Correlation effects and orbital magnetism of Co clusters

Recent experiments on isolated Co clusters have shown huge orbital magnetic moments in comparison with their bulk and surface counterparts. These clusters hence provide the unique possibility to study the evolution of the orbital magnetic moment with respect to the cluster size and how competing interactions contribute to the quenching of orbital magnetism. We investigate here different theoretical methods to calculate the spin and orbital moments of Co clusters, and assess the performances of the methods in comparison with experiments. It is shown that density functional theory in conventional local density or generalized gradient approximations, or even with a hybrid functional, severely underestimates the orbital moment. As natural extensions/corrections we considered the orbital polarization correction, the LDA+U approximation as well as the LDA+DMFT method. Our theory shows that of the considered methods, only the LDA+DMFT method provides orbital moments in agreement with experiment, thus emphasizing the importance of dynamic correlations effects for determining fundamental magnetic properties of magnets in the nano-size regime

Inferring Binding Energies from Selected Binding Sites

We employ a biophysical model that accounts for the non-linear relationship between binding energy and the statistics of selected binding sites. The model includes the chemical potential of the transcription factor, non-specific binding affinity of the protein for DNA, as well as sequence-specific parameters that may include non-independent contributions of bases to the interaction. We obtain maximum likelihood estimates for all of the parameters and compare the results to standard probabilistic methods of parameter estimation. On simulated data, where the true energy model is known and samples are generated with a variety of parameter values, we show that our method returns much more accurate estimates of the true parameters and much better predictions of the selected binding site distributions. We also introduce a new high-throughput SELEX (HT-SELEX) procedure to determine the binding specificity of a transcription factor in which the initial randomized library and the selected sites are sequenced with next generation methods that return hundreds of thousands of sites. We show that after a single round of selection our method can estimate binding parameters that give very good fits to the selected site distributions, much better than standard motif identification algorithms

Analytic continuation by averaging Pade approximants

Contains fulltext : 156887.pdf (preprint version ) (Open Access

Exchange parameters of strongly correlated materials: Extraction from spin-polarized density functional theory plus dynamical mean-field theory

Contains fulltext : 144939.pdf (publisher's version ) (Open Access

A Perspective on Molecular Structure and Bond-Breaking in Radiation Damage in Serial Femtosecond Crystallography

X-ray free-electron lasers (XFELs) have a unique capability for time-resolved studies of protein dynamics and conformational changes on femto- and pico-second time scales. The extreme intensity of X-ray pulses can potentially cause significant modifications to the sample structure during exposure. Successful time-resolved XFEL crystallography depends on the unambiguous interpretation of the protein dynamics of interest from the effects of radiation damage. Proteins containing relatively heavy elements, such as sulfur or metals, have a higher risk for radiation damage. In metaloenzymes, for example, the dynamics of interest usually occur at the metal centers, which are also hotspots for damage due to the higher atomic number of the elements they contain. An ongoing challenge with such local damage is to understand the residual bonding in these locally ionized systems and bond-breaking dynamics. Here, we present a perspective on radiation damage in XFEL experiments with a particular focus on the impacts for time-resolved protein crystallography. We discuss recent experimental and modelling results of bond-breaking and ion motion at disulfide bonding sites in protein crystals

Modeling Timed Concurrent Systems

Abstract. Timed concurrent systems are widely used in concurrent and distributed real-time software, modeling of hybrid systems, design of hardware systems (using hardware description languages), discrete-event simulation, and modeling of communication networks. They consist of concurrent components that communicate using timed signals, that is, sets of (semantically) time-stamped events. The denotational semantics of such systems is traditionally formulated in a metric space, wherein causal components are modeled as contracting functions. We show that this formulation excessively restricts the models of time that can be used. In particular, it cannot handle super-dense time, commonly used in hardware description languages and hybrid systems modeling, finite time lines, and time with no origin. Moreover, if we admit continuoustime and mixed signals (essential for hybrid systems modeling) or certain Zeno signals, then causality is no longer equivalent to its formalization in terms of contracting functions. In this paper, we offer an alternative semantic framework using a generalized ultrametric that overcomes these limitations.