Magnetic field induced band insulator to Mott insulator transformations in 4-component alkali fermions at half-filling

Under the influence of an external magnetic field and spin-changing collisions, the band insulator (BI) state of one-dimensional (1D) s-wave repulsively interacting 4-component fermions at half-filling transforms into Mott insulator (MI) states with spontaneously broken translational symmetry: a dimerized state for shallow lattices and a N{\'e}el state for deep lattices via an intermediate topological state. Since a BI has vanishing entropy per particle, these MI phases could be particularly inviting for experimental realization under the similar conditions as those for $^{40}$K atoms [1], provided the magnetic field is changed adiabatically.Comment: 5 eps figure

Bounds on area and charge for marginally trapped surfaces with cosmological constant

We sharpen the known inequalities $A \Lambda \le 4\pi (1-g)$ and $A\ge 4\pi Q^2$ between the area $A$ and the electric charge $Q$ of a stable marginally outer trapped surface (MOTS) of genus g in the presence of a cosmological constant $\Lambda$. In particular, instead of requiring stability we include the principal eigenvalue $\lambda$ of the stability operator. For $\Lambda^{*} = \Lambda + \lambda > 0$ we obtain a lower and an upper bound for $\Lambda^{*} A$ in terms of $\Lambda^{*} Q^2$ as well as the upper bound $Q \le 1/(2\sqrt{\Lambda^{*}})$ for the charge, which reduces to $Q \le 1/(2\sqrt{\Lambda})$ in the stable case $\lambda \ge 0$. For $\Lambda^{*} < 0$ there remains only a lower bound on $A$. In the spherically symmetric, static, stable case one of the area inequalities is saturated iff the surface gravity vanishes. We also discuss implications of our inequalities for "jumps" and mergers of charged MOTS.Comment: minor corrections to previous version and to published versio

Working with OpenCL to Speed Up a Genetic Programming Financial Forecasting Algorithm: Initial Results

The genetic programming tool EDDIE has been shown to be a successful financial forecasting tool, however it has suffered from an increase in execution time as new features have been added. Speed is an important aspect in financial problems, especially in the field of algorithmic trading, where a delay in taking a decision could cost millions. To offset this performance loss, EDDIE has been modified to take advantage of multi-core CPUs and dedicated GPUs. This has been achieved by modifying the candidate solution evaluation to use an OpenCL kernel, allowing the parallel evaluation of solutions. Our computational results have shown improvements in the running time of EDDIE when the evaluation was delegated to the OpenCL kernel running on a multi-core CPU, with speed ups up to 21 times faster than the original EDDIE algorithm. While most previous works in the literature reported significantly improvements in performance when running an OpenCL kernel on a GPU device, we did not observe this in our results. Further investigation revealed that memory copying overheads and branching code in the kernel are potentially causes of the (under-)performance of the OpenCL kernel when running on the GPU device

Analysis of regulatory network involved in mechanical induction of embryonic stem cell differentiation

Embryonic stem cells are conventionally differentiated by modulating specific growth factors in the cell culture media. Recently the effect of cellular mechanical microenvironment in inducing phenotype specific differentiation has attracted considerable attention. We have shown the possibility of inducing endoderm differentiation by culturing the stem cells on fibrin substrates of specific stiffness [1]. Here, we analyze the regulatory network involved in such mechanically induced endoderm differentiation under two different experimental configurations of 2-dimensional and 3-dimensional culture, respectively. Mouse embryonic stem cells are differentiated on an array of substrates of varying mechanical properties and analyzed for relevant endoderm markers. The experimental data set is further analyzed for identification of co-regulated transcription factors across different substrate conditions using the technique of bi-clustering. Overlapped bi-clusters are identified following an optimization formulation, which is solved using an evolutionary algorithm. While typically such analysis is performed at the mean value of expression data across experimental repeats, the variability of stem cell systems reduces the confidence on such analysis of mean data. Bootstrapping technique is thus integrated with the bi-clustering algorithm to determine sets of robust bi-clusters, which is found to differ significantly from corresponding bi-clusters at the mean data value. Analysis of robust bi-clusters reveals an overall similar network interaction as has been reported for chemically induced endoderm or endodermal organs but with differences in patterning between 2-dimensional and 3-dimensional culture. Such analysis sheds light on the pathway of stem cell differentiation indicating the prospect of the two culture configurations for further maturation. © 2012 Zhang et al

Black hole Area-Angular momentum inequality in non-vacuum spacetimes

We show that the area-angular momentum inequality A\geq 8\pi|J| holds for axially symmetric closed outermost stably marginally trapped surfaces. These are horizon sections (in particular, apparent horizons) contained in otherwise generic non-necessarily axisymmetric black hole spacetimes, with non-negative cosmological constant and whose matter content satisfies the dominant energy condition.Comment: 5 pages, no figures, updated to match published versio

Mice and rats achieve similar levels of performance in an adaptive decision-making task

Two opposing constraints exist when choosing a model organism for studying the neural basis of adaptive decision-making: (1) experimental access and (2) behavioral complexity. Available molecular and genetic approaches for studying neural circuits in the mouse fulfill the first requirement. In contrast, it is still under debate if mice can perform cognitive tasks of sufficient complexity. Here we compare learning and performance of mice and rats, the preferred behavioral rodent model, during an acoustic flexible categorization two-alternative choice task. The task required animals to switch between two categorization definitions several times within a behavioral session. We found that both species achieved similarly high performance levels. On average, rats learned the task faster than mice, although some mice were as fast as the average rat. No major differences in subjective categorization boundaries or the speed of adaptation between the two species were found. Our results demonstrate that mice are an appropriate model for the study of the neural mechanisms underlying adaptive decision-making, and suggest they might be suitable for other cognitive tasks as well

An introduction to local Black Hole horizons in the 3+1 approach to General Relativity

We present an introduction to dynamical trapping horizons as quasi-local models for black hole horizons, from the perspective of an Initial Value Problem approach to the construction of generic black hole spacetimes. We focus on the geometric and structural properties of these horizons aiming, as a main application, at the numerical evolution and analysis of black hole spacetimes in astrophysical scenarios. In this setting, we discuss their dual role as an "a priori" ingredient in certain formulations of Einstein equations and as an "a posteriori" tool for the diagnosis of dynamical black hole spacetimes. Complementary to the first-principles discussion of quasi-local horizon physics, we place an emphasis on the "rigidity" properties of these hypersurfaces and their role as privileged geometric probes into near-horizon strong-field spacetime dynamics.Comment: 37 pages, 5 figures. Notes prepared for the course at the 2011 Shanghai Asia-Pacific School and Workshop on Gravitation (Shanghai Normal University, February 10-14, 2011