18,438 research outputs found
Exact Expressions for Minor Hysteresis Loops in the Random Field Ising Model on a Bethe Lattice at Zero Temperature
We obtain exact expressions for the minor hysteresis loops in the
ferromagnetic random field Ising model on a Bethe lattice at zero temperature
in the case when the driving field is cycled infinitely slowly.Comment: Replaced with the published versio
Effect of a Pacific sea surface temperature anomaly on the circulation over North America
During the fall and winter of 1976-1977, sea surface temperature (SST) in the north Pacific was characterized by abnormally cold temperatures in the central and western portions of the north Pacific with a warm pool located off the west coast of the U.S. It was suggested that the north Pacific SST anomalies were one of the multiple causes of the abnormally cold temperatures in eastern North America during the 1976-1977 winter. An attempt was made to test this hypothesis by conducting a numerical experiment with the GLAS general circulation model
REinforcement learning based Adaptive samPling: REAPing Rewards by Exploring Protein Conformational Landscapes
One of the key limitations of Molecular Dynamics simulations is the
computational intractability of sampling protein conformational landscapes
associated with either large system size or long timescales. To overcome this
bottleneck, we present the REinforcement learning based Adaptive samPling
(REAP) algorithm that aims to efficiently sample conformational space by
learning the relative importance of each reaction coordinate as it samples the
landscape. To achieve this, the algorithm uses concepts from the field of
reinforcement learning, a subset of machine learning, which rewards sampling
along important degrees of freedom and disregards others that do not facilitate
exploration or exploitation. We demonstrate the effectiveness of REAP by
comparing the sampling to long continuous MD simulations and least-counts
adaptive sampling on two model landscapes (L-shaped and circular), and
realistic systems such as alanine dipeptide and Src kinase. In all four
systems, the REAP algorithm consistently demonstrates its ability to explore
conformational space faster than the other two methods when comparing the
expected values of the landscape discovered for a given amount of time. The key
advantage of REAP is on-the-fly estimation of the importance of collective
variables, which makes it particularly useful for systems with limited
structural information
The seasonal cycle of energetics from the GLAS/UMD climate GCM
The annual cycle of atmospheric energetics from a 2-year integration of the GLAS/UMD Climate GCM is computed and compared to results from the European Centre analyses of the GWE year, and to previously published results on a global basis. All calculations are done in the mixed space-time domain. The main conclusions are: (1) the seasonal cycle of today's eddy kinetic energy (in both hemispheres), and of the transient eddy available potential energy and the potential-to-kinetic energy conversions (mean and eddy) in the Northern Hemisphere are well simulated by the GCM; (2) the GCM's tendency to have anomalously large mean u-winds at upper levels in high latitudes leads to excessive wintertime values of mean kinetic and available potential energies, and causes distortions in the GCM latitude-height distribution of kinetic energy and of many of the conversions; (3) the eddy conversion of available potential-to-kinetic energy obtained from the ageostrophic wind in these analyses; and (4) the conversions in the Southern Hemisphere are not well simulated by the GCM, although the observations are somewhat questionable
Self-Diffusion in 2D Dusty Plasma Liquids: Numerical Simulation Results
We perform Brownian dynamics simulations for studying the self-diffusion in
two-dimensional (2D) dusty plasma liquids, in terms of both mean-square
displacement and velocity autocorrelation function (VAF). Super-diffusion of
charged dust particles has been observed to be most significant at infinitely
small damping rate for intermediate coupling strength, where the
long-time asymptotic behavior of VAF is found to be the product of and
. The former represents the prediction of early theories in
2D simple liquids and the latter the VAF of a free Brownian particle. This
leads to a smooth transition from super-diffusion to normal diffusion, and then
to sub-diffusion with an increase of the damping rate. These results well
explain the seemingly contradictory scattered in recent classical molecular
dynamics simulations and experiments of dusty plasmas.Comment: 10 pages 5 figures, accepted by PR
Risk factors for acute exacerbations of COPD in a primary care population: A retrospective observational cohort study
Objectives: To evaluate risk factors associated with exacerbation frequency in primary care. Information on exacerbations of chronic obstructive pulmonary disease (COPD) has mainly been generated by secondary care-based clinical cohorts. Design: Retrospective observational cohort study. Setting: Electronic medical records database (England and Wales). Participants: 58 589 patients with COPD aged ≥40 years with COPD diagnosis recorded between 1 April 2009 and 30 September 2012, and with at least 365 days of follow-up before and after the COPD diagnosis, were identified in the Clinical Practice Research Datalink. Mean age: 69 years; 47% female; mean forced expiratory volume in 1s 60% predicted. Outcome measures: Data on moderate or severe exacerbation episodes defined by diagnosis and/or medication codes 12 months following cohort entry were retrieved, together with demographic and clinical characteristics. Associations between patient characteristics and odds of having none versus one, none versus frequent (≥2) and one versus frequent exacerbations over 12 months follow-up were evaluated using multivariate logistic regression models. Results: During follow-up, 23% of patients had evidence of frequent moderate-to-severe COPD exacerbations (24% one; 53% none). Independent predictors of increased odds of having exacerbations during the follow-up, either frequent episodes or one episode, included prior exacerbations, increasing dyspnoea score, increasing grade of airflow limitation, females and prior or current history of several comorbidities (eg, asthma, depression, anxiety, heart failure and cancer). Conclusions: Primary care-managed patients with COPD at the highest risk of exacerbations can be identified by exploring medical history for the presence of prior exacerbations, greater COPD disease severity and co-occurrence of other medical conditions
Hysteresis in the Random Field Ising Model and Bootstrap Percolation
We study hysteresis in the random-field Ising model with an asymmetric
distribution of quenched fields, in the limit of low disorder in two and three
dimensions. We relate the spin flip process to bootstrap percolation, and show
that the characteristic length for self-averaging increases as in 2d, and as in 3d, for disorder
strength much less than the exchange coupling J. For system size , the coercive field varies as for
the square lattice, and as on the cubic lattice.
Its limiting value is 0 for L tending to infinity, both for square and cubic
lattices. For lattices with coordination number 3, the limiting magnetization
shows no jump, and tends to J.Comment: 4 pages, 4 figure
GPU Acceleration of Image Convolution using Spatially-varying Kernel
Image subtraction in astronomy is a tool for transient object discovery such
as asteroids, extra-solar planets and supernovae. To match point spread
functions (PSFs) between images of the same field taken at different times a
convolution technique is used. Particularly suitable for large-scale images is
a computationally intensive spatially-varying kernel. The underlying algorithm
is inherently massively parallel due to unique kernel generation at every pixel
location. The spatially-varying kernel cannot be efficiently computed through
the Convolution Theorem, and thus does not lend itself to acceleration by Fast
Fourier Transform (FFT). This work presents results of accelerated
implementation of the spatially-varying kernel image convolution in multi-cores
with OpenMP and graphic processing units (GPUs). Typical speedups over ANSI-C
were a factor of 50 and a factor of 1000 over the initial IDL implementation,
demonstrating that the techniques are a practical and high impact path to
terabyte-per-night image pipelines and petascale processing.Comment: 4 pages. Accepted to IEEE-ICIP 201
Analysis of the 3DVAR Filter for the Partially Observed Lorenz '63 Model
The problem of effectively combining data with a mathematical model
constitutes a major challenge in applied mathematics. It is particular
challenging for high-dimensional dynamical systems where data is received
sequentially in time and the objective is to estimate the system state in an
on-line fashion; this situation arises, for example, in weather forecasting.
The sequential particle filter is then impractical and ad hoc filters, which
employ some form of Gaussian approximation, are widely used. Prototypical of
these ad hoc filters is the 3DVAR method. The goal of this paper is to analyze
the 3DVAR method, using the Lorenz '63 model to exemplify the key ideas. The
situation where the data is partial and noisy is studied, and both discrete
time and continuous time data streams are considered. The theory demonstrates
how the widely used technique of variance inflation acts to stabilize the
filter, and hence leads to asymptotic accuracy
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