Strong deflection gravitational lensing by a modified Hayward black hole

A modified Hayward black hole is a nonsingular black hole. It is proposed to form when the pressure generated by quantum gravity can stop matter's collapse as the matter reaches Planck density. Strong deflection gravitational lensing happening nearby its event horizon might provide some clues of these quantum effects in its central core. We investigate observables of the strong deflection lensing, including angular separations, brightness differences and time delays between its relativistic images, and estimate their values for the supermassive black hole in the Galactic center. We find that it is possible to distinguish the modified Hayward black hole from a Schwarzschild one, but it demands very high resolution beyond current stage.Comment: 10 pages, 1 figur

Simulating emergent urban form: desakota in China

We propose that the emergent phenomenon know as ?desakota?, the rapidurbanization of densely populated rural populations in the newlydeveloped world, particularly China, can be simulated using agent-basedmodels which combine both local and global features. We argue thatdeskota represents a surprising and unusual form of urbanization wellmatchedto processes of land development that are driven from the bottomup but moderated by the higher-level macro economy. We develop asimple logic which links local household reform to global urban reform,translating these ideas into a model structure which reflects these twoscales. Our model first determines the rate of growth of different spatialaggregates using linear statistical analysis. It then allocates this growth tothe local level using developer agents who determine the transformation ormutation of rural households to urban pursuits based on local land costs,accessibilities, and growth management practices. The model is applied todesakota development in the Suzhou region between 1990 and 2000. Weshow how the global rates of change predicted at the township level in theWuxian City region surrounding Suzhou are tempered by localtransformations of rural to urban land uses which we predict using cellularautomata rules. The model, which is implemented in the RePast 3software, is validated using a blend of data taken from remote sensing andgovernment statistical sources. It represents an example of generativesocial science that fuses plausible behavior with formalized logics matchedagainst empirical evidence, essential in showing how novel patterns ofurbanization such as desakota emerge

A Scalable and Extensible Framework for Superposition-Structured Models

In many learning tasks, structural models usually lead to better interpretability and higher generalization performance. In recent years, however, the simple structural models such as lasso are frequently proved to be insufficient. Accordingly, there has been a lot of work on "superposition-structured" models where multiple structural constraints are imposed. To efficiently solve these "superposition-structured" statistical models, we develop a framework based on a proximal Newton-type method. Employing the smoothed conic dual approach with the LBFGS updating formula, we propose a scalable and extensible proximal quasi-Newton (SEP-QN) framework. Empirical analysis on various datasets shows that our framework is potentially powerful, and achieves super-linear convergence rate for optimizing some popular "superposition-structured" statistical models such as the fused sparse group lasso

Localization of U(1)U(1) gauge vector field on flat branes with five-dimension (asymptotic) AdS5_{5} spacetime

In order to localize $U(1)$ gauge vector field on Randall-Sundrum-like braneworld model with infinite extra dimension, we propose a new kind of non-minimal coupling between the $U(1)$ gauge field and the gravity. We propose three kinds of coupling methods and they all support the localization of zero mode. In addition, one of them can support the localization of massive modes. Moreover, the massive tachyonic modes can be excluded. And our method can be used not only in the thin braneword models but also in the thick ones.Comment: Added acknowledgments to the refree. Appeared on JHE