Geometric, electronic, and magnetic structure of Co2_2FeSi: Curie temperature and magnetic moment measurements and calculations

In this work a simple concept was used for a systematic search for new materials with high spin polarization. It is based on two semi-empirical models. Firstly, the Slater-Pauling rule was used for estimation of the magnetic moment. This model is well supported by electronic structure calculations. The second model was found particularly for Co$_2$ based Heusler compounds when comparing their magnetic properties. It turned out that these compounds exhibit seemingly a linear dependence of the Curie temperature as function of the magnetic moment. Stimulated by these models, Co$_2$FeSi was revisited. The compound was investigated in detail concerning its geometrical and magnetic structure by means of X-ray diffraction, X-ray absorption and M\"o\ss bauer spectroscopies as well as high and low temperature magnetometry. The measurements revealed that it is, currently, the material with the highest magnetic moment ($6\mu_B$) and Curie-temperature (1100K) in the classes of Heusler compounds as well as half-metallic ferromagnets. The experimental findings are supported by detailed electronic structure calculations

ELM—the database of eukaryotic linear motifs

Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instance

Axion dark matter search using arm cavity transmitted beams of gravitational wave detectors

Axion is a promising candidate for ultralight dark matter which may cause a polarization rotation of laser light. Recently, a new idea of probing the axion dark matter by optical linear cavities used in the arms of gravitational wave detectors has been proposed [Phys. Rev. Lett. 123, 111301 (2019)]. In this article, a realistic scheme of the axion dark matter search with the arm cavity transmission ports is revisited. Since photons detected by the transmission ports travel in the cavity for odd-number of times, the effect of axion dark matter on their phases is not cancelled out and the sensitivity at low-mass range is significantly improved compared to the search using reflection ports. We also take into account the stochastic nature of the axion field and the availability of the two detection ports in the gravitational wave detectors. The sensitivity to the axion-photon coupling, $g_{a\gamma}$, of the ground-based gravitational wave detector, such as Advanced LIGO, with 1-year observation is estimated to be $g_{a\gamma} \sim 3\times10^{-12}$ GeV$^{-1}$ below the axion mass of $10^{-15}$ eV, which improves upon the limit achieved by the CERN Axion Solar Telescope.Comment: 10 pages, 4 figure

Hierarchic Superposition Revisited

Many applications of automated deduction require reasoning in first-order logic modulo background theories, in particular some form of integer arithmetic. A major unsolved research challenge is to design theorem provers that are "reasonably complete" even in the presence of free function symbols ranging into a background theory sort. The hierarchic superposition calculus of Bachmair, Ganzinger, and Waldmann already supports such symbols, but, as we demonstrate, not optimally. This paper aims to rectify the situation by introducing a novel form of clause abstraction, a core component in the hierarchic superposition calculus for transforming clauses into a form needed for internal operation. We argue for the benefits of the resulting calculus and provide two new completeness results: one for the fragment where all background-sorted terms are ground and another one for a special case of linear (integer or rational) arithmetic as a background theory

Visser's Massive Gravity Bimetric Theory Revisited

A massive gravity theory was proposed by Visser in the late nineties. This theory, based on a backgroung metric $b_{\alpha \beta}$ and on an usual dynamical metric $g_{\alpha \beta}$ has the advantage of being free of ghosts as well as discontinuities present in other massive theories proposed in the past. In the present investigation, the equations of Visser's theory are revisited with a particular care on the related conservation laws.\ It will be shown that a multiplicative factor is missing in the graviton tensor originally derived by Visser, which has no incidence on the weak field approach but becomes important in the strong field regime when, for instance, cosmological applications are considered. In this case, contrary to some previous claims found in the literature, we conclude that a non-static background metric is required in order to obtain a solution able to mimic the $\Lambda$CDM cosmology.Comment: 10 pages - Accepted for publication in Physical Review

Faithfulness and learning hypergraphs from discrete distributions

The concepts of faithfulness and strong-faithfulness are important for statistical learning of graphical models. Graphs are not sufficient for describing the association structure of a discrete distribution. Hypergraphs representing hierarchical log-linear models are considered instead, and the concept of parametric (strong-) faithfulness with respect to a hypergraph is introduced. Strong-faithfulness ensures the existence of uniformly consistent parameter estimators and enables building uniformly consistent procedures for a hypergraph search. The strength of association in a discrete distribution can be quantified with various measures, leading to different concepts of strong-faithfulness. Lower and upper bounds for the proportions of distributions that do not satisfy strong-faithfulness are computed for different parameterizations and measures of association.Comment: 23 pages, 6 figure