Symmetry and correlation effects on band structure explain the anomalous transport properties of (111) LaAlO3_3/SrTiO3_3

The interface between the two insulating oxides SrTiO$_3$ and LaAlO$_3$ gives rise to a two-dimensional electron system with intriguing transport phenomena, including superconductivity, which are controllable by a gate. Previous measurements on the (001) interface have shown that the superconducting critical temperature, the Hall density, and the frequency of quantum oscillations, vary nonmonotonically and in a correlated fashion with the gate voltage. In this paper we experimentally demonstrate that the (111) interface features a qualitatively distinct behavior, in which the frequency of Shubnikov-de Haas oscillations changes monotonically, while the variation of other properties is nonmonotonic albeit uncorrelated. We develop a theoretical model, incorporating the different symmetries of these interfaces as well as electronic-correlation-induced band competition. We show that the latter dominates at (001), leading to similar nonmonotonicity in all observables, while the former is more important at (111), giving rise to highly curved Fermi contours, and accounting for all its anomalous transport measurements.Comment: 6+7 pages, 4+6 figures, Published Versio

Order parameter node removal in the d-wave superconductor YBa2Cu3O7−xYBa_{2}Cu_{3}O_{7-x} under magnetic field

hether the node in the order parameter characteristic of a $d-wave$ superconductor can or cannot be removed by an applied magnetic field has been a subject of debate in recent years. Thermal conductivity results on the high Tc superconductor $Bi_{2}Sr_{2}CaCu_{2}O_{8}$ originally explained by Laughlin in terms of such a node removal were complicated by hysteresis effects, and judged inconclusive. We present new tunneling data on $YBa_{2}Cu_{3}O_{7-x}$ that support the existence of the node removal effect, under specific orientations of the sample's surfaces and magnetic field. We also explain the hysteretic behavior and other previous tunneling results so far not understood satisfactorily, attributing them to a combination of node removal and Doppler shift of low energy surface bound states.Comment: 3 pages, 3 figure

A Pilot Point Guided Pattern Matching Approach to Integrate Dynamic Data into Geological Modeling

Methods based on multiple-point statistics (MPS) have been routinely used to characterize complex geological formations in the last decade. These methods use the available static data (for example, measured conductivities) for conditioning. Integrating dynamic data (for example, measured transient piezometric head data) into the same framework is challenging because of the complex non-linear relationship between the dynamic response and geology. The Ensemble PATtern (EnPAT) search method was recently developed as a promising technique to handle this problem. In this approach, a pattern is postulated to be composed of both parameter and state variables, and then, parameter values are sequentially (point-wise) simulated by directly sampling the matched pattern from an ensemble of training images of both geologic parameters and state variables. As a consequence, the updated ensemble of realizations of the geological parameters preserve curvilinear structures (i.e., non-multiGaussanity) as well as the complex relationship between static and dynamic data. Moreover, the uncertainty of flow and transport predictions can be assessed using the updated ensemble of geological models. In this work, we further modify the EnPAT method by introducing the pilot-point concept into the algorithm. More specifically, the parameter values at a set of randomly selected pilot point locations are simulated by the pattern searching procedure, and then a faster MPS method is used to complete the simulation by conditioning to the previously simulated pilot point values. This pilot point guided MPS implementation results in lower computational cost and more accurate inference of the parameter field. In addition, in some situations where there is sparsity of measured geologic static data, the EnPAT algorithm is extended to work only with the dynamic data. We employed a synthetic example to demonstrate the effectiveness of pilot points in the implementation of EnPAT, and also the capability of dynamic data to identify complex geologic structures when measured conductivity data are not available.The first three authors gratefully acknowledge the financial support by DOE through project DE-FE0004962. The fourth author acknowledges the financial support by the Spanish Ministry of Science and Innovation through project CGL2011-23295. The authors also wish to thank Wolfgang Nowak as well as two anonymous reviewers for their comments, which helped improving the final version of the manuscript.Li, L.; Srinivasan, S.; Zhou, H.; Gómez-Hernández, JJ. (2013). A Pilot Point Guided Pattern Matching Approach to Integrate Dynamic Data into Geological Modeling. Advances in Water Resources. 62(Part A):125-138. https://doi.org/10.1016/j.advwatres.2013.10.008S12513862Part