14,126 research outputs found

    Slow Dynamics in a Two-Dimensional Anderson-Hubbard Model

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    We study the real-time dynamics of a two-dimensional Anderson--Hubbard model using nonequilibrium self-consistent perturbation theory within the second-Born approximation. When compared with exact diagonalization performed on small clusters, we demonstrate that for strong disorder this technique approaches the exact result on all available timescales, while for intermediate disorder, in the vicinity of the many-body localization transition, it produces quantitatively accurate results up to nontrivial times. Our method allows for the treatment of system sizes inaccessible by any numerically exact method and for the complete elimination of finite size effects for the times considered. We show that for a sufficiently strong disorder the system becomes nonergodic, while for intermediate disorder strengths and for all accessible time scales transport in the system is strictly subdiffusive. We argue that these results are incompatible with a simple percolation picture, but are consistent with the heuristic random resistor network model where subdiffusion may be observed for long times until a crossover to diffusion occurs. The prediction of slow finite-time dynamics in a two-dimensional interacting and disordered system can be directly verified in future cold atoms experimentsComment: Title change and minor changes in the tex

    Randomized Algorithms for the Loop Cutset Problem

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    We show how to find a minimum weight loop cutset in a Bayesian network with high probability. Finding such a loop cutset is the first step in the method of conditioning for inference. Our randomized algorithm for finding a loop cutset outputs a minimum loop cutset after O(c 6^k kn) steps with probability at least 1 - (1 - 1/(6^k))^c6^k, where c > 1 is a constant specified by the user, k is the minimal size of a minimum weight loop cutset, and n is the number of vertices. We also show empirically that a variant of this algorithm often finds a loop cutset that is closer to the minimum weight loop cutset than the ones found by the best deterministic algorithms known

    True covariance simulation of the EUVE update filter

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    A covariance analysis of the performance and sensitivity of the attitude determination Extended Kalman Filter (EKF) used by the On Board Computer (OBC) of the Extreme Ultra Violet Explorer (EUVE) spacecraft is presented. The linearized dynamics and measurement equations of the error states are derived which constitute the truth model describing the real behavior of the systems involved. The design model used by the OBC EKF is then obtained by reducing the order of the truth model. The covariance matrix of the EKF which uses the reduced order model is not the correct covariance of the EKF estimation error. A true covariance analysis has to be carried out in order to evaluate the correct accuracy of the OBC generated estimates. The results of such analysis are presented which indicate both the performance and the sensitivity of the OBC EKF

    Longitudinal flying qualities criteria for single-pilot instrument flight operations

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    Modern estimation and control theory, flight testing, and statistical analysis were used to deduce flying qualities criteria for General Aviation Single Pilot Instrument Flight Rule (SPIFR) operations. The principal concern is that unsatisfactory aircraft dynamic response combined with high navigation/communication workload can produce problems of safety and efficiency. To alleviate these problems. The relative importance of these factors must be determined. This objective was achieved by flying SPIFR tasks with different aircraft dynamic configurations and assessing the effects of such variations under these conditions. The experimental results yielded quantitative indicators of pilot's performance and workload, and for each of them, multivariate regression was applied to evaluate several candidate flying qualities criteria

    Fast Structuring of Radio Networks for Multi-Message Communications

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    We introduce collision free layerings as a powerful way to structure radio networks. These layerings can replace hard-to-compute BFS-trees in many contexts while having an efficient randomized distributed construction. We demonstrate their versatility by using them to provide near optimal distributed algorithms for several multi-message communication primitives. Designing efficient communication primitives for radio networks has a rich history that began 25 years ago when Bar-Yehuda et al. introduced fast randomized algorithms for broadcasting and for constructing BFS-trees. Their BFS-tree construction time was O(Dlog2n)O(D \log^2 n) rounds, where DD is the network diameter and nn is the number of nodes. Since then, the complexity of a broadcast has been resolved to be TBC=Θ(DlognD+log2n)T_{BC} = \Theta(D \log \frac{n}{D} + \log^2 n) rounds. On the other hand, BFS-trees have been used as a crucial building block for many communication primitives and their construction time remained a bottleneck for these primitives. We introduce collision free layerings that can be used in place of BFS-trees and we give a randomized construction of these layerings that runs in nearly broadcast time, that is, w.h.p. in TLay=O(DlognD+log2+ϵn)T_{Lay} = O(D \log \frac{n}{D} + \log^{2+\epsilon} n) rounds for any constant ϵ>0\epsilon>0. We then use these layerings to obtain: (1) A randomized algorithm for gathering kk messages running w.h.p. in O(TLay+k)O(T_{Lay} + k) rounds. (2) A randomized kk-message broadcast algorithm running w.h.p. in O(TLay+klogn)O(T_{Lay} + k \log n) rounds. These algorithms are optimal up to the small difference in the additive poly-logarithmic term between TBCT_{BC} and TLayT_{Lay}. Moreover, they imply the first optimal O(nlogn)O(n \log n) round randomized gossip algorithm

    Proposing "b-Parity" - a New Approximate Quantum Number in Inclusive b-jet Production - as an Efficient Probe of New Flavor Physics

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    We consider the inclusive reaction \ell^+ \ell^- -> nb +X (n = number of b-jets) in lepton colliders for which we propose a useful approximately conserved quantum number b_P=(-1)^n that we call b-Parity (b_P). We make the observation that the Standard Model (SM) is essentially b_P-even since SM b_P-violating signals are necessarily CKM suppressed. In contrast new flavor physics can produce b_P=-1 signals whose only significant SM background is due to b-jet misidentification. Thus, we show that b-jet counting, which relies primarily on b-tagging, becomes a very simple and sensitive probe of new flavor physics (i.e., of b_P-violation).Comment: 5 pages using revtex, 2 figures embadded in the text using epsfig. As will appear in Phys.Rev.Lett.. Considerable improvement was made in the background calculation as compared to version 1, by including purity parameters, QCD effects and 4-jets processe

    Spectral Analysis and the Dynamic Response of Complex Networks

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    The eigenvalues and eigenvectors of the connectivity matrix of complex networks contain information about its topology and its collective behavior. In particular, the spectral density ρ(λ)\rho(\lambda) of this matrix reveals important network characteristics: random networks follow Wigner's semicircular law whereas scale-free networks exhibit a triangular distribution. In this paper we show that the spectral density of hierarchical networks follow a very different pattern, which can be used as a fingerprint of modularity. Of particular importance is the value ρ(0)\rho(0), related to the homeostatic response of the network: it is maximum for random and scale free networks but very small for hierarchical modular networks. It is also large for an actual biological protein-protein interaction network, demonstrating that the current leading model for such networks is not adequate.Comment: 4 pages 14 figure

    An analytically solvable model of probabilistic network dynamics

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    We present a simple model of network dynamics that can be solved analytically for uniform networks. We obtain the dynamics of response of the system to perturbations. The analytical solution is an excellent approximation for random networks. A comparison with the scale-free network, though qualitatively similar, shows the effect of distinct topology.Comment: 4 pages, 1 figur
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