134,599 research outputs found
Radon Transform in Finite Dimensional Hilbert Space
Novel analysis of finite dimensional Hilbert space is outlined. The approach
bypasses general, inherent, difficulties present in handling angular variables
in finite dimensional problems: The finite dimensional, d, Hilbert space
operators are underpinned with finite geometry which provide intuitive
perspective to the physical operators. The analysis emphasizes a central role
for projectors of mutual unbiased bases (MUB) states, extending thereby their
use in finite dimensional quantum mechanics studies. Interrelation among the
Hilbert space operators revealed via their (finite) dual affine plane geometry
(DAPG) underpinning are displayed and utilized in formulating the finite
dimensional ubiquitous Radon transformation and its inverse illustrating phase
space-like physics encoded in lines and points of the geometry. The finite
geometry required for our study is outlined.Comment: 8page
Multiscale computational first order homogenization of thick shells for the analysis of out-of-plane loaded masonry walls
This work presents a multiscale method based on computational homogenization for the analysis of general heterogeneous thick shell structures, with special focus on periodic brick-masonry walls. The proposed method is designed for the analysis of shells whose micro-structure is heterogeneous in the in-plane directions, but initially homogeneous in the shell-thickness direction, a structural topology that can be found in single-leaf brick masonry walls. Under this assumption, this work proposes an efficient homogenization scheme where both the macro-scale and the micro-scale are described by the same shell theory. The proposed method is then applied to the analysis of out-of-plane loaded brick-masonry walls, and compared to experimental and micro-modeling results.Peer ReviewedPostprint (author's final draft
MGOS: A library for molecular geometry and its operating system
The geometry of atomic arrangement underpins the structural understanding of molecules in many fields. However, no general framework of mathematical/computational theory for the geometry of atomic arrangement exists. Here we present "Molecular Geometry (MG)'' as a theoretical framework accompanied by "MG Operating System (MGOS)'' which consists of callable functions implementing the MG theory. MG allows researchers to model complicated molecular structure problems in terms of elementary yet standard notions of volume, area, etc. and MGOS frees them from the hard and tedious task of developing/implementing geometric algorithms so that they can focus more on their primary research issues. MG facilitates simpler modeling of molecular structure problems; MGOS functions can be conveniently embedded in application programs for the efficient and accurate solution of geometric queries involving atomic arrangements. The use of MGOS in problems involving spherical entities is akin to the use of math libraries in general purpose programming languages in science and engineering. (C) 2019 The Author(s). Published by Elsevier B.V
Linguistic Geometries for Unsupervised Dimensionality Reduction
Text documents are complex high dimensional objects. To effectively visualize
such data it is important to reduce its dimensionality and visualize the low
dimensional embedding as a 2-D or 3-D scatter plot. In this paper we explore
dimensionality reduction methods that draw upon domain knowledge in order to
achieve a better low dimensional embedding and visualization of documents. We
consider the use of geometries specified manually by an expert, geometries
derived automatically from corpus statistics, and geometries computed from
linguistic resources.Comment: 13 pages, 15 figure
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