Localization and interactions in topological and non-topological bands in two dimensions

A two-dimensional electron gas in a high magnetic field displays macroscopically degenerate Landau levels, which can be split into Hofstadter subbands by means of a weak periodic potential. By carefully engineering such a potential, one can precisely tune the number, bandwidths, bandgaps and Chern character of these subbands. This allows a detailed study of the interplay of disorder, interaction and topology in two dimensional systems. We first explore the physics of disorder and single-particle localization in subbands derived from the lowest Landau level, that nevertheless may have a topological nature different from that of the entire lowest Landau level. By projecting the Hamiltonian onto subbands of interest, we systematically explore the localization properties of single-particle eigenstates in the presence of quenched disorder. We then introduce electron-electron interactions and investigate the fate of many-body localization in subbands of varying topological character

Asymptotic analysis and spectrum of three anyons

The spectrum of anyons confined in harmonic oscillator potential shows both linear and nonlinear dependence on the statistical parameter. While the existence of exact linear solutions have been shown analytically, the nonlinear dependence has been arrived at by numerical and/or perturbative methods. We develop a method which shows the possibility of nonlinearly interpolating spectrum. To be specific we analyse the eigenvalue equation in various asymptotic regions for the three anyon problem.Comment: 28 pages, LaTeX, 2 Figure

Effect of Hilbert space truncation on Anderson localization

The 1-D Anderson model possesses a completely localized spectrum of eigenstates for all values of the disorder. We consider the effect of projecting the Hamiltonian to a truncated Hilbert space, destroying time reversal symmetry. We analyze the ensuing eigenstates using different measures such as inverse participation ratio and sample-averaged moments of the position operator. In addition, we examine amplitude fluctuations in detail to detect the possibility of multifractal behavior (characteristic of mobility edges) that may arise as a result of the truncation procedure.Comment: 20 pages, 23 figure

Queue Length Asymptotics for Generalized Max-Weight Scheduling in the presence of Heavy-Tailed Traffic

We investigate the asymptotic behavior of the steady-state queue length distribution under generalized max-weight scheduling in the presence of heavy-tailed traffic. We consider a system consisting of two parallel queues, served by a single server. One of the queues receives heavy-tailed traffic, and the other receives light-tailed traffic. We study the class of throughput optimal max-weight-alpha scheduling policies, and derive an exact asymptotic characterization of the steady-state queue length distributions. In particular, we show that the tail of the light queue distribution is heavier than a power-law curve, whose tail coefficient we obtain explicitly. Our asymptotic characterization also contains an intuitively surprising result - the celebrated max-weight scheduling policy leads to the worst possible tail of the light queue distribution, among all non-idling policies. Motivated by the above negative result regarding the max-weight-alpha policy, we analyze a log-max-weight (LMW) scheduling policy. We show that the LMW policy guarantees an exponentially decaying light queue tail, while still being throughput optimal

Test of Convergence in Agricultural Factor Productivity: A Semiparametric Approach

We tested for club convergence in U.S. agricultural total factory productivity using a sigma convergence test. We used the same club of states as used by McCunn and Huffman as well as different states within 10 clubs identified by the cluster analysis. Results showed convergence was evident only in a few club groups. Clusters group identified using a statistical method identified only converging clubs. Variables affecting total factor productivity among states were identified using parametric, semiparametric and nonparametric methods. Semiparametric and nonparametric methods gave a better fit than a parametric method as indicated by the specification test. Our results indicated that health care expenditure, public research and extension investment, and private expenditure are important variables impacting total factor productivity differences across states.Clubs, sigma convergence, cluster analysis, semiparametric and nonparametric methods, Productivity Analysis, Research Methods/ Statistical Methods,