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

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

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

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