The plasma-insulator transition of spin-polarized Hydrogen

A mixed classical-quantum density functional theory is used to calculate pair correlations and the free energy of a spin-polarized Hydrogen plasma. A transition to an atomic insulator phase is estimated to occur around r_s=2.5 at T=10^4K, and a pressure $P\approx0.5Mbar$. Spin polarization is imposed to prevent the formation of H_2 molecules.Comment: 10 pages, 4 figure

Examining Spillover Effects from Teach For America Corps Members in Miami-Dade County Public Schools

Despite a large body of evidence documenting the effectiveness of Teach For America (TFA) corps members at raising the math test scores of their students, little is known about the program's impact at the school level. TFA's recent placement strategy in the Miami-Dade County Public Schools (M-DCPS), where large numbers of TFA corps members are placed as clusters into a targeted set of disadvantaged schools, provides an opportunity to evaluate the impact of the TFA program on broader school performance. This study examines whether the influx of TFA corps members led to a spillover effect on other teachers' performance. We find that many of the schools chosen to participate in the cluster strategy experienced large subsequent gains in math achievement. These gains were driven in part by the composition effect of having larger numbers of effective TFA corps members. However, we do not find any evidence that the clustering strategy led to any spillover effect on school-wide performance. In other words, our estimates suggest that extra student gains for TFA corps members under the clustering strategy would be equivalent to the gains that would result from an alternate placement strategy where corps members were evenly distributed across schools

Near-Optimal Detection in MIMO Systems using Gibbs Sampling

In this paper we study a Markov Chain Monte Carlo (MCMC) Gibbs sampler for solving the integer least-squares problem. In digital communication the problem is equivalent to performing Maximum Likelihood (ML) detection in Multiple-Input Multiple-Output (MIMO) systems. While the use of MCMC methods for such problems has already been proposed, our method is novel in that we optimize the "temperature" parameter so that in steady state, i.e. after the Markov chain has mixed, there is only polynomially (rather than exponentially) small probability of encountering the optimal solution. More precisely, we obtain the largest value of the temperature parameter for this to occur, since the higher the temperature, the faster the mixing. This is in contrast to simulated annealing techniques where, rather than being held fixed, the temperature parameter is tended to zero. Simulations suggest that the resulting Gibbs sampler provides a computationally efficient way of achieving approximative ML detection in MIMO systems having a huge number of transmit and receive dimensions. In fact, they further suggest that the Markov chain is rapidly mixing. Thus, it has been observed that even in cases were ML detection using, e.g. sphere decoding becomes infeasible, the Gibbs sampler can still offer a near-optimal solution using much less computations.Comment: To appear in Globecom 200

Stabilization of nonlinear velocity profiles in athermal systems undergoing planar shear flow

We perform molecular dynamics simulations of model granular systems undergoing boundary-driven planar shear flow in two spatial dimensions with the goal of developing a more complete understanding of how dense particulate systems respond to applied shear. In particular, we are interested in determining when these systems will possess linear velocity profiles and when they will develop highly localized velocity profiles in response to shear. In previous work on similar systems we showed that nonlinear velocity profiles form when the speed of the shearing boundary exceeds the speed of shear waves in the material. However, we find that nonlinear velocity profiles in these systems are unstable at very long times. The degree of nonlinearity slowly decreases in time; the velocity profiles become linear when the granular temperature and density profiles are uniform across the system at long times. We measure the time $t_l$ required for the velocity profiles to become linear and find that $t_l$ increases as a power-law with the speed of the shearing boundary and increases rapidly as the packing fraction approaches random close packing. We also performed simulations in which differences in the granular temperature across the system were maintained by vertically vibrating one of the boundaries during shear flow. We find that nonlinear velocity profiles form and are stable at long times if the difference in the granular temperature across the system exceeds a threshold value that is comparable to the glass transition temperature in an equilibrium system at the same average density. Finally, the sheared and vibrated systems form stable shear bands, or highly localized velocity profiles, when the applied shear stress is lowered below the yield stress of the static part of the system.Comment: 11 pages, 14 figure

Microlensing pulsars

We investigate the possibilities that pulsars act as the lens in gravitational microlensing events towards the galactic bulge or a spiral arm. Our estimation is based on expectant survey and observations of FAST (Five hundred meter Aperture Spherical Telescope) and SKA (Square Kilometer Array), and two different models of pulsar distribution are used. We find that the lensing rate is > 1 event/decade, being high enough to search the real events. Therefore, the microlensing observations focusing on pulsars identified by FAST or SKA in the future are meaningful. As an independent determination of pulsar mass, a future detection of microlensing pulsars should be significant in the history of studying pulsars, especially in constraining the state of matter (either hadronic or quark matter) at supra-nuclear densities. The observations of such events by using advanced optical facilities (e.g., the James Webb Space Telescope and the Thirty Meter Telescope) in future are highly suggested.Comment: 5pages, 2figure

A Spectral Method for Elliptic Equations: The Neumann Problem

Let $\Omega$ be an open, simply connected, and bounded region in $\mathbb{R}^{d}$, $d\geq2$, and assume its boundary $\partial\Omega$ is smooth. Consider solving an elliptic partial differential equation $-\Delta u+\gamma u=f$ over $\Omega$ with a Neumann boundary condition. The problem is converted to an equivalent elliptic problem over the unit ball $B$, and then a spectral Galerkin method is used to create a convergent sequence of multivariate polynomials $u_{n}$ of degree $\leq n$ that is convergent to $u$. The transformation from $\Omega$ to $B$ requires a special analytical calculation for its implementation. With sufficiently smooth problem parameters, the method is shown to be rapidly convergent. For $u\in C^{\infty}(\overline{\Omega})$ and assuming $\partial\Omega$ is a $C^{\infty}$ boundary, the convergence of $\Vert u-u_{n}\Vert_{H^{1}}$ to zero is faster than any power of $1/n$. Numerical examples in $\mathbb{R}^{2}$ and $\mathbb{R}^{3}$ show experimentally an exponential rate of convergence.Comment: 23 pages, 11 figure

Climate Change, Water Supply, and Agriculture in the Arid Western United States: Eighty Years of Agricultural Census Observations from Idaho

As the population and agricultural development in the U.S. expanded west throughout the 20th century, major water infrastructure projects were initiated in order to meet irrigation demand and to reduce the risk and uncertainty associated with highly variable water supplies.2 Agriculture in the arid and semi-arid western U.S. is particularly vulnerable to variability in water supply, and has evolved to rely heavily on major water infrastructure projects.3 In 2007, of the 57 million acres of irrigated cropland and pastureland in the U.S., nearly three-quarters was in the 17 western-most contiguous states; in 2008, irrigated agriculture applied 91.2 million acre-feet of water, with over four-fifths being used in the arid west

The asymptotic tails of limit distributions of continuous time Markov chains

This paper investigates tail asymptotics of stationary distributions and quasi-stationary distributions of continuous-time Markov chains on a subset of the non-negative integers. A new identity for stationary measures is established. In particular, for continuous-time Markov chains with asymptotic power-law transition rates, tail asymptotics for stationary distributions are classified into three types by three easily computable parameters: (i) Conley-Maxwell-Poisson distributions (light-tailed), (ii) exponential-tailed distributions, and (iii) heavy-tailed distributions. Similar results are derived for quasi-stationary distributions. The approach to establish tail asymptotics is different from the classical semimartingale approach. We apply our results to biochemical reaction networks (modeled as continuous-time Markov chains), a general single-cell stochastic gene expression model, an extended class of branching processes, and stochastic population processes with bursty reproduction, none of which are birth-death processes