9,300 research outputs found
The calculation of the distance to a nearby defective matrix
In this paper a new fast algorithm for the computation of the distance of a
matrix to a nearby defective matrix is presented. The problem is formulated
following Alam & Bora (Linear Algebra Appl., 396 (2005), pp.~273--301) and
reduces to finding when a parameter-dependent matrix is singular subject to a
constraint. The solution is achieved by an extension of the Implicit
Determinant Method introduced by Spence & Poulton (J. Comput. Phys., 204
(2005), pp.~65--81). Numerical results for several examples illustrate the
performance of the algorithm.Comment: 12 page
Review of High-Quality Random Number Generators
This is a review of pseudorandom number generators (RNG's) of the highest
quality, suitable for use in the most demanding Monte Carlo calculations. All
the RNG's we recommend here are based on the Kolmogorov-Anosov theory of mixing
in classical mechanical systems, which guarantees under certain conditions and
in certain asymptotic limits, that points on the trajectories of these systems
can be used to produce random number sequences of exceptional quality. We
outline this theory of mixing and establish criteria for deciding which RNG's
are sufficiently good approximations to the ideal mathematical systems that
guarantee highest quality. The well-known RANLUX (at highest luxury level) and
its recent variant RANLUX++ are seen to meet our criteria, and some of the
proposed versions of MIXMAX can be modified easily to meet the same criteria.Comment: 21 pages, 4 figure
Particle Detection Algorithms for Complex Plasmas
In complex plasmas, the behavior of freely floating micrometer sized
particles is studied. The particles can be directly visualized and recorded by
digital video cameras. To analyze the dynamics of single particles, reliable
algorithms are required to accurately determine their positions to sub-pixel
accuracy from the recorded images. Typically, straightforward algorithms are
used for this task. Here, we combine the algorithms with common techniques for
image processing. We study several algorithms and pre- and post-processing
methods, and we investigate the impact of the choice of threshold parameters,
including an automatic threshold detection. The results quantitatively show
that each algorithm and method has its own advantage, often depending on the
problem at hand. This knowledge is applicable not only to complex plasmas, but
useful for any kind of comparable image-based particle tracking, e.g. in the
field of colloids or granular matter
Giant edge state splitting at atomically precise zigzag edges
Zigzag edges of graphene nanostructures host localized electronic states that
are predicted to be spin-polarized. However, these edge states are highly
susceptible to edge roughness and interaction with a supporting substrate,
complicating the study of their intrinsic electronic and magnetic structure.
Here, we focus on atomically precise graphene nanoribbons whose two short
zigzag edges host exactly one localized electron each. Using the tip of a
scanning tunneling microscope, the graphene nanoribbons are transferred from
the metallic growth substrate onto insulating islands of NaCl in order to
decouple their electronic structure from the metal. The absence of charge
transfer and hybridization with the substrate is confirmed by scanning
tunneling spectroscopy (STS), which reveals a pair of occupied / unoccupied
edge states. Their large energy splitting of 1.9 eV is in accordance with ab
initio many-body perturbation theory calculations and reflects the dominant
role of electron-electron interactions in these localized states.Comment: 14 pages, 4 figure
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Quantitating the epigenetic transformation contributing to cholesterol homeostasis using Gaussian process.
To understand the impact of epigenetics on human misfolding disease, we apply Gaussian-process regression (GPR) based machine learning (ML) (GPR-ML) through variation spatial profiling (VSP). VSP generates population-based matrices describing the spatial covariance (SCV) relationships that link genetic diversity to fitness of the individual in response to histone deacetylases inhibitors (HDACi). Niemann-Pick C1 (NPC1) is a Mendelian disorder caused by >300 variants in the NPC1 gene that disrupt cholesterol homeostasis leading to the rapid onset and progression of neurodegenerative disease. We determine the sequence-to-function-to-structure relationships of the NPC1 polypeptide fold required for membrane trafficking and generation of a tunnel that mediates cholesterol flux in late endosomal/lysosomal (LE/Ly) compartments. HDACi treatment reveals unanticipated epigenomic plasticity in SCV relationships that restore NPC1 functionality. GPR-ML based matrices capture the epigenetic processes impacting information flow through central dogma, providing a framework for quantifying the effect of the environment on the healthspan of the individual
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