Prediction of quantum stripe ordering in optical lattices

We predict the robust existence of a novel quantum orbital stripe order in the $p$-band Bose-Hubbard model of two-dimensional triangular optical lattices with cold bosonic atoms. An orbital angular momentum moment is formed on each site exhibiting a stripe order both in the superfluid and Mott-insulating phases. The stripe order spontaneously breaks time-reversal, lattice translation and rotation symmetries. In addition, it induces staggered plaquette bond currents in the superfluid phase. Possible signatures of this stripe order in the time of flight experiment are discussed.Comment: 4 pages, three figures, accepted by Phys. Rev. Let

Lattice four-dimensional N=4 SYM is practical

We show that nonperturbative lattice studies of four-dimensional N=4 Super-Yang-Mills are within reach. We use Ginsparg-Wilson fermions to avoid gluino masses and an exact implementation of the (chiral) $R$-symmetry, which greatly limits the number of counterterms that must be fine-tuned. Only bosonic operators require fine tuning, so all tunings can be done ``offline'' by a Ferrenberg-Swendsen type reweighting. We show what measurables can be used to perform the tuning.Comment: 4 page

Human-scale economics: Economic growth and poverty reduction in Northeastern Thailand

Ministry of Education, Singapore under its Academic Research Funding Tier

Incompressible Quantum Liquids and New Conservation Laws

In this letter we investigate a class of Hamiltonians which, in addition to the usual center-of-mass (CM) momentum conservation, also have center-of-mass position conservation. We find that regardless of the particle statistics, the energy spectrum is at least q-fold degenerate when the filling factor is $p/q$, where $p$ and $q$ are coprime integers. Interestingly the simplest Hamiltonian respecting this type of symmetry encapsulates two prominent examples of novel states of matter, namely the fractional quantum Hall liquid and the quantum dimer liquid. We discuss the relevance of this class of Hamiltonian to the search for featureless Mott insulators.Comment: updated version, to be published by PR

Quantum transport and two-parameter scaling at the surface of a weak topological insulator

Weak topological insulators have an even number of Dirac cones in their surface spectrum and are thought to be unstable to disorder, which leads to an insulating surface. Here we argue that the presence of disorder alone will not localize the surface states, rather; the presence of a time-reversal symmetric mass term is required for localization. Through numerical simulations, we show that in the absence of the mass term the surface always flow to a stable metallic phase and the conductivity obeys a one-parameter scaling relation, just as in the case of a strong topological insulator surface. With the inclusion of the mass, the transport properties of the surface of a weak topological insulator follow a two-parameter scaling form.Comment: 4 pages + Appendices, v2 added conductance distributio

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

BACKGROUND: Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. RESULTS: Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. CONCLUSION: This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases

Nonlinear Radiation Pressure and Stochasticity in Ultraintense Laser Fields

The radiation force on a single electron in an ultraintense plane wave ($a = eE/mc\omega \sim 1$) is calculated and shown to be proportional to $a^4$ in the high-$a$ limit for arbitrary waveform and polarization. The cyclotron motion of an electron in a constant magnetic field and an ultraintense plane wave is numerically found to be quasiperiodic even in the high-$a$ limit if the magnetic field is not too strong, as suggested by previous analytical work. A strong magnetic field causes highly chaotic electron motion and the boundary of the highly chaotic region of parameter space is determined numerically. Applications to experiments and astrophysics are briefly discussed.Comment: 5 pages, 4 figures; uses RevTex, epsf macros. Corrected, expanded versio