Results 11 to 20 of about 79,195 (126)

Popular matchings in the marriage and roommates problems [PDF]

open access: yes, 2010
Popular matchings have recently been a subject of study in the context of the so-called House Allocation Problem, where the objective is to match applicants to houses over which the applicants have preferences.
A.E. Roth   +23 more
core   +1 more source

Strong Integer Additive Set-valued Graphs: A Creative Review [PDF]

open access: yes, 2015
For a non-empty ground set $X$, finite or infinite, the {\em set-valuation} or {\em set-labeling} of a given graph $G$ is an injective function $f:V(G) \to \mathcal{P}(X)$, where $\mathcal{P}(X)$ is the power set of the set $X$. A set-indexer of a graph $
K. A. Germina   +3 more
core   +1 more source

Wishart distributions for decomposable graphs

open access: yes, 2007
When considering a graphical Gaussian model ${\mathcal{N}}_G$ Markov with respect to a decomposable graph $G$, the parameter space of interest for the precision parameter is the cone $P_G$ of positive definite matrices with fixed zeros corresponding to ...
Letac, Gérard, Massam, Hélène
core   +4 more sources

Spin‐Split Edge States in Metal‐Supported Graphene Nanoislands Obtained by CVD

open access: yesAdvanced Materials, EarlyView.
Combining STM measurements and ab‐initio calculations, we show that zig‐zag edges in graphene nanoislands grown on Ni(111) by CVD retrieve their spin‐polarized edge states after intercalation of a few monolayers of Au. ABSTRACT Spin‐split states localized on zigzag edges have been predicted for different free‐standing graphene nanostructures.
Michele Gastaldo   +6 more
wiley   +1 more source

Homogeneous sets, clique-separators, critical graphs, and optimal $\chi$-binding functions

open access: yes, 2021
Given a set $\mathcal{H}$ of graphs, let $f_\mathcal{H}^\star\colon \mathbb{N}_{>0}\to \mathbb{N}_{>0}$ be the optimal $\chi$-binding function of the class of $\mathcal{H}$-free graphs, that is, $$f_\mathcal{H}^\star(\omega)=\max\{\chi(G): G\text{ is ...
Brause, Christoph   +2 more
core  

Imperfection in Semiconductors Leading to High Performance Devices

open access: yesAdvanced Science, EarlyView.
Crystalline perfection is typically pursued in semiconductors to enhance device performance. However, through modeling and experimental work, we show that defects can be strategically employed in a specific detection regime to increase sensitivity to extreme values. GaN diodes are demonstrated to effectively detect high‐energy proton beams at fluxes as
Jean‐Yves Duboz   +8 more
wiley   +1 more source

The Strong Perfect Graph Conjecture: 40 years of Attempts, and its Resolution [PDF]

open access: yes, 2009
International audienceThe Strong Perfect Graph Conjecture (SPGC) was certainly one of the most challenging conjectures in graph theory. During more than four decades, numerous attempts were made to solve it, by combinatorial methods, by linear algebraic ...
Roussel, Florian   +2 more
core   +1 more source

Linear conic formulations for two-party correlations and values of nonlocal games

open access: yes, 2016
In this work we study the sets of two-party correlations generated from a Bell scenario involving two spatially separated systems with respect to various physical models.
Sikora, Jamie, Varvitsiotis, Antonios
core   +1 more source

Graph‐Theory Approach to Element Miscibility and Alloy Design

open access: yesAdvanced Science, EarlyView.
Graph and network theory enables pathway toward complex multiscale interactions between different elements for alloy design or interface engineering. Utilizing element's inherent properties and preferential interactivity, favorable mixed material formation, solubility and miscibility can be predicted.
Andrew Martin   +6 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

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