3,143 research outputs found
Hopping in a Supercooled Lennard-Jones Liquid: Metabasins, Waiting Time Distribution, and Diffusion
We investigate the jump motion among potential energy minima of a
Lennard-Jones model glass former by extensive computer simulation. From the
time series of minima energies, it becomes clear that the energy landscape is
organized in superstructures, called metabasins. We show that diffusion can be
pictured as a random walk among metabasins, and that the whole temperature
dependence resides in the distribution of waiting times. The waiting time
distribution exhibits algebraic decays: for very short times and
for longer times, where near . We
demonstrate that solely the waiting times in the very stable basins account for
the temperature dependence of the diffusion constant.Comment: to be published in Phys. Rev.
Non Markovian persistence in the diluted Ising model at criticality
We investigate global persistence properties for the non-equilibrium critical
dynamics of the randomly diluted Ising model. The disorder averaged persistence
probability of the global magnetization is found to decay
algebraically with an exponent that we compute analytically in a
dimensional expansion in . Corrections to Markov process are
found to occur already at one loop order and is thus a novel
exponent characterizing this disordered critical point. Our result is
thoroughly compared with Monte Carlo simulations in , which also include a
measurement of the initial slip exponent. Taking carefully into account
corrections to scaling, is found to be a universal exponent,
independent of the dilution factor along the critical line at , and
in good agreement with our one loop calculation.Comment: 7 pages, 4 figure
Local Properties of the Potential Energy Landscape of a Model Glass: Understanding the Low Temperature Anomalies
Though the existence of two-level systems (TLS) is widely accepted to explain
low temperature anomalies in the sound absorption, heat capacity, thermal
conductivity and other quantities, an exact description of their microscopic
nature is still lacking. We performed computer simulations for a binary
Lennard-Jones system, using a newly developed algorithm to locate double-well
potentials (DWP) and thus two-level systems on a systematic basis. We show that
the intrinsic limitations of computer simulations like finite time and finite
size problems do not hamper this analysis. We discuss how the DWP are embedded
in the total potential energy landscape. It turns out that most DWP are
connected to the dynamics of the smaller particles and that these DWP are
rather localized. However, DWP related to the larger particles are more
collective
Backward correlations and dynamic heterogeneities: a computer study of ion dynamics
We analyse the correlated back and forth dynamics and dynamic
heterogeneities, i.e. the presence of fast and slow ions, for a lithium
metasilicate system via computer simulations. For this purpose we define, in
analogy to previous work in the field of glass transition, appropriate
three-time correlation functions. They contain information about the dynamics
during two successive time intervals. First we apply them to simple model
systems in order to clarify their information content. Afterwards we use this
formalism to analyse the lithium trajectories. A strong back-dragging effect is
observed, which also fulfills the time-temperature superposition principle.
Furthermore, it turns out that the back-dragging effect is long-ranged and
exceeds the nearest neighbor position. In contrast, the strength of the dynamic
heterogeneities does not fulfill the time-temperature superposition principle.
The lower the temperature, the stronger the mobility difference between fast
and slow ions. The results are then compared with the simple model systems
considered here as well as with some lattice models of ion dynamics.Comment: 12 pages, 10 figure
What does the potential energy landscape tell us about the dynamics of supercooled liquids and glasses?
For a model glass-former we demonstrate via computer simulations how
macroscopic dynamic quantities can be inferred from a PEL analysis. The
essential step is to consider whole superstructures of many PEL minima, called
metabasins, rather than single minima. We show that two types of metabasins
exist: some allowing for quasi-free motion on the PEL (liquid-like), the others
acting as traps (solid-like). The activated, multi-step escapes from the latter
metabasins are found to dictate the slowing down of dynamics upon cooling over
a much broader temperature range than is currently assumed
The Potential for Student Performance Prediction in Small Cohorts with Minimal Available Attributes
The measurement of student performance during their progress through university study provides academic leadership with critical information on each student’s likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those “at risk” of failure/withdrawal. However, modern university environments, offering easy on-line availability of course material, may see reduced lecture/tutorial attendance, making such identification more challenging. Modern data mining and machine learning techniques provide increasingly accurate predictions of student examination assessment marks, although these approaches have focussed upon large student populations and wide ranges of data attributes per student. However, many university modules comprise relatively small student cohorts, with institutional protocols limiting the student attributes available for analysis. It appears that very little research attention has been devoted to this area of analysis and prediction. We describe an experiment conducted on a final-year university module student cohort of 23, where individual student data are limited to lecture/tutorial attendance, virtual learning environment accesses and intermediate assessments. We found potential for predicting individual student interim and final assessment marks in small student cohorts with very limited attributes and that these predictions could be useful to support module leaders in identifying students potentially “at risk.”.Peer reviewe
Finite-Size Effects in a Supercooled Liquid
We study the influence of the system size on various static and dynamic
properties of a supercooled binary Lennard-Jones liquid via computer
simulations. In this way, we demonstrate that the treatment of systems as small
as N=65 particles yields relevant results for the understanding of bulk
properties. Especially, we find that a system of N=130 particles behaves
basically as two non-interacting systems of half the size.Comment: Proceedings of the III Workshop on Non Equilibrium Phenomena in
Supercooled Fluids, Glasses and Amorphous Materials, Sep 2002, Pis
Origin of non-exponential relaxation in a crystalline ionic conductor: a multi-dimensional 109Ag NMR study
The origin of the non-exponential relaxation of silver ions in the
crystalline ion conductor Ag7P3S11 is analyzed by comparing appropriate
two-time and three-time 109Ag NMR correlation functions. The non-exponentiality
is due to a rate distribution, i.e., dynamic heterogeneities, rather than to an
intrinsic non-exponentiality. Thus, the data give no evidence for the relevance
of correlated back-and-forth jumps on the timescale of the silver relaxation.Comment: 4 pages, 3 figure
Recovering non-Maxwellian particle velocity distribution functions from collective Thomson-scattered spectra
Collective optical Thomson scattering (TS) is a diagnostic commonly used to
characterize plasma parameters. These parameters are typically extracted by a
fitting algorithm that minimizes the difference between a measured scattered
spectrum and an analytic spectrum calculated from the velocity distribution
function (VDF) of the plasma. However, most existing TS analysis algorithms
assume the VDFs are Maxwellian, and applying an algorithm which makes this
assumption does not accurately extract the plasma parameters of a
non-Maxwellian plasma due to the effect of non-Maxwellian deviations on the TS
spectra. We present new open-source numerical tools for forward modeling
analytic spectra from arbitrary VDFs, and show that these tools are able to
more accurately extract plasma parameters from synthetic TS spectra generated
by non-Maxwellian VDFs compared to standard TS algorithms. Estimated posterior
probability distributions of fits to synthetic spectra for a variety of example
non-Maxwellian VDFs are used to determine uncertainties in the extracted plasma
parameters, and show that correlations between parameters can significantly
affect the accuracy of fits in plasmas with non-Maxwellian VDFs
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