23,866 research outputs found
Coherent transport of armchair graphene constrictions
The coherent transport properties of armchair graphene nanoconstrictions(GNC)
are studied using tight-binding approach and Green's function method. We find a
non-bonding state at zero Fermi energy which results in a zero conductance
valley, when a single vacancy locates at of a perfect metallic
armchair graphene nanoribbon(aGNR). However, the non-bonding state doesn't
exist when a vacancy locates at y=3n, and the conductance behavior of lowest
conducting channel will not be affected by the vacancy. For the square-shaped
armchair GNC consisting of three metallic aGNR segments, resonant tunneling
behavior is observed in the single channel energy region. We find that the
presence of localized edge state locating at the zigzag boundary can affect the
resonant tunneling severely. A simplified one dimensional model is put forward
at last, which explains the resonant tunneling behavior of armchair GNC very
well.Comment: 6 pages, 11 figure
Nearly Tight Bounds for Sandpile Transience on the Grid
We use techniques from the theory of electrical networks to give nearly tight
bounds for the transience class of the Abelian sandpile model on the
two-dimensional grid up to polylogarithmic factors. The Abelian sandpile model
is a discrete process on graphs that is intimately related to the phenomenon of
self-organized criticality. In this process, vertices receive grains of sand,
and once the number of grains exceeds their degree, they topple by sending
grains to their neighbors. The transience class of a model is the maximum
number of grains that can be added to the system before it necessarily reaches
its steady-state behavior or, equivalently, a recurrent state. Through a more
refined and global analysis of electrical potentials and random walks, we give
an upper bound and an lower bound for the
transience class of the grid. Our methods naturally extend to
-sized -dimensional grids to give upper
bounds and lower bounds.Comment: 36 pages, 4 figure
- …