271 research outputs found
An intermediate state between the kagome-ice and the fully polarized state in DyTiO
DyTiO is at present the cleanest example of a spin-ice material.
Previous theoretical and experimental work on the first-order transition
between the kagome-ice and the fully polarized state has been taken as a
validation for the dipolar spin-ice model. Here we investigate in further depth
this phase transition using ac-susceptibility and dc-magnetization, and compare
this results with Monte-Carlo simulations and previous magnetization and
specific heat measurements. We find signatures of an intermediate state between
the kagome-ice and full polarization. This signatures are absent in current
theoretical models used to describe spin-ice materials.Comment: 7 pages, 4 figure
Dynamic relaxation of a liquid cavity under amorphous boundary conditions
The growth of cooperatively rearranging regions was invoked long ago by Adam
and Gibbs to explain the slowing down of glass-forming liquids. The lack of
knowledge about the nature of the growing order, though, complicates the
definition of an appropriate correlation function. One option is the
point-to-set correlation function, which measures the spatial span of the
influence of amorphous boundary conditions on a confined system. By using a
swap Monte Carlo algorithm we measure the equilibration time of a liquid
droplet bounded by amorphous boundary conditions in a model glass-former at low
temperature, and we show that the cavity relaxation time increases with the
size of the droplet, saturating to the bulk value when the droplet outgrows the
point-to-set correlation length. This fact supports the idea that the
point-to-set correlation length is the natural size of the cooperatively
rearranging regions. On the other hand, the cavity relaxation time computed by
a standard, nonswap dynamics, has the opposite behavior, showing a very steep
increase when the cavity size is decreased. We try to reconcile this difference
by discussing the possible hybridization between MCT and activated processes,
and by introducing a new kind of amorphous boundary conditions, inspired by the
concept of frozen external state as an alternative to the commonly used frozen
external configuration.Comment: Completely rewritten version. After the first submission it was
realized that swap and nonswap dynamics results are qualitatively different.
This version reports the results of both dynamics and discusses the different
behaviors. 17 pages, 18 figure
High temperature onset of field-induced transitions in the spin-ice compound Dy2Ti2O7
We have studied the field-dependent ac magnetic susceptibility of single
crystals of Dy2Ti2O7 spin ice along the [111] direction in the temperature
range 1.8 K - 7 K. Our data reflect the onset of local spin ice order in the
appearance of different field regimes. In particular, we observe a prominent
feature at approximately 1.0 T that is a precursor of the low-temperature
metamagnetic transition out of field-induced kagome ice, below which the
kinetic constraints imposed by the ice rules manifest themselves in a
substantial frequency-dependence of the susceptibility. Despite the relatively
high temperatures, our results are consistent with a monopole picture, and they
demonstrate that such a picture can give physical insight to the spin ice
systems even outside the low-temperature, low-density limit where monopole
excitations are well-defined quasiparticles
Numerical simulations of liquids with amorphous boundary conditions
It has recently become clear that simulations under amorphpous boundary
conditions (ABCs) can provide valuable information on the dynamics and
thermodynamics of disordered systems with no obvious ordered parameter. In
particular, they allow to detect a correlation length that is not measurable
with standard correlation functions. Here we explain what exactly is meant by
ABCs, discuss their relation with point-to-set correlations and briefly
describe some recent results obtained with this technique.Comment: Presented at STATPHYS 2
Rigid-Band Shift of the Fermi Level in a Strongly Correlated Metal: Sr(2-y)La(y)RuO(4)
We report a systematic study of electron doping of Sr2RuO4 by non-isovalent
substitution of La^(3+) for Sr^(2+). Using a combination of de Haas-van Alphen
oscillations, specific heat, and resistivity measurements, we show that
electron doping leads to a rigid-band shift of the Fermi level corresponding to
one doped electron per La ion, with constant many-body quasiparticle mass
enhancement over the band mass. The susceptibility spectrum is substantially
altered and enhanced by the doping but this has surprisingly little effect on
the strength of the unconventional superconducting pairing.Comment: 4 pages, 3 figure
Anderson Localization in Euclidean Random Matrices
We study spectra and localization properties of Euclidean random matrices.
The problem is approximately mapped onto that of a matrix defined on a random
graph. We introduce a powerful method to find the density of states and the
localization threshold. We solve numerically an exact equation for the
probability distribution function of the diagonal element of the the resolvent
matrix, with a population dynamics algorithm, and we show how this can be used
to find the localization threshold. An application of the method in the context
of the Instantaneous Normal Modes of a liquid system is given.Comment: 4 page
Metamagnetic Quantum Criticality
A renormalization group treatment of metamagnetic quantum criticality in
metals is presented. In clean systems the universality class is found to be of
the overdamped, conserving (dynamical exponent z=3) Ising type. Detailed
results are obtained for the field and temperature dependence of physical
quantities including the differential susceptibility, resistivity and specific
heat near the transition. An application of the theory is made to Sr3Ru2O7,
which appears to exhibit a metamagnetic critical end-point at a very low
temperature and a field of order 5-7T.Comment: 4 pages latex (Revtex 4) and 3 eps figure
Integration of machine learning with neutron scattering for the Hamiltonian tuning of spin ice under pressure
Quantum materials research requires co-design of theory with experiments and involves demanding simulations and the analysis of vast quantities of data, usually including pattern recognition and clustering. Artificial intelligence is a natural route to optimise these processes and bring theory and experiments together. Here, we propose a scheme that integrates machine learning with high-performance simulations and scattering measurements, covering the pipeline of typical neutron experiments. Our approach uses nonlinear autoencoders trained on realistic simulations along with a fast surrogate for the calculation of scattering in the form of a generative model. We demonstrate this approach in a highly frustrated magnet, Dy2Ti2O7, using machine learning predictions to guide the neutron scattering experiment under hydrostatic pressure, extract material parameters and construct a phase diagram. Our scheme provides a comprehensive set of capabilities that allows direct integration of theory along with automated data processing and provides on a rapid timescale direct insight into a challenging condensed matter system.Fil: Samarakoon, Anjana. Oak Ridge National Laboratory; Estados Unidos. Argonne National Laboratory; Estados UnidosFil: Tennant, D. Alan. Oak Ridge National Laboratory; Estados UnidosFil: Ye, Feng. Oak Ridge National Laboratory; Estados UnidosFil: Zhang, Qiang. Oak Ridge National Laboratory; Estados UnidosFil: Grigera, Santiago AndrĂ©s. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - La Plata. Instituto de FĂsica de LĂquidos y Sistemas BiolĂłgicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de FĂsica de LĂquidos y Sistemas BiolĂłgicos; Argentin
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