Universal Tomonaga-Luttinger liquid phases in one-dimensional strongly attractive SU(N) fermionic cold atoms

A simple set of algebraic equations is derived for the exact low-temperature thermodynamics of one-dimensional multi-component strongly attractive fermionic atoms with enlarged SU(N) spin symmetry and Zeeman splitting. Universal multi-component Tomonaga-Luttinger liquid (TLL) phases are thus determined. For linear Zeeman splitting, the physics of the gapless phase at low temperatures belongs to the universality class of a two-component asymmetric TLL corresponding to spin-neutral N-atom composites and spin-(N-1)/2 single atoms. The equation of states is also obtained to open up the study of multi-component TLL phases in 1D systems of N-component Fermi gases with population imbalance.Comment: 12 pages, 3 figure

Abnormal Fees and Timely Loss Recognition - A Long-Term Perspective

This is the author accepted manuscript. The final version is available from the American Accounting Association via the DOI in this recordWe examine the relation between timely loss recognition and abnormal audit, non-audit, and total fees over a long period (2001–2007 and 2010–2015). We use positive abnormal audit fees as a measure of abnormal audit effort, and positive abnormal non-audit fees as a measure of economic bond between the auditor and the auditee. Using the Ball and Shivakumar (2006) model, we report some evidence suggesting audit effort is associated with slower loss recognition in accruals before the Sarbanes–Oxley Act (SOX) became effective. However, we find stronger evidence that audit effort is associated with slower loss recognition post-SOX when clients raise substantial external funds or when the auditor is not an industry specialist. Using C_Score, we find a negative association between changes in abnormal audit fees and total fees, and changes in C_Score post-SOX, but not pre-SOX. We find no sample-wide evidence that abnormal non-audit fees are associated with the speed of loss recognition. Collectively, the results suggest post-SOX auditors exert more effort when losses are delayed and that non-audit services do not compromise auditor independence

Universal behavior of giant electroresistance in epitaxial La0.67Ca0.33MnO3 thin films

We report a giant resistance drop induced by dc electrical currents in La0.67Ca0.33MnO3 epitaxial thin films. Resistance of the patterned thin films decreases exponentially with increasing current and a maximum drop shows at the temperature of resistance peak Tp. Variation of resistance with current densities can be scaled below and above Tp, respectively. This work can be useful for the future applications of electroresistance.Comment: 13 pages, 4 figure

Ice Model Calibration using Semi-continuous Spatial Data

Rapid changes in Earth’s cryosphere caused by human activity can lead to significant environmental impacts. Computer models provide a useful tool for understanding the behavior and projecting the future of Arctic and Antarctic ice sheets. However, these models are typically subject to large parametric uncertainties due to poorly constrained model input parameters that govern the behavior of simulated ice sheets. Computer model calibration provides a formal statistical framework to infer parameters using observational data, and to quantify the uncertainty in projections due to the uncertainty in these parameters. Calibration of ice sheet models is often challenging because the relevant model output and observational data take the form of semi-continuous spatial data, with a point mass at zero and a right-skewed continuous distribution for positive values. Current calibration approaches cannot handle such data. Here we introduce a hierarchical latent variable model that handles binary spatial patterns and positive continuous spatial patterns as separate components. To overcome challenges due to high-dimensionality we use likelihood-based generalized principal component analysis to impose low-dimensional structures on the latent variables for spatial dependence. We apply our methodology to calibrate a physical model for the Antarctic ice sheet and demonstrate that we can overcome the aforementioned modeling and computational challenges. As a result of our calibration, we obtain improved future ice-volume change projections

Trace Element Chemistry of Larkman Nunatuk (LAR) 12011, a New Olivine-Phyric Shergottite

The olivine-phyric shergottite LAR12011 was found at Larkman Nunatuk during the 2012 ANSMET expedition [1]. The preliminary analysis of LAR12011 presented in [1] and oxygen isotope analysis in [2] confirms its Martian origin. This new sample is paired with LAR06319 [1-3]. Here, we present petrography and new data on the trace element chemistry of LAR12011

Exactly solvable models and ultracold Fermi gases

Exactly solvable models of ultracold Fermi gases are reviewed via their thermodynamic Bethe Ansatz solution. Analytical and numerical results are obtained for the thermodynamics and ground state properties of two- and three-component one-dimensional attractive fermions with population imbalance. New results for the universal finite temperature corrections are given for the two-component model. For the three-component model, numerical solution of the dressed energy equations confirm that the analytical expressions for the critical fields and the resulting phase diagrams at zero temperature are highly accurate in the strong coupling regime. The results provide a precise description of the quantum phases and universal thermodynamics which are applicable to experiments with cold fermionic atoms confined to one-dimensional tubes.Comment: based on an invited talk at Statphys24, Cairns (Australia) 2010. 16 pages, 6 figure

XGBoostPP: Tree-based Estimation of Point Process Intensity Functions

We propose a novel tree-based ensemble method, named XGBoostPP, to nonparametrically estimate the intensity of a point process as a function of covariates. It extends the use of gradient-boosted regression trees (Chen & Guestrin, 2016) to the point process literature via two carefully designed loss functions. The first loss is based on the Poisson likelihood, working for general point processes. The second loss is based on the weighted Poisson likelihood, where spatially dependent weights are introduced to further improve the estimation efficiency for clustered processes. An efficient greedy search algorithm is developed for model estimation, and the effectiveness of the proposed method is demonstrated through extensive simulation studies and two real data analyses. In particular, we report that XGBoostPP achieves superior performance to existing approaches when the dimension of the covariate space is high, revealing the advantages of tree-based ensemble methods in estimating complex intensity functions.Comment: 21 pages, 3 figure