Black Holes, Entropy Bound and Causality Violation

The gravity/gauge theory duality has provided us a way of studying QCD at short distances from straightforward calculations in classical general relativity. Among numerous results obtained so far, one of the most striking is the universality of the ratio of the shear viscosity to the entropy density. For all gauge theories with Einstein gravity dual, this ratio is \eta/s=1/4\pi. However, in general higher-curvature gravity theories, including two concrete models under discussion - the Gauss-Bonnet gravity and the (Riemann)^2 gravity - the ratio \eta/s can be smaller than 1/4\pi (thus violating the conjecture bound), equal to 1/4\pi or even larger than 1/4\pi. As we probe spacetime at shorter distances, there arises an internal inconsistency in the theory, such as a violation of microcausality, which is correlated with a classical limit on black hole entropy.Comment: 8 pages, no figures; Invited contribution to appear in the Proceedings of the 75 Years since Solvay, Singapore, Nov 2008, (World Scientific, Singapore, 2009

Acoustic black holes from supercurrent tunneling

We present a version of acoustic black holes by using the principle of the Josephson effect. We find that in the case two superconductors $A$ and $B$ are separated by an insulating barrier, an acoustic black hole may be created in the middle region between the two superconductors. We discuss in detail how to describe an acoustic black hole in the Josephson junction and write the metric in the langauge of the superconducting electronics. Our final results infer that for big enough tunneling current and thickness of the junction, experimental verification of the Hawking temperature could be possible.Comment: 15pages,1 figure, to appear in IJMP

Stochastic Physics, Complex Systems and Biology

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated equilibrium, spontaneous random "mutations" and "adaptations". On an evlutionary time scale it produces sustainable diversity among individuals in a homogeneous population rather than convergence as usually predicted by a deterministic dynamics. The emergent discrete states in such a system, i.e., attractors, have natural robustness against both internal and external perturbations. Phenotypic states of a biological cell, a mesoscopic nonlinear stochastic open biochemical system, could be understood through such a perspective.Comment: 10 page

Theory of the spatial structure of non-linear lasing modes

A self-consistent integral equation is formulated and solved iteratively which determines the steady-state lasing modes of open multi-mode lasers. These modes are naturally decomposed in terms of frequency dependent biorthogonal modes of a linear wave equation and not in terms of resonances of the cold cavity. A one-dimensional cavity laser is analyzed and the lasing mode is found to have non-trivial spatial structure even in the single-mode limit. In the multi-mode regime spatial hole-burning and mode competition is treated exactly. The formalism generalizes to complex, chaotic and random laser media.Comment: 4 pages, 3 figure

Geoarchaeological evidence of the AD 1642 Yellow River flood that destroyed Kaifeng, a former capital of dynastic China

Rising global temperatures will increase the number of extreme weather events, creating new challenges for cities around the world. Archaeological research on the destruction and subsequent reoccupation of ancient cities has the potential to reveal geological and social dynamics that have historically contributed to making urban settings resilient to these extreme weather events. Using a combination of archaeological and geological methods, we examine how extreme flood events at Kaifeng, a former capital of dynastic China, have shaped the city’s urban resilience. Specifically, we focus on an extreme Yellow River flood event in AD 1642 that historical records suggest killed around 300,000 people living in Kaifeng. Our recent archaeological excavations have discovered compelling geological and archaeological evidence that corroborates these documents, revealing that the AD 1642 Yellow River flood destroyed Kaifeng’s inner city, entombing the city and its inhabitants within meters of silt and clay. We argue that the AD 1642 flood was extraordinarily catastrophic because Kaifeng’s city walls only partly collapsed, entrapping most of the flood waters within the city. Both the geology of the Yellow River floods as well as the socio-political context of Kaifeng shaped the city’s resilience to extreme flood events

VConv-DAE: Deep Volumetric Shape Learning Without Object Labels

With the advent of affordable depth sensors, 3D capture becomes more and more ubiquitous and already has made its way into commercial products. Yet, capturing the geometry or complete shapes of everyday objects using scanning devices (e.g. Kinect) still comes with several challenges that result in noise or even incomplete shapes. Recent success in deep learning has shown how to learn complex shape distributions in a data-driven way from large scale 3D CAD Model collections and to utilize them for 3D processing on volumetric representations and thereby circumventing problems of topology and tessellation. Prior work has shown encouraging results on problems ranging from shape completion to recognition. We provide an analysis of such approaches and discover that training as well as the resulting representation are strongly and unnecessarily tied to the notion of object labels. Thus, we propose a full convolutional volumetric auto encoder that learns volumetric representation from noisy data by estimating the voxel occupancy grids. The proposed method outperforms prior work on challenging tasks like denoising and shape completion. We also show that the obtained deep embedding gives competitive performance when used for classification and promising results for shape interpolation

First High Contrast Imaging Using a Gaussian Aperture Pupil Mask

Placing a pupil mask with a gaussian aperture into the optical train of current telescopes represents a way to attain high contrast imaging that potentially improves contrast by orders of magnitude compared to current techniques. We present here the first observations ever using a gaussian aperture pupil mask (GAPM) on the Penn State near-IR Imager and Spectrograph (PIRIS) at the Mt. Wilson 100$^{\prime\prime}$ telescope. Two nearby stars were observed, $\epsilon$ Eridani and $\mu$ Her A. A faint companion was detected around $\mu$ Her A, confirming it as a proper motion companion. Furthermore, the observed H and K magnitudes of the companion were used to constrain its nature. No companions or faint structure were observed for $\epsilon$ Eridani. We found that our observations with the GAPM achieved contrast levels similar to our coronographic images, without blocking light from the central star. The mask's performance also nearly reached sensitivities reported for other ground based adaptive optics coronographs and deep HST images, but did not reach theoretically predicted contrast levels. We outline ways that could improve the performance of the GAPM by an order of magnitude or more.Comment: 8 pages, 4 figures, accepted by ApJ letter