Negative Specific Heat in a Quasi-2D Generalized Vorticity Model

Negative specific heat is a dramatic phenomenon where processes decrease in temperature when adding energy. It has been observed in gravo-thermal collapse of globular clusters. We now report finding this phenomenon in bundles of nearly parallel, periodic, single-sign generalized vortex filaments in the electron magnetohydrodynamic (EMH) model for the unbounded plane under strong magnetic confinement. We derive the specific heat using a steepest descent method and a mean field property. Our derivations show that as temperature increases, the overall size of the system increases exponentially and the energy drops. The implication of negative specific heat is a runaway reaction, resulting in a collapsing inner core surrounded by an expanding halo of filaments.Comment: 12 pages, 3 figures; updated with revision

StakeSource: harnessing the power of crowdsourcing and social networks in stakeholder analysis

Projects often fail because they overlook stakeholders. Unfortunately, existing stakeholder analysis tools only capture stakeholders' information, relying on experts to manually identify them. StakeSource is a web-based tool that automates stakeholder analysis. It "crowdsources" the stakeholders themselves for recommendations about other stakeholders and aggregates their answers using social network analysis

Many-body localization and mobility edge in a disordered Heisenberg spin ladder

We examine the interplay of interaction and disorder for a Heisenberg spin ladder system with random fields. We identify many-body localized states based on the entanglement entropy scaling, where delocalized and localized states have volume and area laws, respectively. We first establish the quantum phase transition at a critical random field strength $h_c \sim 8.5\pm 0.5$, where all energy eigenstates are localized beyond that value. Interestingly, the entanglement entropy and fluctuation of the bipartite magnetization show distinct probability distributions which characterize different quantum phases. Furthermore, we show that for weaker $h$, energy eigenstates with higher energy density are delocalized while states at lower energy density are localized. This defines a mobility edge and a mobility gap separating these two phases. By following the evolution of low energy eigenstates, we observe that the mobility gap grows with increasing the random field strength, which drives the system to the phase of the full many-body localization with increasing disorder strength.Comment: 6 pages, 4 figure

Intensity correlations and entanglement by frequency doubling in a dual ported resonator

We show that non-classical intensity correlations and quadrature entanglement can be generated by frequency doubling in a resonator with two output ports. We predict twin-beam intensity correlations 6 dB below the coherent state limit, and that the product of the inference variances of the quadrature fluctuations gives an Einstein-Podolsky-Rosen (EPR) correlation coefficient of V_EPR = 0.6 < 1. Comparison with an entanglement source based on combining two frequency doublers with a beam splitter shows that the dual ported resonator provides stronger entanglement at lower levels of individual beam squeezing. Calculations are performed using a self-consistent propagation method that does not invoke a mean field approximation. Results are given for physically realistic parameters that account for the Gaussian shape of the intracavity beams, as well as intracavity losses.Comment: 12 pages, 9 figures, normalization corrected, fig 3 and fig 7 update

Convex relaxation of mixture regression with efficient algorithms

We develop a convex relaxation of maximum a posteriori estimation of a mixture of regression models. Although our relaxation involves a semidefinite matrix variable, we reformulate the problem to eliminate the need for general semidefinite programming. In particular, we provide two reformulations that admit fast algorithms. The first is a max-min spectral reformulation exploiting quasi-Newton descent. The second is a min-min reformulation consisting of fast alternating steps of closed-form updates. We evaluate the methods against Expectation-Maximization in a real problem of motion segmentation from video data

Measuring the Impact of Living Wage Laws: A Critical Appraisal of David Neumark's How Living Wage Laws Affect Low-Wage Workers and Low-Income Families

Drawing on data from the Current Population Survey (CPS), David Neumark (2002) finds that living wage laws have brought substantial wage increases for a high proportion of workers in cities that have passed these laws. He also finds that living wage laws significantly reduce employment opportunities for low-wage workers. We argue, first, that by truncating his sample to concentrate his analysis on low-wage workers, Neumark’s analysis is vulnerable to sample selection bias, and that his results are not robust to alternative specifications that utilize quantile regression to avoid such selection bias. In addition, we argue that Neumark has erroneously utilized the CPS data set to derive these results. We show that, with respect to both wage and employment effects, Neumark’s results are not robust to more accurate alternative classifications as to which workers are covered by living wage laws. We also show that the wage effects that Neumark observes for all U.S. cities with living wage laws can be more accurately explained as resulting from effects on sub-minimum wage workers in Los Angeles alone of a falling unemployment rate and rising minimum wage in that city.

StakeNet: using social networks to analyse the stakeholders of large-scale software projects

Many software projects fail because they overlook stakeholders or involve the wrong representatives of significant groups. Unfortunately, existing methods in stakeholder analysis are likely to omit stakeholders, and consider all stakeholders as equally influential. To identify and prioritise stakeholders, we have developed StakeNet, which consists of three main steps: identify stakeholders and ask them to recommend other stakeholders and stakeholder roles, build a social network whose nodes are stakeholders and links are recommendations, and prioritise stakeholders using a variety of social network measures. To evaluate StakeNet, we conducted one of the first empirical studies of requirements stakeholders on a software project for a 30,000-user system. Using the data collected from surveying and interviewing 68 stakeholders, we show that StakeNet identifies stakeholders and their roles with high recall, and accurately prioritises them. StakeNet uncovers a critical stakeholder role overlooked in the project, whose omission significantly impacted project success