Correlation Effects in Carbon Nanotubes

We consider the effects of Coulomb interactions on single-wall carbon nanotubes using an on-site Hubbard interaction, u. For the (N,N) armchair tubes the low energy theory is shown to be identical to a 2-chain Hubbard model at half-filling, with an effective interaction u_N = u/N. Umklapp scattering leads to gaps in the spectrum of charge and spin excitations which are exponentially small for large N. Above the gaps the intrinsic nanotube resistivity due to these scattering processes is linear in temperature, as observed experimentally. The presence of "d-wave" superconductivity in the 2-chain Hubbard model away from half-filling suggests that doped armchair nanotubes might exhibit superconductity with a purely electronic mechanism.Comment: 4 pages (REVTeX), 5 postscript figures included automatically using epsf.sty. Complete postscript version also available at http://www.itp.ucsb.edu/~balents/papers.htm

Brane world solutions of perfect fluid in the background of a bulk containing dust or cosmological constant

The paper presents some solutions to the five dimensional Einstein equations due to a perfect fluid on the brane with pure dust filling the entire bulk in one case and a cosmological constant (or vacuum) in the bulk for the second case. In the first case, there is a linear relationship between isotropic pressure, energy density and the brane tension, while in the second case, the perfect fluid is assumed to be in the form of chaplygin gas. Cosmological solutions are found both for brane and bulk scenarios and some interesting features are obtained for the chaplygin gas on the brane which are distinctly different from the standard cosmology in four dimensions.Comment: 10 Latex pages, 5 figure

Reducing bias and quantifying uncertainty in watershed flux estimates: the R package loadflex

Many ecological insights into the function of rivers and watersheds emerge from quantifying the flux of solutes or suspended materials in rivers. Numerous methods for flux estimation have been described, and each has its strengths and weaknesses. Currently, the largest practical challenges in flux estimation are to select among these methods and to implement or apply whichever method is chosen. To ease this process of method selection and application, we have written an R software package called loadflex that implements several of the most popular methods for flux estimation, including regressions, interpolations, and the special case of interpolation known as the period-weighted approach. Our package also implements a lesser-known and empirically promising approach called the “composite method,” to which we have added an algorithm for estimating prediction uncertainty. Here we describe the structure and key features of loadflex, with a special emphasis on the rationale and details of our composite method implementation. We then demonstrate the use of loadflex by fitting four different models to nitrate data from the Lamprey River in southeastern New Hampshire, where two large floods in 2006–2007 are hypothesized to have driven a long-term shift in nitrate concentrations and fluxes from the watershed. The models each give believable estimates, and yet they yield different answers for whether and how the floods altered nitrate loads. In general, the best modeling approach for each new dataset will depend on the specific site and solute of interest, and researchers need to make an informed choice among the many possible models. Our package addresses this need by making it simple to apply and compare multiple load estimation models, ultimately allowing researchers to estimate riverine concentrations and fluxes with greater ease and accuracy