Magnetic field effects on the density of states of orthorhombic superconductors

The quasiparticle density of states in a two-dimensional d-wave superconductor depends on the orientation of the in-plane external magnetic field H. This is because. in the region of the gap nodes, the Doppler shift due to the circulating supercurrents around a vortex depend on the direction of H. For a tetragonal system the induced pattern is four-fold symmetric and, at zero energy, the density of states exhibits minima along the node directions. But YBa_2C_3O_{6.95} is orthorhombic because of the chains and the pattern becomes two-fold symmetric with the position of the minima occuring when H is oriented along the Fermi velocity at a node on the Fermi surface. The effect of impurity scattering in the Born and unitary limit is discussed.Comment: 24 pages, 11 Figure

Effect of pseudogap formation on the penetration depth of underdoped high TcT_c cuprates

The penetration depth is calculated over the entire doping range of the cuprate phase diagram with emphasis on the underdoped regime. Pseudogap formation on approaching the Mott transition, for doping below a quantum critical point, is described within a model based on the resonating valence bond spin liquid which provides an ansatz for the coherent piece of the Green's function. Fermi surface reconstruction, which is an essential element of the model, has a strong effect on the superfluid density at T=0 producing a sharp drop in magnitude, but does not change the slope of the linear low temperature variation. Comparison with recent data on Bi-based cuprates provides validation of the theory and shows that the effects of correlations, captured by Gutzwiller factors, are essential for a qualitative understanding of the data. We find that the Ferrell-Glover-Tinkham sum rule still holds and we compare our results with those for the Fermi arc and the nodal liquid models.Comment: 14 pages, 9 figures, submitted to PR

Enabling Hyper-Personalisation: Automated Ad Creative Generation and Ranking for Fashion e-Commerce

Homepage is the first touch point in the customer's journey and is one of the prominent channels of revenue for many e-commerce companies. A user's attention is mostly captured by homepage banner images (also called Ads/Creatives). The set of banners shown and their design, influence the customer's interest and plays a key role in optimizing the click through rates of the banners. Presently, massive and repetitive effort is put in, to manually create aesthetically pleasing banner images. Due to the large amount of time and effort involved in this process, only a small set of banners are made live at any point. This reduces the number of banners created as well as the degree of personalization that can be achieved. This paper thus presents a method to generate creatives automatically on a large scale in a short duration. The availability of diverse banners generated helps in improving personalization as they can cater to the taste of larger audience. The focus of our paper is on generating wide variety of homepage banners that can be made as an input for user level personalization engine. Following are the main contributions of this paper: 1) We introduce and explain the need for large scale banner generation for e-commerce 2) We present on how we utilize existing deep learning based detectors which can automatically annotate the required objects/tags from the image. 3) We also propose a Genetic Algorithm based method to generate an optimal banner layout for the given image content, input components and other design constraints. 4) Further, to aid the process of picking the right set of banners, we designed a ranking method and evaluated multiple models. All our experiments have been performed on data from Myntra (http://www.myntra.com), one of the top fashion e-commerce players in India.Comment: Workshop on Recommender Systems in Fashion, 13th ACM Conference on Recommender Systems, 201

Orthorhombicity mixing of s- and d- gap components in YBa2Cu3O7YBa_2Cu_3O_7 without involving the chains

Momentum decoupling develops when forward scattering dominates the pairing interaction and implies tendency for decorrelation between the physical behavior in the various regions of the Fermi surface. In this regime it is possible to obtain anisotropic s- or d-wave superconductivity even with isotropic pairing scattering. We show that in the momentum decoupling regime the distortion of the $CuO_2$ planes is enough to explain the experimental reports for s- mixing in the dominantly d-wave gap of $YBa_2Cu_3O_7$. In the case of spin fluctuations mediated pairing instead, a large part of the condensate must be located in the chains in order to understand the experiments.Comment: LATEX file and 3 Postscript figure

Electronic structure in underdoped cuprates due to the emergence of a pseudogap

The phenomenological Green's function developed in the works of Yang, Rice and Zhang has been very successful in understanding many of the anomalous superconducting properties of the deeply underdoped cuprates. It is based on considerations of the resonating valence bond spin liquid approximation and is designed to describe the underdoped regime of the cuprates. Here we emphasize the region of doping, $x$, just below the quantum critical point at which the pseudogap develops. In addition to Luttinger hole pockets centered around the nodal direction, there are electron pockets near the antinodes which are connected to the hole pockets by gapped bridging contours. We determine the contours of nearest approach as would be measured in angular resolved photoemission experiments and emphasize signatures of the Fermi surface reconstruction from the large Fermi contour of Fermi liquid theory (which contains $1+x$ hole states) to the Luttinger pocket (which contains $x$ hole states). We find that the quasiparticle effective mass renormalization increases strongly towards the edge of the Luttinger pockets beyond which it diverges.Comment: 11 pages, 9 figure

Fermi-Liquid Interactions in d-Wave Superconductor

This article develops a quantitative quasiparticle model of the low-temperature properties of d-wave superconductors which incorporates both Fermi-liquid effects and band-structure effects. The Fermi-liquid interaction effects are found to be classifiable into strong and negligible renormalizaton effects, for symmetric and antisymmetric combinations of the energies of $k\uparrow$ and $-k\downarrow$ quasiparticles, respectively. A particularly important conclusion is that the leading clean-limit temperature-dependent correction to the superfluid density is not renormalized by Fermi-liquid interactions, but is subject to a Fermi velocity (or mass) renormalization effect. This leads to difficulties in accounting for the penetration depth measurements with physically acceptable parameters, and hence reopens the question of the quantitative validity of the quasiparticle picture.Comment: 4 page

CE15014

In the southwest of Ireland and the Celtic Sea (ICES Divisions VIIaS, g & j),herring acoustic surveys have been carried out since 1989. In the Celtic Sea and VIIj, herring acoustic surveys have been carried out since 1989, and this survey is the 21st in the overall acoustic series or the tenth in the modified time series conducted exclusively in October. The geographical confines of the annual 21 day survey have been modified in recent years to include areas to the south of the main winter spawning grounds in an effort to identify the whereabouts of winter spawning fish before the annual inshore spawning migration. Spatial resolution of acoustic transects has been increased over the entire south coast survey area. The acoustic component of the survey has been further complemented since 2004 by detailed hydrographic, marine mammal and seabird surveys

Data Pipeline Management in Practice: Challenges and Opportunities

Data pipelines involve a complex chain of interconnected activities that starts with a data source and ends in a data sink. Data pipelines are important for data-driven organizations since a data pipeline can process data in multiple formats from distributed data sources with minimal human intervention, accelerate data life cycle activities, and enhance productivity in data-driven enterprises. However, there are challenges and opportunities in implementing data pipelines but practical industry experiences are seldom reported. The findings of this study are derived by conducting a qualitative multiple-case study and interviews with the representatives of three companies. The challenges include data quality issues, infrastructure maintenance problems, and organizational barriers. On the other hand, data pipelines are implemented to enable traceability, fault-tolerance, and reduce human errors through maximizing automation thereby producing high-quality data. Based on multiple-case study research with five use cases from three case companies, this paper identifies the key challenges and benefits associated with the implementation and use of data pipelines

Annealing-Dependent Magnetic Depth Profile in Ga[1-x]Mn[x]As

We have studied the depth-dependent magnetic and structural properties of as-grown and optimally annealed Ga[1-x]Mn[x]As films using polarized neutron reflectometry. In addition to increasing total magnetization, the annealing process was observed to produce a significantly more homogeneous distribution of the magnetization. This difference in the films is attributed to the redistribution of Mn at interstitial sites during the annealing process. Also, we have seen evidence of significant magnetization depletion at the surface of both as-grown and annealed films.Comment: 5 pages, 3 figure