Magnetic moments of octet baryons, angular momenta of quarks and sea antiquark polarizations

One can determine antiquark polarizations in proton using the information from deep inelastic scattering, $\beta$ decays of baryons, orbital angular momenta of quarks, as well as their integrated magnetic distributions. The last quantities were determined previously by us performing a fit to magnetic moments of baryon octet. However, because of the SU(3) symmetry our results depend on two parameters. The quantity $\Gamma_{V}$, measured recently in a COMPASS experiment, gives the relation between these parameters. We can fix the last unknown parameter using the ratio of up and down quark magnetic moments which one can get from the fit to radiative vector meson decays. We calculate antiquark polarizations with the orbital momenta of valence quarks that follow from lattice calculations. The value of difference for up and down antiquark polarizations obtained in our calculations is consistent with the result obtained in a HERMES experiment.Comment: 14 pages, latex, 5 eps figure

Subnanosecond Fluctuations in Low-Barrier Nanomagnets

Fast magnetic fluctuations due to thermal torques have useful technological functionality ranging from cryptography to probabilistic computing. The characteristic time of fluctuations in typical uniaxial anisotropy magnets studied so far is bounded from below by the well-known energy relaxation mechanism. This time scales as $\alpha^{-1}$, where $\alpha$ parameterizes the strength of dissipative processes. Here, we theoretically analyze the fluctuating dynamics in easy-plane and antiferromagnetically coupled nanomagnets. We find in such magnets, the dynamics are strongly influenced by fluctuating intrinsic fields, which give rise to an additional dephasing-type mechanism for washing out correlations. In particular, we establish two time scales for characterizing fluctuations (i) the average time for a nanomagnet to reverse|which for the experimentally relevant regime of low damping is governed primarily by dephasing and becomes independent of $\alpha$, (ii) the time scale for memory loss of a single nanomagnet|which scales as $\alpha^{-1/3}$ and is governed by a combination of energy dissipation and dephasing mechanism. For typical experimentally accessible values of intrinsic fields, the resultant thermal-fluctuation rate is increased by multiple orders of magnitude when compared with the bound set solely by the energy relaxation mechanism in uniaxial magnets. This could lead to higher operating speeds of emerging devices exploiting magnetic fluctuations

On the maximal number of real embeddings of minimally rigid graphs in R2\mathbb{R}^2, R3\mathbb{R}^3 and S2S^2

Rigidity theory studies the properties of graphs that can have rigid embeddings in a euclidean space $\mathbb{R}^d$ or on a sphere and which in addition satisfy certain edge length constraints. One of the major open problems in this field is to determine lower and upper bounds on the number of realizations with respect to a given number of vertices. This problem is closely related to the classification of rigid graphs according to their maximal number of real embeddings. In this paper, we are interested in finding edge lengths that can maximize the number of real embeddings of minimally rigid graphs in the plane, space, and on the sphere. We use algebraic formulations to provide upper bounds. To find values of the parameters that lead to graphs with a large number of real realizations, possibly attaining the (algebraic) upper bounds, we use some standard heuristics and we also develop a new method inspired by coupler curves. We apply this new method to obtain embeddings in $\mathbb{R}^3$. One of its main novelties is that it allows us to sample efficiently from a larger number of parameters by selecting only a subset of them at each iteration. Our results include a full classification of the 7-vertex graphs according to their maximal numbers of real embeddings in the cases of the embeddings in $\mathbb{R}^2$ and $\mathbb{R}^3$, while in the case of $S^2$ we achieve this classification for all 6-vertex graphs. Additionally, by increasing the number of embeddings of selected graphs, we improve the previously known asymptotic lower bound on the maximum number of realizations. The methods and the results concerning the spatial embeddings are part of the proceedings of ISSAC 2018 (Bartzos et al, 2018)

Disentangling causal webs in the brain using functional Magnetic Resonance Imaging: A review of current approaches

In the past two decades, functional Magnetic Resonance Imaging has been used to relate neuronal network activity to cognitive processing and behaviour. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this work, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, LiNGAM, Patel's Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area

Data Mining the SDSS SkyServer Database

An earlier paper (Szalay et. al. "Designing and Mining MultiTerabyte Astronomy Archives: The Sloan Digital Sky Survey," ACM SIGMOD 2000) described the Sloan Digital Sky Survey's (SDSS) data management needs by defining twenty database queries and twelve data visualization tasks that a good data management system should support. We built a database and interfaces to support both the query load and also a website for ad-hoc access. This paper reports on the database design, describes the data loading pipeline, and reports on the query implementation and performance. The queries typically translated to a single SQL statement. Most queries run in less than 20 seconds, allowing scientists to interactively explore the database. This paper is an in-depth tour of those queries. Readers should first have studied the companion overview paper Szalay et. al. "The SDSS SkyServer, Public Access to the Sloan Digital Sky Server Data" ACM SIGMOND 2002.Comment: 40 pages, Original source is at http://research.microsoft.com/~gray/Papers/MSR_TR_O2_01_20_queries.do

Measurement-based modelling and validation of PV systems

This paper presents the analysis and results of modelling of various photovoltaic (PV) systems. Two general models are discussed and presented: an analytical model and an equivalent circuit model, both formulated for main PV technologies currently available on the market. Analytical model does not require any PV system specific input data or parameter, and is formulated as a generic performance model of a considered PV technology. Equivalent circuit model, however, requires specific input data and adjustment of the model parameters, in order to provide an accurate representation of a modelled PV system. The paper provides direct comparison of models based on manufacturer’s specification data and available measurements, as well as the discussion of obtained results

The 27-day versus 13.5-day variations in the solar Lyman-alpha radiation and the radio wave absorption in the lower ionosphere over Europe

In order to clarify the question of solar periods in absorption, the pattern was studied of the solar Lyman-alpha radiation (the principal ionizing agent of the lower ionosphere) and of the radio wave absorption at five widely spaced places in Europe. When the solar Lyman-alpha flux variability is very well developed, then it dominates in the lower ionospheric variability. The most pronounced Lyman-alpha variation on time scale day-month is the solar rotation variation (about 27 days). When the Lyman-alpha variability is developed rather poorly, as it is typical for periods dominated by the 13.5 day variability, then the lower ionospheric variability appears to be dominated by variations of meteorological origin. The conclusions hold for all five widely spaced placed in Europe

Dynamics of conduction blocks in a model of paced cardiac tissue

We study numerically the dynamics of conduction blocks using a detailed electrophysiological model. We find that this dynamics depends critically on the size of the paced region. Small pacing regions lead to stationary conduction blocks while larger pacing regions can lead to conduction blocks that travel periodically towards the pacing region. We show that this size-dependence dynamics can lead to a novel arrhythmogenic mechanism. Furthermore, we show that the essential phenomena can be captured in a much simpler coupled-map model.Comment: 8 pages 6 figure