Quantum Antiferromagnetism in Quasicrystals

The antiferromagnetic Heisenberg model is studied on a two-dimensional bipartite quasiperiodic lattice. The distribution of local staggered magnetic moments is determined on finite square approximants with up to 1393 sites, using the Stochastic Series Expansion Quantum Monte Carlo method. A non-trivial inhomogeneous ground state is found. For a given local coordination number, the values of the magnetic moments are spread out, reflecting the fact that no two sites in a quasicrystal are identical. A hierarchical structure in the values of the moments is observed which arises from the self-similarity of the quasiperiodic lattice. Furthermore, the computed spin structure factor shows antiferromagnetic modulations that can be measured in neutron scattering and nuclear magnetic resonance experiments. This generic model is a first step towards understanding magnetic quasicrystals such as the recently discovered Zn-Mg-Ho icosahedral structure.Comment: RevTex, 4 pages with 5 figure

Impurity assisted nanoscale localization of plasmonic excitations in graphene

The plasmon modes of pristine and impurity doped graphene are calculated, using a real-space theory which determines the non-local dielectric response within the random phase approximation. A full diagonalization of the polarization operator is performed, allowing the extraction of all its poles. It is demonstrated how impurities induce the formation of localized modes which are absent in pristine graphene. The dependence of the spatial modulations over few lattice sites and frequencies of the localized plasmons on the electronic filling and impurity strength is discussed. Furthermore, it is shown that the chemical potential and impurity strength can be tuned to control target features of the localized modes. These predictions can be tested by scanning tunneling microscopy experiments.Comment: 5 pages, 4 figure

Top transport in electroweak baryogenesis

In non-supersymmetric models of electroweak baryogenesis the top quark plays a crucial role. Its CP-violating source term can be calculated in the WKB approximation. We point out how to resolve certain discrepancies between computations starting from the Dirac equation and the Schwinger--Keldysh formalism. We also improve on the transport equations, keeping the W-scatterings at finite rate. We apply these results to a model with one Higgs doublet, augmented by dimension-6 operators, where our refinements lead to an increase in the baryon asymmetry by a factor of up to about 5.Comment: 17 pages, 3 figures, references adde

Neuroticism and conscientiousness respectively constrain and facilitate short-term plasticity within the working memory neural network

Individual differences in cognitive efficiency, particularly in relation to working memory (WM), have been associated both with personality dimensions that reflect enduring regularities in brain configuration, and with short-term neural plasticity, that reflects task-related changes in brain connectivity. To elucidate the relationship of these two divergent mechanisms, we tested the hypothesis that personality dimensions, which reflect enduring aspects of brain configuration, inform about the neurobiological framework within which short-term, task-related plasticity, as measured by effective connectivity, can be facilitated or constrained. As WM consistently engages the dorsolateral prefrontal (DLPFC), parietal (PAR), and anterior cingulate cortex (ACC), we specified a WM network model with bidirectional, ipsilateral, and contralateral connections between these regions from a functional magnetic resonance imaging dataset obtained from 40 healthy adults while performing the 3-back WM task. Task-related effective connectivity changes within this network were estimated using Dynamic Causal Modelling. Personality was evaluated along the major dimensions of Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Only two dimensions were relevant to task-dependent effective connectivity. Neuroticism and Conscientiousness respectively constrained and facilitated neuroplastic responses within the WM network. These results suggest individual differences in cognitive efficiency arise from the interplay between enduring and short-term plasticity in brain configuration

A revised chronostratigraphic framework for International Ocean Discovery Program Expedition 355 sites in Laxmi Basin, eastern Arabian Sea

AbstractInternational Ocean Discovery Program Expedition 355 drilled Sites U1456 and U1457 in Laxmi Basin (eastern Arabian Sea) to document the impact of the South Asian monsoon on weathering and erosion of the Himalaya. We revised the chronostratigraphic framework for these sites using a combination of biostratigraphy, magnetostratigraphy and strontium isotope stratigraphy. The sedimentary section at the two sites is similar and we divided it into six units bounded by unconformities or emplaced as a mass-transport deposit (MTD). Unit 1 underlies the MTD, and is of early–middle Miocene age at Site U1456 and early Paleocene age at Site U1457. An unconformity (U1) created by emplacement of the MTD (unit 2) during the late Miocene Epoch (at c. 9.83–9.69 Ma) separates units 1 and 2 and is identified by a marked change in lithology. Unit 3 consists of hemipelagic sediment with thin interbeds of graded sandstone of late Miocene age, separated from unit 4 by a second unconformity (U2) of 0.5–0.9 Myr duration. Unit 4 consists of upper Miocene interbedded mudstone and sandstone and hemipelagic chalk deposited between c. 8 and 6 Ma. A c. 1.4–1.6 Myr hiatus (U3) encompasses the Miocene–Pliocene boundary and separates unit 4 from unit 5. Unit 5 includes upper Pliocene – lower Pleistocene siliciclastic sediment that is separated from unit 6 by a c. 0.45 Myr hiatus (U4) in the lower Pleistocene sediments. Unit 6 includes a thick package of rapidly deposited Pleistocene sand and mud overlain by predominantly hemipelagic sediment deposited since c. 1.2 Ma

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data

QCD thermodynamics with continuum extrapolated Wilson fermions II

We continue our investigation of 2+1 flavor QCD thermodynamics using dynamical Wilson fermions in the fixed scale approach. Two additional pion masses, approximately 440 MeV and 285 MeV, are added to our previous work at 545 MeV. The simulations were performed at 3 or 4 lattice spacings at each pion mass. The renormalized chiral condensate, strange quark number susceptibility and Polyakov loop is obtained as a function of the temperature and we observe a decrease in the light chiral pseudo-critical temperature as the pion mass is lowered while the pseudo-critical temperature associated with the strange quark number susceptibility or the Polyakov loop is only mildly sensitive to the pion mass. These findings are in agreement with previous continuum results obtained in the staggered formulation.Comment: 19 pages, 13 figures, published versio