46,394 research outputs found
Numerical Loop-Tree Duality: contour deformation and subtraction
We introduce a novel construction of a contour deformation within the
framework of Loop-Tree Duality for the numerical computation of loop integrals
featuring threshold singularities in momentum space. The functional form of our
contour deformation automatically satisfies all constraints without the need
for fine-tuning. We demonstrate that our construction is systematic and
efficient by applying it to more than 100 examples of finite scalar integrals
featuring up to six loops. We also showcase a first step towards handling
non-integrable singularities by applying our work to one-loop infrared
divergent scalar integrals and to the one-loop amplitude for the ordered
production of two and three photons. This requires the combination of our
contour deformation with local counterterms that regulate soft, collinear and
ultraviolet divergences. This work is an important step towards computing
higher-order corrections to relevant scattering cross-sections in a fully
numerical fashion.Comment: 87 page
Liver segmentation using automatically defined patient specific B-Spline surface models
This paper presents a novel liver segmentation algorithm. This is a model-driven approach; however, unlike previous techniques which use a statistical model obtained from a training set, we initialize patient-specific models directly from their own pre-segmentation. As a result, the non-trivial problems such as landmark correspondences, model registration etc. can be avoided. Moreover, by dividing the liver region into three sub-regions, we convert the problem of building one complex shape model into constructing three much simpler models, which can be fitted independently, greatly improving the computation efficiency. A robust graph-based narrow band optimal surface fitting scheme is also presented. The proposed approach is evaluated on 35 CT images. Compared to contemporary approaches, our approach has no training requirement and requires significantly less processing time, with an RMS error of 2.440.53mm against manual segmentation
Information Surfaces in Systems Biology and Applications to Engineering Sustainable Agriculture
Systems biology of plants offers myriad opportunities and many challenges in
modeling. A number of technical challenges stem from paucity of computational
methods for discovery of the most fundamental properties of complex dynamical
systems. In systems engineering, eigen-mode analysis have proved to be a
powerful approach. Following this philosophy, we introduce a new theory that
has the benefits of eigen-mode analysis, while it allows investigation of
complex dynamics prior to estimation of optimal scales and resolutions.
Information Surfaces organizes the many intricate relationships among
"eigen-modes" of gene networks at multiple scales and via an adaptable
multi-resolution analytic approach that permits discovery of the appropriate
scale and resolution for discovery of functions of genes in the model plant
Arabidopsis. Applications are many, and some pertain developments of crops that
sustainable agriculture requires.Comment: 24 Pages, DoCEIS 1
Beyond fuzzy spheres
We study polynomial deformations of the fuzzy sphere, specifically given by
the cubic or the Higgs algebra. We derive the Higgs algebra by quantizing the
Poisson structure on a surface in . We find that several
surfaces, differing by constants, are described by the Higgs algebra at the
fuzzy level. Some of these surfaces have a singularity and we overcome this by
quantizing this manifold using coherent states for this nonlinear algebra. This
is seen in the measure constructed from these coherent states. We also find the
star product for this non-commutative algebra as a first step in constructing
field theories on such fuzzy spaces.Comment: 9 pages, 3 Figures, Minor changes in the abstract have been made. The
manuscript has been modified for better clarity. A reference has also been
adde
Stochastic Dynamics of Bionanosystems: Multiscale Analysis and Specialized Ensembles
An approach for simulating bionanosystems, such as viruses and ribosomes, is
presented. This calibration-free approach is based on an all-atom description
for bionanosystems, a universal interatomic force field, and a multiscale
perspective. The supramillion-atom nature of these bionanosystems prohibits the
use of a direct molecular dynamics approach for phenomena like viral structural
transitions or self-assembly that develop over milliseconds or longer. A key
element of these multiscale systems is the cross-talk between, and consequent
strong coupling of, processes over many scales in space and time. We elucidate
the role of interscale cross-talk and overcome bionanosystem simulation
difficulties with automated construction of order parameters (OPs) describing
supra-nanometer scale structural features, construction of OP dependent
ensembles describing the statistical properties of atomistic variables that
ultimately contribute to the entropies driving the dynamics of the OPs, and the
derivation of a rigorous equation for the stochastic dynamics of the OPs. Since
the atomic scale features of the system are treated statistically, several
ensembles are constructed that reflect various experimental conditions. The
theory provides a basis for a practical, quantitative bionanosystem modeling
approach that preserves the cross-talk between the atomic and nanoscale
features. A method for integrating information from nanotechnical experimental
data in the derivation of equations of stochastic OP dynamics is also
introduced.Comment: 24 page
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