Spectral properties of the three-dimensional Hubbard model

We present momentum resolved single-particle spectra for the three-dimensional Hubbard model for the paramagnetic and antiferromagnetically ordered phase obtained within the dynamical cluster approximation. The effective cluster problem is solved by continuous-time Quantum Monte Carlo simulations. The absence of a time discretization error and the ability to perform Monte Carlo measurements directly in Matsubara frequencies enable us to analytically continue the self-energies by maximum entropy, which is essential to obtain momentum resolved spectral functions for the N'eel state. We investigate the dependence on temperature and interaction strength and the effect of magnetic frustration introduced by a next-nearest neighbor hopping. One particular question we address here is the influence of the frustrating interaction on the metal insulator transition of the three-dimensional Hubbard model.Comment: 16 pages, 14 figure

Casimir Invariants for Systems Undergoing Collective Motion

Dicke states are states of a collection of particles which have been under active investigation for several reasons. One reason is that the decay rates of these states can be quite different from a set of independently evolving particles. Another reason is that a particular class of these states are decoherence-free or noiseless with respect to a set of errors. These noiseless states, or more generally subsystems, can avoid certain types of errors in quantum information processing devices. Here we provide a method for calculating invariants of systems of particles undergoing collective motions. These invariants can be used to determine a complete set of commuting observables for a class of Dicke states as well as identify possible logical operations for decoherence-free/noiseless subsystems. Our method is quite general and provides results for cases where the constituent particles have more than two internal states.Comment: 5 page

Gene expression in bryozoan larvae suggest a fundamental importance of pre-patterned blastemic cells in the bryozoan life-cycle

<p>Abstract</p> <p>Background</p> <p>Bryozoa is a clade of aquatic protostomes. The bryozoan life cycle typically comprises a larval stage, which metamorphoses into a sessile adult that proliferates by asexual budding to form colonies. The homology of bryozoan larvae with other protostome larvae is enigmatic. Bryozoan larvae exhibit blastemic tissues that contribute to build the adult during morphogenesis. However, it remains unclear if the cells of these tissues are pre-determined according to their future fate or if the cells are undifferentiated, pluripotent stem cells. Gene expression studies can help to identify molecular patterning of larval and adult tissues and enlighten the evolution of bryozoan life cycle stages.</p> <p>Results</p> <p>We investigated the spatial expression of 13 developmental genes in the larval stage of the gymnolaemate bryozoan <it>Bugula neritina</it>. We found most genes expressed in discrete regions in larval blastemic tissues that form definitive components of the adult body plan. Only two of the 13 genes, <it>BnTropomyosin </it>and <it>BnFoxAB</it>, were exclusively expressed in larval tissues that are discarded during metamorphosis.</p> <p>Conclusions</p> <p>Our results suggest that the larval blastemas in <it>Bugula </it>are pre-patterned according to their future fate in the adult. The gene expression patterns indicate that some of the bryozoan blastemas can be interpreted to correspond to homologous adult tissues of other animals. This study challenges an earlier proposed view that metazoan larvae share homologous undifferentiated "set-aside cells", and instead points to an independent origin of the bryozoan larval stage with respect to other lophotrochozoans.</p

A generic physical vulnerability model for floods: review and concept for data-scarce regions

The use of different methods for physical flood vulnerability assessment has evolved over time, from traditional single-parameter stage–damage curves to multi-parameter approaches such as multivariate or indicator-based models. However, despite the extensive implementation of these models in flood risk assessment globally, a considerable gap remains in their applicability to data-scarce regions. Considering that these regions are mostly areas with a limited capacity to cope with disasters, there is an essential need for assessing the physical vulnerability of the built environment and contributing to an improvement of flood risk reduction. To close this gap, we propose linking approaches with reduced data requirements, such as vulnerability indicators (integrating major damage drivers) and damage grades (integrating frequently observed damage patterns). First, we present a review of current studies of physical vulnerability indicators and flood damage models comprised of stage–damage curves and the multivariate methods that have been applied to predict damage grades. Second, we propose a new conceptual framework for assessing the physical vulnerability of buildings exposed to flood hazards that has been specifically tailored for use in data-scarce regions. This framework is operationalized in three steps: (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking resulting index classes with damage patterns, utilizing a synthetic “what-if” analysis. The new framework is a first step for enhancing flood damage prediction to support risk reduction in data-scarce regions. It addresses selected gaps in the literature by extending the application of the vulnerability index for damage grade prediction through the use of a synthetic multi-parameter approach. The framework can be adapted to different data-scarce regions and allows for integrating possible modifications to damage drivers and damage grades

Analytic Continuation of Quantum Monte Carlo Data by Stochastic Analytical Inference

We present an algorithm for the analytic continuation of imaginary-time quantum Monte Carlo data which is strictly based on principles of Bayesian statistical inference. Within this framework we are able to obtain an explicit expression for the calculation of a weighted average over possible energy spectra, which can be evaluated by standard Monte Carlo simulations, yielding as by-product also the distribution function as function of the regularization parameter. Our algorithm thus avoids the usual ad-hoc assumptions introduced in similar algortihms to fix the regularization parameter. We apply the algorithm to imaginary-time quantum Monte Carlo data and compare the resulting energy spectra with those from a standard maximum entropy calculation

Studies on the double alkylation of 2,2-disubstituted-1,3-dithiacycloalkane-S-oxides: synthesis of tertiary thiol derivatives

Di-alkylation of 2,2-dimethyl-1,3-dithiacycloalkane-S-oxides has been achieved allowing the synthesis of two tertiary thiol centres. The diastereoisomers of the mono-alkylated products have been shown to react at different rates. The X-ray crystal structures of three substituted dithiane-S-oxides have been determined, and the conversion of the dialkylated products into cyclic disulfide derivatives of tertiary thiols (1,2-dithiolanes) has been achieved by treatment with acid