Scanning Tunneling Spectroscopic Studies of the Low-Energy Quasiparticle Excitations in Cuprate Superconductors

We report scanning tunneling spectroscopic (STS) studies of the low-energy quasiparticle excitations of cuprate superconductors as a function of magnetic field and doping level. Our studies suggest that the origin of the pseudogap (PG) is associated with competing orders (COs), and that the occurrence (absence) of PG above the superconducting (SC) transition T_c is associated with a CO energy Δ_(CO) larger (smaller) than the SC gap Δ_(SC). Moreover, the spatial homogeneity of Δ_(SC) and Δ_(CO) depends on the type of disorder in different cuprates: For optimally and under-doped YBa_2Cu_3O_(7−δ) (Y-123), we find that Δ_(SC) < Δ_(CO) and that both Δ_(SC) and Δ(CO) exhibit long-range spatial homogeneity, in contrast to the highly inhomogeneous STS in Bi_2Sr_2CaCu_2O_(8+x) (Bi-2212). We attribute this contrast to the stoichiometric cations and ordered apical oxygen in Y-123, which differs from the non-stoichiometric Bi-to-Sr ratio in Bi-2212 with disordered Sr and apical oxygen in the SrO planes. For Ca-doped Y-123, the substitution of Y by Ca contributes to excess holes and disorder in the CuO_2 planes, giving rise to increasing inhomogeneity, decreasing Δ_(SC) and Δ_(CO), and a suppressed vortex-solid phase. For electron-type cuprate Sr_(0.9)La_(0.1)CuO_2 (La-112), the homogeneous Δ_(SC) and Δ_(CO) distributions may be attributed to stoichiometric cations and the absence of apical oxygen, with Δ_(CO) < Δ_(SC) revealed only inside the vortex cores. Finally, the vortex-core radius (ξ_(halo)) in electron-type cuprates is comparable to the SC coherence length ξ_(SC), whereas ξ_(halo) ∼ 10ξ_(SC) in hole-type cuprates, suggesting that ξ_(halo) may be correlated with the CO strength. The vortex-state irreversibility line in the magnetic field versus temperature phase diagram also reveals doping dependence, indicating the relevance of competing orders to vortex pinning

Regression with Linear Factored Functions

Many applications that use empirically estimated functions face a curse of dimensionality, because the integrals over most function classes must be approximated by sampling. This paper introduces a novel regression-algorithm that learns linear factored functions (LFF). This class of functions has structural properties that allow to analytically solve certain integrals and to calculate point-wise products. Applications like belief propagation and reinforcement learning can exploit these properties to break the curse and speed up computation. We derive a regularized greedy optimization scheme, that learns factored basis functions during training. The novel regression algorithm performs competitively to Gaussian processes on benchmark tasks, and the learned LFF functions are with 4-9 factored basis functions on average very compact.Comment: Under review as conference paper at ECML/PKDD 201

First- and Second-Order Phase Transitions, Fulde-Ferrel Inhomogeneous State and Quantum Criticality in Ferromagnet/Superconductor Double Tunnel Junctions

First- and second-order phase transitions, Fulde-Ferrel (FF) inhomogeneous superconducting (SC) state and quantum criticality in ferromagnet/superconductor/ferromagnet double tunnel junctions are investigated. For the antiparallel alignment of magnetizations, it is shown that a first-order phase transition from the homogeneous BCS state to the inhomogeneous FF state occurs at a certain bias voltage $V^{\ast}$; while the transitions from the BCS state and the FF state to the normal state at $V_{c}$ are of the second-order. A phase diagram for the central superconductor is presented. In addition, a quantum critical point (QCP), $$, is identified. It is uncovered that near the QCP, the SC gap, the chemical potential shift induced by the spin accumulation, and the difference of free energies between the SC and normal states vanish as $$ with the quantum critical exponents $z\nu =1/2$, 1 and 2, respectively. The tunnel conductance and magnetoresistance are also discussed.Comment: 5 pages, 4 figures, Phys. Rev. B 71, 144514 (2005

ELECTRONIC STRUCTURE OF FeSi

The full set of high-energy spectroscopy measurements including X-ray photoelectron valence band spectra and soft X-ray emission valence band spectra of both components of FeSi (Fe K_beta_5, Fe L_alpha, Si K_beta_1,3 and Si L_2,3) are performed and compared with the results of ab-initio band structure calculations using the linearized muffin-tin orbital method and linearized augmented plane wave method.Comment: 11 pages + 3 PostScript figures, RevTex3.0, to be published in J.Phys.:Cond.Matte

Calculation of atomic spontaneous emission rate in 1D finite photonic crystal with defects

We derive the expression for spontaneous emission rate in finite one-dimensional photonic crystal with arbitrary defects using the effective resonator model to describe electromagnetic field distributions in the structure. We obtain explicit formulas for contributions of different types of modes, i.e. radiation, substrate and guided modes. Formal calculations are illustrated with a few numerical examples, which demonstrate that the application of effective resonator model simplifies interpretation of results.Comment: Cent. Eur. J. Phys, in pres

Modulation of aminopyridine block of potassium currents in squid axon

Aminopyridines are known to block potassium (K) currents in excitable membranes in a manner dependent upon membrane potential, such that the block is relieved by depolarization and restored upon repolarization. In the present study, the effects of aminopyridines on voltage-dependent potassium (K) channels were examined in internally perfused, voltage-clamped squid giant axons. The time course of block restoration after conditioning depolarization was found to be modulated by membrane electric field, K-channel gating, and external cations. Depolarized holding potentials accelerated block restoration without altering steady-state block levels, suggesting that the voltage dependence of block restoration may be related to K channel gating rather than drug binding per se. In support of this notion, low external calcium concentration, which shifts the voltage dependence of K-channel gating to more negative potentials, also accelerated block restoration. Conversely, the relationship between the rate of block restoration and membrane holding potential was shifted in the depolarizing direction by phloretin, an agent that shifts the dependence of K-channel opening on membrane potential in a similar manner. Modification of K-channel gating also was found to alter the rate of block restoration. Addition of internal zinc or internal treatment with glutaraldehyde slowed the time course of both K-channel activation and aminopyridine block restoration. Aminopyridines also were found to interact in the K channel with external Cs+, NH4+, and Rb+, each of which slowed aminopyridine block restoration. Our results suggest that aminopyridines enter and occlude K channels, and that the availability of the binding site may be modulated by channel gating such that access is limited by the probability of the channel reaching an intermediate closed state at the resting potential

Upper critical field, lower critical field and critical current density of FeTe0.60Se0.40 single crystal

The transport and magnetic studies are performed on high quality FeTe0.60Se0.40 single crystals to determine the upper critical fields (Hc2), lower critical field (Hc1) and the Critical current density (Jc). The value of upper critical field Hc2 are very large, whereas the activation energy as determined from the slope of the Arrhenius plots are was found to be lower than that in the FeAs122 superconductor. The lower critical field was determined in ab direction and c direction of the crystal, and was found to have a anisotropy of 'gamma'{=(Hc1//c) / (Hc1//b)} ~ 4. The magnetic isotherms measured up to 12 Tesla shows the presence of fishtail behavior. The critical current densities at 1.8K of the single crystal was found to almost same in both ab and c direction as 1X105 Amp/cm2 in low field regime.Comment: 9 pages, 6 figure

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set