High resolution angle-resolved photoemission measurements have been carried out on transition metal dichalcogenide PdTe2 that is a superconductor with a Tc at 1.7 K. Combined with theoretical calculations, we have discovered for the first time the existence of topologically nontrivial surface state with Dirac cone in PbTe2 superconductor. It is located at the Brillouin zone center and possesses helical spin texture. Distinct from the usual three-dimensional topological insulators where the Dirac cone of the surface state lies at the Fermi level, the Dirac point of the surface state in PdTe2 lies deep below the Fermi level at ~1.75 eV binding energy and is well separated from the bulk states. The identification of topological surface state in PdTe2 superconductor deep below the Fermi level provides a unique system to explore for new phenomena and properties and opens a door for finding new topological materials in transition metal chalcogenides.
We consider a fundamental algorithmic question in spectral graph theory: Compute a spectral sparsifier of random-walk matrix-polynomial $$L_alpha(G)=D-sum_{r=1}^dalpha_rD(D^{-1}A)^r$$ where $A$ is the adjacency matrix of a weighted, undirected graph, $D$ is the diagonal matrix of weighted degrees, and $alpha=(alpha_1...alpha_d)$ are nonnegative coefficients with $sum_{r=1}^dalpha_r=1$. Recall that $D^{-1}A$ is the transition matrix of random walks on the graph. The sparsification of $L_alpha(G)$ appears to be algorithmically challenging as the matrix power $(D^{-1}A)^r$ is defined by all paths of length $r$, whose precise calculation would be prohibitively expensive. In this paper, we develop the first nearly linear time algorithm for this sparsification problem: For any $G$ with $n$ vertices and $m$ edges, $d$ coefficients $alpha$, and $epsilon > 0$, our algorithm runs in time $O(d^2mlog^2n/epsilon^{2})$ to construct a Laplacian matrix $tilde{L}=D-tilde{A}$ with $O(nlog n/epsilon^{2})$ non-zeros such that $tilde{L}approx_{epsilon}L_alpha(G)$. Matrix polynomials arise in mathematical analysis of matrix functions as well as numerical solutions of matrix equations. Our work is particularly motivated by the algorithmic problems for speeding up the classic Newtons method in applications such as computing the inverse square-root of the precision matrix of a Gaussian random field, as well as computing the $q$th-root transition (for $qgeq1$) in a time-reversible Markov model. The key algorithmic step for both applications is the construction of a spectral sparsifier of a constant degree random-walk matrix-polynomials introduced by Newtons method. Our algorithm can also be used to build efficient data structures for effective resistances for multi-step time-reversible Markov models, and we anticipate that it could be useful for other tasks in network analysis.
Empirical likelihood approach is one of non-parametric statistical methods, which is applied to the hypothesis testing or construction of confidence regions for pivotal unknown quantities. This method has been applied to the case of independent identically distributed random variables and second order stationary processes. In recent years, we observe heavy-tailed data in many fields. To model such data suitably, we consider symmetric scalar and multivariate $alpha$-stable linear processes generated by infinite variance innovation sequence. We use a Whittle likelihood type estimating function in the empirical likelihood ratio function and derive the asymptotic distribution of the empirical likelihood ratio statistic for $alpha$-stable linear processes. With the empirical likelihood statistic approach, the theory of estimation and testing for second order stationary processes is nicely extended to heavy-tailed data analyses, not straightforward, and applicable to a lot of financial statistical analyses.
In this paper, we propose a new approach, based on the so-called modulating functions to estimate the average velocity, the dispersion coefficient and the differentiation order in a space fractional advection dispersion equation. First, the average velocity and the dispersion coefficient are estimated by applying the modulating functions method, where the problem is transferred into solving a system of algebraic equations. Then, the modulating functions method combined with Newtons method is applied to estimate all three parameters simultaneously. Numerical results are presented with noisy measurements to show the effectiveness and the robustness of the proposed method.
The modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville fractional derivatives. First, a new fractional integration by parts formula involving the fractional derivative of a modulating function is given. Then, we apply this formula to a fractional order system, for which the fractional derivatives of the input and the output can be transferred into the ones of the modulating functions. By choosing a set of modulating functions, a linear system of algebraic equations is obtained. Hence, the unknown parameters of a fractional order system can be estimated by solving a linear system. Using this method, we do not need any initial values which are usually unknown and not equal to zero. Also we do not need to estimate the fractional derivatives of noisy output. Moreover, it is shown that the proposed estimators are robust against high frequency sinusoidal noises and the ones due to a class of stochastic processes. Finally, the efficiency and the stability of the proposed method is confirmed by some numerical simulations.
The two Higgs bi-doublet left-right symmetric model (2HBDM) as a simple extension of the minimal left-right symmetric model with a single Higgs bi-doublet is motivated to realize both spontaneous P and CP violation while consistent with the low energy phenomenology without significant fine tuning. By carefully investigating the Higgs potential of the model, we find that sizable CP-violating phases are allowed after the spontaneous symmetry breaking. The mass spectra of the extra scalars in the 2HBDM are significantly different from the ones in the minimal left-right symmetric model. In particular, we demonstrate in the decoupling limit when the right-handed gauge symmetry breaking scale is much higher than the electroweak scale, the 2HBDM decouples into general two Higgs doublet model (2HDM) with spontaneous CP violation and has rich induced sources of CP violation. We show that in the decoupling limit, it contains extra light Higgs bosons with masses around electroweak scale, which can be directly searched at the ongoing LHC and future ILC experiments.
Numerical causal derivative estimators from noisy data are essential for real time applications especially for control applications or fluid simulation so as to address the new paradigms in solid modeling and video compression. By using an analytical point of view due to Lanczos cite{C. Lanczos} to this causal case, we revisit $n^{th}$ order derivative estimators originally introduced within an algebraic framework by Mboup, Fliess and Join in cite{num,num0}. Thanks to a given noise level $delta$ and a well-suitable integration length window, we show that the derivative estimator error can be $mathcal{O}(delta ^{frac{q+1}{n+1+q}})$ where $q$ is the order of truncation of the Jacobi polynomial series expansion used. This so obtained bound helps us to choose the values of our parameter estimators. We show the efficiency of our method on some examples.
In this paper, we give estimators of the frequency, amplitude and phase of a noisy sinusoidal signal with time-varying amplitude by using the algebraic parametric techniques introduced by Fliess and Sira-Ramirez. We apply a similar strategy to estimate these parameters by using modulating functions method. The convergence of the noise error part due to a large class of noises is studied to show the robustness and the stability of these methods. We also show that the estimators obtained by modulating functions method are robust to large sampling period and to non zero-mean noises.
High quality single crystals of heavy Fermion CeCoIn5 superconductor have been grown by flux method with a typical size of (1~2)mm x (1~2)mm x ~0.1 mm. The single crystals are characterized by structural analysis from X-ray diffraction and Laue diffraction, as well as compositional analysis. Magnetic and electrical measurements on the single crystals show a sharp superconducting transition with a transition temperature at Tc(onset) ~ 2.3 K and a transition width of ~0.15 K. The resistivity of the CeCoIn5 crystal exhibits a hump at ~45 K which is typical of a heavy Fermion system. High resolution angle-resolved photoemission spectroscopy (ARPES) measurements of CeCoIn5 reveal clear Fermi surface sheets that are consistent with the band structure calculations when assuming itinerant Ce 4f electrons at low temperature. This work provides important information on the electronic structure of heavy Fermion CeCoIn5 superconductor. It also lays a foundation for further studies on the physical properties and superconducting mechanism of the heavy Fermion superconductors.
We calculate the shear viscosity of strongly coupled field theories dual to Gauss-Bonnet gravity at zero temperature with nonzero chemical potential. We find that the ratio of the shear viscosity over the entropy density is $1/4pi$, which is in accordance with the zero temperature limit of the ratio at nonzero temperatures. We also calculate the DC conductivity for this system at zero temperature and find that the real part of the DC conductivity vanishes up to a delta function, which is similar to the result in Einstein gravity. We show that at zero temperature, we can still have the conclusion that the shear viscosity is fully determined by the effective coupling of transverse gravitons in a kind of theories that the effective action of transverse gravitons can be written into a form of minimally coupled scalars with a deformed effective coupling.
