2,001 research outputs found

    Helical modes in carbon nanotubes generated by strong electric fields

    Full text link
    Helical modes, conducting opposite spins in opposite directions, are shown to exist in metallic armchair nanotubes in an all-electric setup. This is a consequence of the interplay between spin-orbit interaction and strong electric fields. The helical regime can also be obtained in chiral metallic nanotubes by applying an additional magnetic field. In particular, it is possible to obtain helical modes at one of the two Dirac points only, while the other one remains gapped. Starting from a tight-binding model we derive the effective low-energy Hamiltonian and the resulting spectrum

    Hyperplane arrangements of Torelli type

    Full text link
    We give a necessary and sufficient condition in order for a hyperplane arrangement to be of Torelli type, namely that it is recovered as the set of unstable hyperplanes of its Dolgachev sheaf of logarithmic differentials. Decompositions and semistability of non-Torelli arrangements are investigated.Comment: 2 Figue

    Insertions Yielding Equivalent Double Occurrence Words

    Full text link
    A double occurrence word (DOW) is a word in which every symbol appears exactly twice; two DOWs are equivalent if one is a symbol-to-symbol image of the other. We consider the so called repeat pattern (αα\alpha\alpha) and the return pattern (ααR\alpha\alpha^R), with gaps allowed between the α\alpha's. These patterns generalize square and palindromic factors of DOWs, respectively. We introduce a notion of inserting repeat/return words into DOWs and study how two distinct insertions into the same word can produce equivalent DOWs. Given a DOW ww, we characterize the structure of ww which allows two distinct insertions to yield equivalent DOWs. This characterization depends on the locations of the insertions and on the length of the inserted repeat/return words and implies that when one inserted word is a repeat word and the other is a return word, then both words must be trivial (i.e., have only one symbol). The characterization also introduces a method to generate families of words recursively

    The Stripe 82 Massive Galaxy Project III: A Lack of Growth Among Massive Galaxies

    Get PDF
    The average stellar mass (Mstar) of high-mass galaxies (Mstar > 3e11 Msun) is expected to grow by ~30% since z~1, largely through ongoing mergers that are also invoked to explain the observed increase in galaxy sizes. Direct evidence for the corresponding growth in stellar mass has been elusive, however, in part because the volumes sampled by previous redshift surveys have been too small to yield reliable statistics. In this work, we make use of the Stripe 82 Massive Galaxy Catalog to build a mass-limited sample of 41,770 galaxies (Mstar > 1.6e11) with optical to near-IR photometry and a large fraction (>55%) of spectroscopic redshifts. Our sample spans 139 square degrees, significantly larger than most previous efforts. After accounting for a number of potential systematic errors, including the effects of Mstar scatter, we measure galaxy stellar mass functions over 0.3 < z < 0.65 and detect no growth in the typical Mstar of massive galaxies with an uncertainty of 9%. This confidence level is dominated by uncertainties in the star formation history assumed for Mstar estimates, although our inability to characterize low surface-brightness outskirts may be the most important limitation of our study. Even among these high-mass galaxies, we find evidence for differential evolution when splitting the sample by recent star formation (SF) activity. While low-SF systems appear to become completely passive, we find a mostly sub-dominant population of galaxies with residual, but low rates of star formation (~1 Msun/yr) number density does not evolve. Interestingly, these galaxies become more prominent at higher Mstar, representing ~10% of all galaxies at Mstar ~ 1e12 Msun and perhaps dominating at even larger masses.Comment: Accepted in Ap

    Learning Inverse Rig Mappings by Nonlinear Regression

    Get PDF
    corecore