Fock-state dynamics in Raman photoassociation of Bose-Einstein condensates

By stochastic modeling of the process of Raman photoassociation of Bose-Einstein condensates, we show that, the farther the initial quantum state is from a coherent state, the farther the one-dimensional predictions are from those of the commonly used zero-dimensional approach. We compare the dynamics of condensates, initially in different quantum states, finding that, even when the quantum prediction for an initial coherent state is relatively close to the Gross-Pitaevskii prediction, an initial Fock state gives qualitatively different predictions. We also show that this difference is not present in a single-mode type of model, but that the quantum statistics assume a more important role as the dimensionality of the model is increased. This contrasting behavior in different dimensions, well known with critical phenomena in statistical mechanics, makes itself plainly visible here in a mesoscopic system and is a strong demonstration of the need to consider physically realistic models of interacting condensates.

A parallel implementation of the lattice solid model for the simulation of rock mechanics and earthquake dynamics

The Lattice Solid Model has been used successfully as a virtual laboratory to simulate fracturing of rocks, the dynamics of faults, earthquakes and gouge processes. However, results from those simulations show that in order to make the next step towards more realistic experiments it will be necessary to use models containing a significantly larger number of particles than current models. Thus, those simulations will require a greatly increased amount of computational resources. Whereas the computing power provided by single processors can be expected to increase according to Moore's law, i.e., to double every 18-24 months, parallel computers can provide significantly larger computing power today. In order to make this computing power available for the simulation of the microphysics of earthquakes, a parallel version of the Lattice Solid Model has been implemented. Benchmarks using large models with several millions of particles have shown that the parallel implementation of the Lattice Solid Model can achieve a high parallel-efficiency of about 80% for large numbers of processors on different computer architectures.

Comparisons of diffusive and viscous contributions to transport coefficients of light gases in single-walled carbon nanotubes

We examine here the relative importance of different contributions to transport of light gases in single walled carbon nanotubes, using methane and hydrogen as examples. Transport coefficients at 298 K are determined using molecular dynamics simulation with atomistic models of the nanotube wall, from which the diffusive and viscous contributions are resolved using a recent approach that provides an explicit expression for the latter. We also exploit an exact theory for the transport of Lennard-Jones fluids at low density considering diffuse reflection at the tube wall, thereby permitting the estimation of Maxwell coefficients for the wall reflection. It is found that reflection from the carbon nanotube wall is nearly specular, as a result of which slip flow dominates, and the viscous contribution is small in comparison, even for a tube as large as 8.1 nm in diameter. The reflection coefficient for hydrogen is 3-6 times as large as that for methane in tubes of 1.36 nm diameter, indicating less specular reflection for hydrogen and greater sensitivity to atomic detail of the surface. This reconciles results showing that transport coefficients for hydrogen and methane, obtained in simulation, are comparable in tubes of this size. With increase in adsorbate density, the reflection coefficient increases, suggesting that adsorbate interactions near the wall serve to roughen the local potential energy landscape perceived by fluid molecules.

Enhancement of hydrogen physisorption on single-walled carbon nanotubes resulting from defects created by carbon bombardment

The defect effect on hydrogen adsorption on single-walled carbon nanotubes (SWNTs) has been studied by using extensive molecular dynamics simulations and density functional theory (DFT) calculations. It indicates that the defects created on the exterior wall of the SWNTs by bombarding the tube wall with carbon atoms and C-2 dimers at a collision energy of 20 eV can enhance the hydrogen adsorption potential of the SWNTs substantially. The average adsorption energy for a H-2 molecule adsorbed on the exterior wall of a defected (10,10) SWNT is similar to 150 meV, while that for a H-2 molecule adsorbed on the exterior wall of a perfect (10,10) SWNT is similar to 104 meV. The H-2 sticking coefficient is very sensitive to temperature, and has a maximum value around 70 to 90 K. The electron density contours, the local density of states, and the electron transfers obtained from the DFT calculations clearly indicate that the H-2 molecules are all physisorbed on the SWNTs. At temperatures above 200 K, most of the H-2 molecules adsorbed on the perfect SWNT are soon desorbed, but the H-2 molecules can still remain on the defected SWNTs at 300 K. The detailed processes of H-2 molecules adsorbing on and desorbing from the (10,10) SWNTs are demonstrated.

Costs of learning: the dynamics of mixed-prey exploitation by silver perch, Bidyanus bidyanus (Mitchell, 1838)

Although generalist predators have been reported to forage less efficiently than specialists, there is little information on the extent to which learning can improve the efficiency of mixed-prey foraging. Repeated exposure of silver perch to mixed prey (pelagic Artemia and benthic Chironomus larvae) led to substantial fluctuations in reward rate over relatively long (20-day) timescales. When perch that were familiar with a single prey type were offered two prey types simultaneously, the rate at which they captured both familiar and unfamiliar prey dropped progressively over succeeding trials. This result was not predicted by simple learning paradigms, but could be explained in terms of an interaction between learning and attention. Between-trial patterns in overall intake were complex and differed between the two prey types, but were unaffected by previous prey specialization. However, patterns of prey priority (i.e. the prey type that was preferred at the start of a trial) did vary with previous prey training. All groups of fish converged on the most profitable prey type (chironomids), but this process took 15-20 trials. In contrast, fish offered a single prey type reached asymptotic intake rates within five trials and retained high capture abilities for at least 5 weeks. Learning and memory allow fish to maximize foraging efficiency on patches of a single prey type. However, when foragers are faced with mixed prey populations, cognitive constraints associated with divided attention may impair efficiency, and this impairment can be exacerbated by experience. (c) 2005 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

First-principles quantum dynamics in interacting Bose gases II: stochastic gauges

First principles simulations of the quantum dynamics of interacting Bose gases using the stochastic gauge representation are analysed. In a companion paper, we showed how the positive-P representation can be applied to these problems using stochastic differential equations. That method, however, is limited by increased sampling error as time evolves. Here, we show how the sampling error can be greatly reduced and the simulation time significantly extended using stochastic gauges. In particular, local stochastic gauges (a subset) are investigated. Improvements are confirmed in numerical calculations of single-, double- and multi-mode systems in the weak-mode coupling regime. Convergence issues are investigated, including the recognition of two modes by which stochastic equations produced by phase-space methods in general can diverge: movable singularities and a noise-weight relationship. The example calculated here displays wave-like behaviour in spatial correlation functions propagating in a uniform 1D gas after a sudden change in the coupling constant. This could in principle be tested experimentally using Feshbach resonance methods.

Molecular dynamics study of MscL interactions with a curved lipid bilayer

Mechanosensitivity is a ubiquitous sensory mechanism found in living organisms. The simplest known mechanotransducing mechanism is found in bacteria in the form of the mechanosensitive membrane channel of large conductance, MscL. This channel has been studied extensively using a variety of methods at a functional and structural level. The channel is gated by membrane tension in the lipid bilayer alone. It serves as a safety valve protecting bacterial cells against hypoosmotic shock. MscL of Escherichia coli embedded in bilayers composed of asymmetric amounts of single-tailed and double-tailed lipids has been shown to gate spontaneously, even in the absence of membrane tension. To gain insight into the effect of the lipid membrane composition and geometry on MscL structure, a fully solvated, all-atom model of MscL in a stress-free curved bilayer composed of double- and single-tailed lipids was studied using a 9.5-ns molecular dynamics simulation. The bilayer was modeled as a domed structure accommodating the asymmetric composition of the monolayers. During the course of the simulation a spontaneous restructuring of the periplasmic loops occurred, leading to interactions between one of the loops and phospholipid headgroups. Previous experimental studies of the role of the loops agree with the observation that opening starts with a restructuring of the periplasmic loop, suggesting an effect of the curved bilayer. Because of limited resources, only one simulation of the large system was performed. However, the results obtained suggest that through the geometry and composition of the bilayer the protein structure can be affected even on short timescales.

Position information but not force information is used in adapting to changes in environmental dynamics

This study investigated how movement error is evaluated and used to change feedforward commands following a change in the environmental dynamics. In particular, we addressed the question of whether only position-error information is used or whether information about the force-field direction can also be used for rapid adaptation to changes in the environmental dynamics. Subjects learned to move in a position-dependent force field (PF) with a parabolic profile and the dynamics of a negative spring, which produced lateral force to the left of the target hand path. They adapted very rapidly, dramatically reducing lateral error after a single trial. Several times during training, the strength of the PF was unexpectedly doubled (PF2) for two trials. This again created a large leftward deviation, which was greatly reduced on the second PF2 trial, and an aftereffect when the force field subsequently returned to its original strength. The aftereffect was abolished if the second PF2 trial was replaced by an oppositely directed velocity-dependent force field (VF). During subsequent training in the VF, immediately after having adapted to the PF, subjects applied a force that assisted the force field for similar to 15 trials, indicating that they did not use information about the force-field direction. We concluded that the CNS uses only the position error for updating the internal model of the environmental dynamics and modifying feedforward commands. Although this strategy is not necessarily optimal, it may be the most reliable strategy for iterative improvement in performance.

The dynamics of matrix momentum

We analyse the matrix momentum algorithm, which provides an efficient approximation to on-line Newton's method, by extending a recent statistical mechanics framework to include second order algorithms. We study the efficacy of this method when the Hessian is available and also consider a practical implementation which uses a single example estimate of the Hessian. The method is shown to provide excellent asymptotic performance, although the single example implementation is sensitive to the choice of training parameters. We conjecture that matrix momentum could provide efficient matrix inversion for other second order algorithms.

Structure and dynamics of multiple cationic vectors-siRNA complexation by all-atomic molecular dynamics simulations

Understanding the molecular mechanism of gene condensation is a key component to rationalizing gene delivery phenomena, including functional properties such as the stability of the gene-vector complex and the intracellular release of the gene. In this work, we adopt an atomistic molecular dynamics simulation approach to study the complexation of short strand duplex RNA with four cationic carrier systems of varying charge and surface topology at different charge ratios. At lower charge ratios, polymers bind quite effectively to siRNA, while at high charge ratios, the complexes are saturated and there are free polymers that are unable to associate with RNA. We also observed reduced fluctuations in RNA structures when complexed with multiple polymers in solution as compared to both free siRNA in water and the single polymer complexes. These novel simulations provide a much better understanding of key mechanistic aspects of gene-polycation complexation and thereby advance progress toward rational design of nonviral gene delivery systems.

HLA-DP2 binding prediction by molecular dynamics simulations

Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

The spatial distribution and temporal dynamics of brain regions activated during the perception of object and non-object patterns

Both animal and human studies suggest that the efficiency with which we are able to grasp objects is attributable to a repertoire of motor signals derived directly from vision. This is in general agreement with the long-held belief that the automatic generation of motor signals by the perception of objects is based on the actions they afford. In this study, we used magnetoencephalography (MEG) to determine the spatial distribution and temporal dynamics of brain regions activated during passive viewing of object and non-object targets that varied in the extent to which they afforded a grasping action. Synthetic Aperture Magnetometry (SAM) was used to localize task-related oscillatory power changes within specific frequency bands, and the time course of activity within given regions-of-interest was determined by calculating time-frequency plots using a Morlet wavelet transform. Both single subject and group-averaged data on the spatial distribution of brain activity are presented. We show that: (i) significant reductions in 10-25 Hz activity within extrastriate cortex, occipito-temporal cortex, sensori-motor cortex and cerebellum were evident with passive viewing of both objects and non-objects; and (ii) reductions in oscillatory activity within the posterior part of the superior parietal cortex (area Ba7) were only evident with the perception of objects. Assuming that focal reductions in low-frequency oscillations (< 30 Hz) reflect areas of heightened neural activity, we conclude that: (i) activity within a network of brain areas, including the sensori-motor cortex, is not critically dependent on stimulus type and may reflect general changes in visual attention; and (ii) the posterior part of the superior parietal cortex, area Ba7, is activated preferentially by objects and may play a role in computations related to grasping. © 2006 Elsevier Inc. All rights reserved.

Mechanisms of heat and mass transfer to and from single drops freely-suspended in an air stream

A specially-designed vertical wind tunnel was used to freely suspend individual liquid drops of 5 mm initial diameter to investigate drop dynamics, terminal velocity and heat and mass transfer rates. Droplets of distilled, de-ionised water, n-propanol, iso-butanol, monoethanolamine and heptane were studied over a temperature range of 50oC to 82oC. The effects of substances that may provide drop surface rigidity (e.g. surface active agents, binders and polymers) on mass transfer rates were investigated by doping distilled de-ionised water drops with sodium di-octyl sulfo-succinate surfactant. Mass transfer rates decreased with reduced drop oscillation as a result of surfactant addition, confirming the importance of droplet surface instability. Rigid naphthalene spheres and drops which formed a skin were also studied; the results confirmed the reduced transfer rates in the absence of drop fluidity. Following consideration of fundamental drop dynamics in air and experimental results from this study, a novel dimensionless group, the Oteng-Attakora, (OT), number was included in the mass transfer equation to account for droplet surface behaviour and for prediction of heat and mass transfer rates from single drops which exhibit surface instability at Re>=500. The OT number and the modified mass transfer equation are respectively: OT=(ava2/d).de1.5(d/) Sh = 2 + 0.02OT0.15Re0.88Sc0.33 Under all conditions drop terminal velocity increased linearly with the square root of drop diameter and the drag coefficient was 1. The data were correlated with a modified equation by Finlay as follows: CD=0.237.((Re/P0.13)1.55(1/We.P0.13) The relevance of the new model to practical evaporative spray processes is discussed.

An investigation into the nature, determinants, and dynamics of service quality expectations

On the basis of a review of the substantive quality and service marketing literature current knowledge regarding service quality expectations was found either absent or deficient. The phenomenon is of increasing importance to both marketing researchers and management and was therefore judged worthy of scholarly consideration. Because the service quality literature was insufficiently rich when embarking on the thesis three basic research issues were considered namely the nature, determinants, and dynamics of service quality expectations. These issues were first conceptually and then qualitatively explored. This process generated research hypotheses mainly relating to a model which were subsequently tested through a series of empirical investigations using questionnaire data from field studies in a single context. The results were internally consistent and strongly supported the main research hypotheses. It was found that service quality expectations can be meaningfully described in terms of generic/service-specific, intangible/tangible, and process/outcome categories. Service-specific quality expectations were also shown to be determined by generic service quality expectations, demographic variables, personal values, psychological needs, general service sophistication, service-specific sophistication, purchase motives, and service-specific information when treating service class involvement as an exogenous variable. Subjects who had previously not directly experienced a particular service were additionally found to revise their expectations of quality when exposed to the service with change being driven by a sub-set of identified determinants.

Oscillatory dynamics in the perception of pain investigated using magnetoencephalography

This thesis investigates changes in the oscillatory dynamics in key areas of the pain matrix during different modalities of pain. Gamma oscillations were seen in the primary somatosensory cortex in response to somatic electrical stimulation at painful and non-painful intensities. The strength of the gamma oscillations was found to relate to the intensity of the stimulus. Gamma oscillations were not seen during distal oesophageal electrical stimulation or the cold pressor test. Gamma oscillations were not seen in all participants during somatic electrical stimulation, however clear evoked responses from SI were seen in everyone. During a train of electrical pulses to the median nerve and the digit, a decrease in the frequency of the gamma oscillations was seen across the duration of the train. During a train of electrical stimuli to the median nerve and the digit, gamma oscillations were seen at ~20-100ms following stimulus onset and at frequencies between 30-100Hz. This gamma response was found to have a strong evoked component. Following a single electrical pulse to the digit, gamma oscillations were seen at 100-250ms and between 60-95Hz and were not temporally coincident with the main components of the evoked response. These results suggest that gamma oscillations may have an important role in encoding different aspects of sensory stimuli within their characteristics such as strength and frequency. These findings help to elucidate how somatic stimuli are processed within the cortex which in turn may be used to understand abnormal cases of somatosensory processing.