401 research outputs found
Intégrales de Selberg complexes et p-adiques et identités de Dyson-Macdonald
Cette thèse fait partie d'un programme de recherche sur la théorie conforme des champs et les représentations de l'algèbre de Lie dollar\frak{sl}_2dollar (réelle, complexe, dollarpdollar-adique, dollarqdollar-déformée). Nous étudions des versions réelle, dollarpdollar-adique et dollarqdollar-déformée d'une intégrale triple apparaissant en physique en connection avec le modèle de Liouville de la théorie conforme des champs. Ces intégrales se trouvent être aussi reliées aux identités de terme constant de Dyson-MacDonald. Et puis, nous donnons une approche différente pour calculer la version comlexe, qui utilise la technique de Bernstein-Reznikov. L'idée principale est d'appliquer des fonctionnelles invariantes à des représentations de séries principales de dollarG=SL(2,\mathbb{C})dollar. Enfin, nous définissons une dollarqdollar-déformation de Jacquet-Langlands de représentations de séries principales de dollarGL_2(\mathbb{R})dollar et nous prouvons l'unicité d'une fonctionnelle triple invariante sur ces objets en utilisant la méthode de H.Y.Loke. Nous trouvons aussi des relations semblables aux équations différentielles de [NSU].This thesis is part of a research program on Conformal field theory and representations of Lie algebra of dollar\frak{sl}_2 and prove the uniqueness of an invariant triple functional on them by using method of H.Y.Loke. Alongside, we find out some relations to similar differential equations in [NSU]
Geomechanics in unconventional resource development
To economically produce from very low permeability shale formations,
hydraulic fracturing stimulation is typically used to improve their
conductivity. This process deforms and breaks the rock, hence requires the
geomechanics data and calculation. The development of unconventional reservoirs
requires large geomechanical data, and geomechanics has involved in all
calculations of the unconventional reservoir projects. Geomechanics has
numerous contributions to the development of unconventional reservoirs from
reservoir characterization and well construction to hydraulic fracturing and
reservoir modeling as well as environmental aspect. This paper reviews and
highlights some important aspects of geomechanics on the successful development
of unconventional reservoirs as well as outlines the recent development in
unconventional reservoir geomechanics. The main objective is to emphasize the
importance of geomechanical data and geomechanics and how they are being used
in in all aspects of unconventional reservoir projects.Comment: 16 pages, 7 figures, 1 tabl
A Note on Graphs of Linear Rank-Width 1
We prove that a connected graph has linear rank-width 1 if and only if it is
a distance-hereditary graph and its split decomposition tree is a path. An
immediate consequence is that one can decide in linear time whether a graph has
linear rank-width at most 1, and give an obstruction if not. Other immediate
consequences are several characterisations of graphs of linear rank-width 1. In
particular a connected graph has linear rank-width 1 if and only if it is
locally equivalent to a caterpillar if and only if it is a vertex-minor of a
path [O-joung Kwon and Sang-il Oum, Graphs of small rank-width are pivot-minors
of graphs of small tree-width, arxiv:1203.3606] if and only if it does not
contain the co-K_2 graph, the Net graph and the 5-cycle graph as vertex-minors
[Isolde Adler, Arthur M. Farley and Andrzej Proskurowski, Obstructions for
linear rank-width at most 1, arxiv:1106.2533].Comment: 9 pages, 2 figures. Not to be publishe
Estimating Local Function Complexity via Mixture of Gaussian Processes
Real world data often exhibit inhomogeneity, e.g., the noise level, the
sampling distribution or the complexity of the target function may change over
the input space. In this paper, we try to isolate local function complexity in
a practical, robust way. This is achieved by first estimating the locally
optimal kernel bandwidth as a functional relationship. Specifically, we propose
Spatially Adaptive Bandwidth Estimation in Regression (SABER), which employs
the mixture of experts consisting of multinomial kernel logistic regression as
a gate and Gaussian process regression models as experts. Using the locally
optimal kernel bandwidths, we deduce an estimate to the local function
complexity by drawing parallels to the theory of locally linear smoothing. We
demonstrate the usefulness of local function complexity for model
interpretation and active learning in quantum chemistry experiments and fluid
dynamics simulations.Comment: 19 pages, 16 figure
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