d_{xy}-Density wave in fermion-fermion cold atom mixtures

We study density wave instabilities in a doubly-degenerate Fermi-Fermi mixture with $SU(2)\times SU(2)$ symmetry on a square lattice. For sufficiently large on-site inter-species repulsion, when the two species of fermions are both at half-filling, two conventional ($s$-wave) number density waves are formed with a $\pi$-phase difference between them to minimize the inter-species repulsion. Upon moving one species away from half-filling, an unconventional density wave with $d_{xy}$-wave symmetry emerges. When both species are away from the vicinity of half-filling, superconducting instabilities dominate. We present results of a functional renormalization-group calculation that maps out the phase diagram at weak couplings. Also, we provide a simple explanation for the emergence of the $d_{xy}$-density wave phase based on a four-patch model. We find a robust and general mechanism for $d_{xy}$-density-wave formation that is related to the shape and size of the Fermi surfaces. The density imbalance between the two species of fermions in the vicinity of half-filling leads to phase-space discrepancy for different inter-species Umklapp couplings. Using a phase space argument for leading corrections in the one-loop renormalization group approach to fermions, we show that the phase-space discrepancy in our system causes opposite flows for the two leading intra-species Umklapp couplings and that this triggers the $d_{xy}$-density-wave instability.Comment: revised long version; 8 pages, 7 figure

A Search for Binary Stars at Low Metallicity

We present initial results measuring the companion fraction of metal-poor stars ([Fe/H]$<-$2.0). We are employing the Lick Observatory planet-finding system to make high-precision Doppler observations of these objects. The binary fraction of metal-poor stars provides important constraints on star formation in the early Galaxy (Carney et al. 2003). Although it has been shown that a majority of solar metallicity stars are in binaries, it is not clear if this is the case for metal-poor stars. Is there a metallicity floor below which binary systems do not form or become rare? To test this we are determining binary fractions at metallicities below [Fe/H]$=-2.0$. Our measurments are not as precise as the planet finders', but we are still finding errors of only 50 to 300 m/s, depending on the signal-to-noise of a spectrum and stellar atmosphere of the star. At this precision we can be much more complete than previous studies in our search for stellar companions.Comment: To appear in conference proceedings,"First Stars III", eds. B. O'Shea, A. Heger & T. Abel. 3 pages, 5 figure

Chemical Abundances For Evolved Stars In M5: Lithium Through Thorium

We present analysis of high-resolution spectra of a sample of stars in the globular cluster M5 (NGC 5904). The sample includes stars from the red giant branch (RGB; seven stars), the red horizontal branch (two stars), and the asymptotic giant branch (AGB; eight stars), with effective temperatures ranging from 4000 K to 6100 K. Spectra were obtained with the HIRES spectrometer on the Keck I telescope, with a wavelength coverage from 3700 angstrom to 7950 angstrom for the HB and AGB sample, and 5300 angstrom to 7600 angstrom for the majority of the RGB sample. We find offsets of some abundance ratios between the AGB and the RGB branches. However, these discrepancies appear to be due to analysis effects, and indicate that caution must be exerted when directly comparing abundance ratios between different evolutionary branches. We find the expected signatures of pollution from material enriched in the products of the hot hydrogen burning cycles such as the CNO, Ne-Na, and Mg-Al cycles, but no significant differences within these signatures among the three stellar evolutionary branches especially when considering the analysis offsets. We are also able to measure an assortment of neutron-capture element abundances, from Sr to Th, in the cluster. We find that the neutron-capture signature for all stars is the same, and shows a predominately r-process origin. However, we also see evidence of a small but consistent extra s-process signature that is not tied to the light-element variations, pointing to a pre-enrichment of this material in the protocluster gas.National Science Foundation AST-0802292NSF AST-0406988, AST-0607770, AST-0607482DFGW. M. Keck FoundationAstronom

Carbon and Strontium Abundances of Metal-Poor Stars

We present carbon and strontium abundances for 100 metal-poor stars measured from R$\sim$7000 spectra obtained with the Echellette Spectrograph and Imager at the Keck Observatory. Using spectral synthesis of the G-band region, we have derived carbon abundances for stars ranging from [Fe/H]$=-1.3$ to [Fe/H]$=-3.8$. The formal errors are $\sim 0.2$ dex in [C/Fe]. The strontium abundance in these stars was measured using spectral synthesis of the resonance line at 4215 {\AA}. Using these two abundance measurments along with the barium abundances from our previous study of these stars, we show it is possible to identify neutron-capture-rich stars with our spectra. We find, as in other studies, a large scatter in [C/Fe] below [Fe/H]$= -2$. Of the stars with [Fe/H]$<-2$, 9$\pm$4% can be classified as carbon-rich metal-poor stars. The Sr and Ba abundances show that three of the carbon-rich stars are neutron-capture-rich, while two have normal Ba and Sr. This fraction of carbon enhanced stars is consistent with other studies that include this metallicity range.Comment: ApJ, Accepte

A method for finding the background potential of quantum devices from scanning gate microscopy data using machine learning

The inverse problem of estimating the background potential from measurements of the local density of states is a challenging issue in quantum mechanics. Even more difficult is to do this estimation using approximate methods such as scanning gate microscopy (SGM). Here, we propose a machine-learning-based solution by exploiting adaptive cellular neural networks (CNNs). In the paradigmatic setting of a quantum point contact, the training data consist of potential-SGM functional relations represented by image pairs. These are generated by the recursive Green’s function method. We demonstrate that the CNN-based machine learning framework can predict the background potential corresponding to the experimental image data. This is confirmed by analyzing the estimated potential with image processing techniques based on the comparison between the charge densities and those obtained using different techniques. Correlation analysis of the images suggests the possibility of estimating different contributions to the background potential. In particular, our results indicate that both charge puddles and fixed impurities contribute to the spatial patterns found in the SGM data. Our work represents a timely contribution to the rapidly evolving field of exploiting machine learning to solve difficult problems in physics

Payment Rules through Discriminant-Based Classifiers

In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requirement with the goal of minimizing expected ex post regret, we are able to adapt statistical machine learning techniques to the design of payment rules. This computational approach to mechanism design is applicable to domains with multi-dimensional types and situations where computational efficiency is a concern. Specifically, given an outcome rule and access to a type distribution, we train a support vector machine with a special discriminant function structure such that it implicitly establishes a payment rule with desirable incentive properties. We discuss applications to a multi-minded combinatorial auction with a greedy winner-determination algorithm and to an assignment problem with egalitarian outcome rule. Experimental results demonstrate both that the construction produces payment rules with low ex post regret, and that penalizing classification errors is effective in preventing failures of ex post individual rationality

Filling some black holes: modeling the connection between urbanization, infrastructure, and global service intensity

This empirical article combines insights from previous research on the level of knowledge-intensive service in metropolitan areas with the aim to develop an understanding of the spatial structure of the global service economy. We use a stepwise regression model with the Globalization and World Cities research network's measure of globalized service provisioning as the dependent variable and a range of variables focusing on population, infrastructure, urban primacy, and national regulation as independent variables. The discussion of the results focuses on model parameters as well as the meaning of outliers and is used to explore some avenues for future research

Acute rejection is associated with antibodies to non-Gal antigens in baboons using Gal-knockout pig kidneys

We transplanted kidneys from α1,3-galactosyltransferase knockout (GalT-KO) pigs into six baboons using two different immunosuppressive regimens, but most of the baboons died from severe acute humoral xenograft rejection. Circulating induced antibodies to non-Gal antigens were markedly elevated at rejection, which mediated strong complement-dependent cytotoxicity against GalT-KO porcine target cells. These data suggest that antibodies to non-Gal antigens will present an additional barrier to transplantation of organs from GalT-KO pigs to humans. © 2005 Nature Publishing Group

Scale-invariant magnetic anisotropy in RuCl3_3 at high magnetic fields

In RuCl$_3$, inelastic neutron scattering and Raman spectroscopy reveal a continuum of non-spin-wave excitations that persists to high temperature, suggesting the presence of a spin liquid state on a honeycomb lattice. In the context of the Kitaev model, magnetic fields introduce finite interactions between the elementary excitations, and thus the effects of high magnetic fields - comparable to the spin exchange energy scale - must be explored. Here we report measurements of the magnetotropic coefficient - the second derivative of the free energy with respect to magnetic field orientation - over a wide range of magnetic fields and temperatures. We find that magnetic field and temperature compete to determine the magnetic response in a way that is independent of the large intrinsic exchange interaction energy. This emergent scale-invariant magnetic anisotropy provides evidence for a high degree of exchange frustration that favors the formation of a spin liquid state in RuCl$_3$.Comment: arXiv admin note: substantial text overlap with arXiv:1901.09245. Nature Physic