23,423 research outputs found
Proposal for a [111] Magnetization Plateau in the Spin Liquid State of Tb2Ti2O7
Despite a Curie-Weiss temperature K, the Tb2Ti2O7
pyrochlore magnetic material lacks long range magnetic order down to at least
mK. It has recently been proposed that the low temperature
collective paramagnetic or spin liquid regime of this material may be akin to a
spin ice state subject to both thermal and quantum fluctuations a {\it
quantum spin ice} (QSI) of sorts. Here we explore the effect of a magnetic
field along the direction on the QSI state. To do so, we
investigate the magnetic properties of a microscopic model of Tb2Ti2O7 in an
independent tetrahedron approximation in a finite along . Such
a model describes semi-quantitatively the collective paramagnetic regime where
nontrivial spin correlations start to develop at the shortest lengthscale, that
is over a single tetrahedron, but where no long range order is yet present. Our
results show that a magnetization plateau develops at low temperatures as the
system develops ferromagnetic spin-ice-like "two-in/two-out"
correlations at the shortest lengthscale. From these results, we are led to
propose that the observation of such a [111] magnetization plateau in Tb2Ti2O7
would provide compelling evidence for a QSI at in this material and
help guide the development of a theory for the origin of its spin liquid state.Comment: 6 pages, 3 figure
A systematic review of data quality issues in knowledge discovery tasks
Hay un gran crecimiento en el volumen de datos porque las organizaciones capturan permanentemente la cantidad colectiva de datos para lograr un mejor proceso de toma de decisiones. El desafÃo mas fundamental es la exploración de los grandes volúmenes de datos y la extracción de conocimiento útil para futuras acciones por medio de tareas para el descubrimiento del conocimiento; sin embargo, muchos datos presentan mala calidad. Presentamos una revisión sistemática de los asuntos de calidad de datos en las áreas del descubrimiento de conocimiento y un estudio de caso aplicado a la enfermedad agrÃcola conocida como la roya del café.Large volume of data is growing because the organizations are continuously capturing the collective amount of data for better decision-making process. The most fundamental challenge is to explore the large volumes of data and extract useful knowledge for future actions through knowledge discovery tasks, nevertheless many data has poor quality. We presented a systematic review of the data quality issues in knowledge discovery tasks and a case study applied to agricultural disease named coffee rust
Clustering and classifying images with local and global variability
A procedure for clustering and classifying images determined by three classification
variables is presented. A measure of global variability based on the singular value
decomposition of the image matrices, and two average measures of local variability
based on spatial correlation and spatial changes. The performance of the procedure is
compared using three different databases
Population Synthesis via k-Nearest Neighbor Crossover Kernel
The recent development of multi-agent simulations brings about a need for
population synthesis. It is a task of reconstructing the entire population from
a sampling survey of limited size (1% or so), supplying the initial conditions
from which simulations begin. This paper presents a new kernel density
estimator for this task. Our method is an analogue of the classical
Breiman-Meisel-Purcell estimator, but employs novel techniques that harness the
huge degree of freedom which is required to model high-dimensional nonlinearly
correlated datasets: the crossover kernel, the k-nearest neighbor restriction
of the kernel construction set and the bagging of kernels. The performance as a
statistical estimator is examined through real and synthetic datasets. We
provide an "optimization-free" parameter selection rule for our method, a
theory of how our method works and a computational cost analysis. To
demonstrate the usefulness as a population synthesizer, our method is applied
to a household synthesis task for an urban micro-simulator.Comment: 10 pages, 4 figures, IEEE International Conference on Data Mining
(ICDM) 201
Studies of non-magnetic impurities in the spin-1/2 Kagome Antiferromagnet
Motivated by recent experiments on ZnCu(OH)Cl, we study the
inhomogeneous Knight shifts (local susceptibilities) of spin 1/2 Kagome
antiferromagnet in the presence of nonmagnetic impurities. Using high
temperature series expansion, we calculate the local susceptibility and its
histogram down to about T=0.4J. At low temperatures, we explore a Dirac spin
liquid proposal and calculate the local susceptibility in the mean field and
beyond mean field using Gutzwiller projection, finding the overall picture to
be consistent with the NMR experiments.Comment: 12 pages, 9 figure
Entanglement Dynamics in 1D Quantum Cellular Automata
Several proposed schemes for the physical realization of a quantum computer
consist of qubits arranged in a cellular array. In the quantum circuit model of
quantum computation, an often complex series of two-qubit gate operations is
required between arbitrarily distant pairs of lattice qubits. An alternative
model of quantum computation based on quantum cellular automata (QCA) requires
only homogeneous local interactions that can be implemented in parallel. This
would be a huge simplification in an actual experiment. We find some minimal
physical requirements for the construction of unitary QCA in a 1 dimensional
Ising spin chain and demonstrate optimal pulse sequences for information
transport and entanglement distribution. We also introduce the theory of
non-unitary QCA and show by example that non-unitary rules can generate
environment assisted entanglement.Comment: 12 pages, 8 figures, submitted to Physical Review
Kinematics of Multigrid Monte Carlo
We study the kinematics of multigrid Monte Carlo algorithms by means of
acceptance rates for nonlocal Metropolis update proposals. An approximation
formula for acceptance rates is derived. We present a comparison of different
coarse-to-fine interpolation schemes in free field theory, where the formula is
exact. The predictions of the approximation formula for several interacting
models are well confirmed by Monte Carlo simulations. The following rule is
found: For a critical model with fundamental Hamiltonian H(phi), absence of
critical slowing down can only be expected if the expansion of
in terms of the shift psi contains no relevant (mass) term. We also introduce a
multigrid update procedure for nonabelian lattice gauge theory and study the
acceptance rates for gauge group SU(2) in four dimensions.Comment: 28 pages, 8 ps-figures, DESY 92-09
- …