders
Given integers , let be the
collection of all -vertex trees with maximum degree at most . A
question of Alon, Krivelevich and Sudakov in 2007 asks for determining the best
possible spectral gap condition forcing an -graph to be
-universal, namely, it contains all members of
as a subgraph simultaneously. In this paper we show
that for all and sufficiently large , every -graph with is
-universal. As an immediate corollary, this implies
that Alon's ingenious construction of triangle-free sparse expander is
-universal, which provides an explicit construction of
such graphs and thus solves a question of Johannsen, Krivelevich and Samotij.
Our main result is formulated under a much more general context, namely, the
-expanders. More precisely, we show that there exist absolute constants
such that the following statement holds for sufficiently large integer
.
For all , every -expander is -universal.
For all with , every -expander is -universal.
Both results significantly improve a result of Johannsen, Krivelevich and
Samotij, and have further implications in locally sparse expanders and
Maker-Breaker games that also improve previously known results drastically.Comment: 27 pages, 4 figures, comments are welcom
Clique immersion in graphs without fixed bipartite graph
A graph contains as an \emph{immersion} if there is an injective
mapping such that for each edge ,
there is a path in joining vertices and , and
all the paths , , are pairwise edge-disjoint. An analogue
of Hadwiger's conjecture for the clique immersions by Lescure and Meyniel
states that every graph contains as an immersion. We consider
the average degree condition and prove that for any bipartite graph , every
-free graph with average degree contains a clique immersion of order
, implying that Lescure and Meyniel's conjecture holds
asymptotically for graphs without fixed bipartite graph.Comment: 2 figure
Machine Learning-Enabled Regional Multi-Hazards Risk Assessment Considering Social Vulnerability
The regional multi-hazards risk assessment poses difficulties due to data access challenges, and the potential interactions between multi-hazards and social vulnerability. For better natural hazards risk perception and preparedness, it is important to study the nature-hazards risk distribution in different areas, specifically a major priority in the areas of high hazards level and social vulnerability. We propose a multi-hazards risk assessment method which considers social vulnerability into the analyzing and utilize machine learning-enabled models to solve this issue. The proposed methodology integrates three aspects as follows: (1) characterization and mapping of multi-hazards (Flooding, Wildfires, and Seismic) using five machine learning methods including Naïve Bayes (NB), K-Nearest Neighbors (KNN), Logistic Regression (LR), Random Forest (RF), and K-Means (KM); (2) evaluation of social vulnerability with a composite index tailored for the case-study area and using machine learning models for classification; (3) risk-based quantification of spatial interaction mechanisms between multi-hazards and social vulnerability. The results indicate that RF model performs best in both hazard-related and social vulnerability datasets. The most cities at multi-hazards risk account for 34.12% of total studied cities (covering 20.80% land). Additionally, high multi-hazards level and socially vulnerable cities account for 15.88% (covering 4.92% land). This study generates a multi-hazards risk map which show a wide variety of spatial patterns and a corresponding understanding of where regional high hazards potential and vulnerable areas are. It emphasizes an urgent need to implement information-based prioritization when natural hazards coming, and effective policy measures for reducing natural-hazards risks in future
On powers of Hamilton cycles in Ramsey-Tur\'{a}n Theory
We prove that for with and , there exist
and such that for every , every -vertex
graph with and
contains an -th power of a Hamilton cycle. We also
show that the minimum degree condition is asymptotically sharp for and
the case was recently conjectured by Staden and Treglown.Comment: 19 pages, 4 figure
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