86,040 research outputs found
Measuring Majorana fermions qubit state and non-Abelian braiding statistics in quenched inhomogeneous spin ladders
We study the Majorana fermions (MFs) in a spin ladder model. We propose and
numerically show that the MFs qubit state can be read out by measuring the
fusion excitation in the quenched inhomogeneous spin ladders. Moreover, we
construct an exactly solvable T-junction spin ladder model, which can be used
to implement braiding operations of MFs. With the braiding processes simulated
numerically as non-equilibrium quench processes, we verify that the MFs in our
spin ladder model obey the non-Abelian braiding statistics. Our scheme not only
provides a promising platform to study the exotic properties of MFs, but also
has broad range of applications in topological quantum computation.Comment: 5+3 pages, 6 figure
Distinct Spin Liquids and their Transitions in Spin-1/2 XXZ Kagome Antiferromagnets
By using the density matrix renormalization group, we study the spin-liquid
phases of spin- XXZ kagome antiferromagnets. We find that the emergence of
spin liquid phase does not depend on the anisotropy of the XXZ interaction. In
particular, the two extreme limits---Ising (strong interaction) and XY
(zero interaction)---host the same spin-liquid phases as the isotropic
Heisenberg model. Both the time-reversal-invariant spin liquid and the chiral
spin liquid with spontaneous time-reversal symmetry breaking are obtained. We
show they evolve continuously into each other by tuning the second- and
third-neighbor interactions. At last, we discuss the possible implication of
our results on the nature of spin liquid in nearest neighbor XXZ kagome
antiferromagnets, including the most studied nearest neighbor spin- kagome
anti-ferromagnetic Heisenberg model
Multivariate Analysis of Variance for Simple Designs
The analysis of variance is a well known tool for testing how treatments change the average response of experimental units. The essence of the procedure is to compare the variation among means of groups of units subjected to the same treatment with the within treatment variation. If the variation among means is large with respect to the within group variation we are likely to conclude that the treatments caused the variation and hence we say the treatments cause some change in the group means.
The usual analysis of variance checks how far apart the group means are in a single scale of measurement. Almost all researchers are interested in how the treatments affect more than one characteristic (variable) of their experimental units. A typical usage of such data is to run a standard analysis of variance on each variable. This procedure can be very misleading when trying to interpret the results. Most of the time there are strong correlations among these variables and hence if one variable tests significant the others will also. The multivariate analysis of variance provides a way of performing valid tests regardless of the correlation structure among the variables of interest
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