16,037 research outputs found
Coupling of shells in a carbon nanotube quantum dot
We systematically study the coupling of longitudinal modes (shells) in a
carbon nanotube quantum dot. Inelastic cotunneling spectroscopy is used to
probe the excitation spectrum in parallel, perpendicular and rotating magnetic
fields. The data is compared to a theoretical model including coupling between
shells, induced by atomically sharp disorder in the nanotube. The calculated
excitation spectra show good correspondence with experimental data.Comment: 8 pages, 4 figure
Theory of Bubble Nucleation and Cooperativity in DNA Melting
The onset of intermediate states (denaturation bubbles) and their role during
the melting transition of DNA are studied using the Peyrard-Bishop-Daxuois
model by Monte Carlo simulations with no adjustable parameters. Comparison is
made with previously published experimental results finding excellent
agreement. Melting curves, critical DNA segment length for stability of bubbles
and the possibility of a two states transition are studied.Comment: 4 figures. Accepted for publication in Physical Review Letter
Looking Good With Flickr Faves: Gaussian Processes for Finding Difference Makers in Personality Impressions
Flickr allows its users to generate galleries of "faves", i.e., pictures that they have tagged as favourite. According to recent studies, the faves are predictive of the personality traits that people attribute to Flickr users. This article investigates the phenomenon and shows that faves allow one to predict whether a Flickr user is perceived to be above median or not with respect to each of the Big-Five Traits (accuracy up to 79\% depending on the trait). The classifier - based on Gaussian Processes with a new kernel designed for this work - allows one to identify the visual characteristics of faves that better account for the prediction outcome
MRI and clinical resolution of a suspected intracranial toxoplasma granuloma with medical treatment in a domestic short hair cat
A two-year-old cat was presented with a left paradoxical vestibular syndrome. MRI of the brain revealed an extra-axial homogenously contrast enhancing mass in the region of the left caudal cerebellar peduncle. Toxoplasma serology was consistent with active infection and the lesion was suspected to be a toxoplasma granuloma. Following eight weeks of tapering oral prednisolone and 11 weeks of oral clindamycin treatment, repeat MRI revealed resolution of the lesion. Eighteen months after initial diagnosis, the cat remained neurologically normal. Differential diagnoses for a solitary, extra-axial, contrast enhancing mass lesion in the feline brain should include toxoplasma granuloma, which can undergo MRI and clinical resolution with medical treatment
Initial results from the Caltech/DRSI balloon-borne isotope experiment
The Caltech/DSRI balloonborne High Energy Isotope Spectrometer Telescope (HEIST) was flown successfully from Palestine, Texas on 14 May, 1984. The experiment was designed to measure cosmic ray isotopic abundances from neon through iron, with incident particle energies from approx. 1.5 to 2.2 GeV/nucleon depending on the element. During approximately 38 hours at float altitude, 100,000 events were recorded with Z or = 6 and incident energies approx. 1.5 GeV/nucleon. We present results from the ongoing data analysis associated with both the preflight Bevalac calibration and the flight data
A 2.75-Approximation Algorithm for the Unconstrained Traveling Tournament Problem
A 2.75-approximation algorithm is proposed for the unconstrained traveling
tournament problem, which is a variant of the traveling tournament problem. For
the unconstrained traveling tournament problem, this is the first proposal of
an approximation algorithm with a constant approximation ratio. In addition,
the proposed algorithm yields a solution that meets both the no-repeater and
mirrored constraints. Computational experiments show that the algorithm
generates solutions of good quality.Comment: 12 pages, 1 figur
Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes
Functional data are defined as realizations of random functions (mostly
smooth functions) varying over a continuum, which are usually collected with
measurement errors on discretized grids. In order to accurately smooth noisy
functional observations and deal with the issue of high-dimensional observation
grids, we propose a novel Bayesian method based on the Bayesian hierarchical
model with a Gaussian-Wishart process prior and basis function representations.
We first derive an induced model for the basis-function coefficients of the
functional data, and then use this model to conduct posterior inference through
Markov chain Monte Carlo. Compared to the standard Bayesian inference that
suffers serious computational burden and unstableness for analyzing
high-dimensional functional data, our method greatly improves the computational
scalability and stability, while inheriting the advantage of simultaneously
smoothing raw observations and estimating the mean-covariance functions in a
nonparametric way. In addition, our method can naturally handle functional data
observed on random or uncommon grids. Simulation and real studies demonstrate
that our method produces similar results as the standard Bayesian inference
with low-dimensional common grids, while efficiently smoothing and estimating
functional data with random and high-dimensional observation grids where the
standard Bayesian inference fails. In conclusion, our method can efficiently
smooth and estimate high-dimensional functional data, providing one way to
resolve the curse of dimensionality for Bayesian functional data analysis with
Gaussian-Wishart processes.Comment: Under revie
A note on Kerr/CFT and free fields
The near-horizon geometry of the extremal four-dimensional Kerr black hole
and certain generalizations thereof has an SL(2,R) x U(1) isometry group.
Excitations around this geometry can be controlled by imposing appropriate
boundary conditions. For certain boundary conditions, the U(1) isometry is
enhanced to a Virasoro algebra. Here, we propose a free-field construction of
this Virasoro algebra.Comment: 10 pages, v2: comments and references adde
Nonparametric Dark Energy Reconstruction from Supernova Data
Understanding the origin of the accelerated expansion of the Universe poses
one of the greatest challenges in physics today. Lacking a compelling
fundamental theory to test, observational efforts are targeted at a better
characterization of the underlying cause. If a new form of mass-energy, dark
energy, is driving the acceleration, the redshift evolution of the equation of
state parameter w(z) will hold essential clues as to its origin. To best
exploit data from observations it is necessary to develop a robust and accurate
reconstruction approach, with controlled errors, for w(z). We introduce a new,
nonparametric method for solving the associated statistical inverse problem
based on Gaussian Process modeling and Markov chain Monte Carlo sampling.
Applying this method to recent supernova measurements, we reconstruct the
continuous history of w out to redshift z=1.5.Comment: 4 pages, 2 figures, accepted for publication in Physical Review
Letter
- …