2,172 research outputs found

    A Super-Fast Distributed Algorithm for Bipartite Metric Facility Location

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    The \textit{facility location} problem consists of a set of \textit{facilities} F\mathcal{F}, a set of \textit{clients} C\mathcal{C}, an \textit{opening cost} fif_i associated with each facility xix_i, and a \textit{connection cost} D(xi,yj)D(x_i,y_j) between each facility xix_i and client yjy_j. The goal is to find a subset of facilities to \textit{open}, and to connect each client to an open facility, so as to minimize the total facility opening costs plus connection costs. This paper presents the first expected-sub-logarithmic-round distributed O(1)-approximation algorithm in the CONGEST\mathcal{CONGEST} model for the \textit{metric} facility location problem on the complete bipartite network with parts F\mathcal{F} and C\mathcal{C}. Our algorithm has an expected running time of O((log⁥log⁥n)3)O((\log \log n)^3) rounds, where n=∣F∣+∣C∣n = |\mathcal{F}| + |\mathcal{C}|. This result can be viewed as a continuation of our recent work (ICALP 2012) in which we presented the first sub-logarithmic-round distributed O(1)-approximation algorithm for metric facility location on a \textit{clique} network. The bipartite setting presents several new challenges not present in the problem on a clique network. We present two new techniques to overcome these challenges. (i) In order to deal with the problem of not being able to choose appropriate probabilities (due to lack of adequate knowledge), we design an algorithm that performs a random walk over a probability space and analyze the progress our algorithm makes as the random walk proceeds. (ii) In order to deal with a problem of quickly disseminating a collection of messages, possibly containing many duplicates, over the bipartite network, we design a probabilistic hashing scheme that delivers all of the messages in expected-O(log⁥log⁥n)O(\log \log n) rounds.Comment: 22 pages. This is the full version of a paper that appeared in DISC 201

    Quantum Phase Tomography of a Strongly Driven Qubit

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    The interference between repeated Landau-Zener transitions in a qubit swept through an avoided level crossing results in Stueckelberg oscillations in qubit magnetization. The resulting oscillatory patterns are a hallmark of the coherent strongly-driven regime in qubits, quantum dots and other two-level systems. The two-dimensional Fourier transforms of these patterns are found to exhibit a family of one-dimensional curves in Fourier space, in agreement with recent observations in a superconducting qubit. We interpret these images in terms of time evolution of the quantum phase of qubit state and show that they can be used to probe dephasing mechanisms in the qubit.Comment: 5 pgs, 4 fg

    Lessons from the Congested Clique Applied to MapReduce

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    The main results of this paper are (I) a simulation algorithm which, under quite general constraints, transforms algorithms running on the Congested Clique into algorithms running in the MapReduce model, and (II) a distributed O(Δ)O(\Delta)-coloring algorithm running on the Congested Clique which has an expected running time of (i) O(1)O(1) rounds, if Δ≄Θ(log⁥4n)\Delta \geq \Theta(\log^4 n); and (ii) O(log⁥log⁥n)O(\log \log n) rounds otherwise. Applying the simulation theorem to the Congested-Clique O(Δ)O(\Delta)-coloring algorithm yields an O(1)O(1)-round O(Δ)O(\Delta)-coloring algorithm in the MapReduce model. Our simulation algorithm illustrates a natural correspondence between per-node bandwidth in the Congested Clique model and memory per machine in the MapReduce model. In the Congested Clique (and more generally, any network in the CONGEST\mathcal{CONGEST} model), the major impediment to constructing fast algorithms is the O(log⁥n)O(\log n) restriction on message sizes. Similarly, in the MapReduce model, the combined restrictions on memory per machine and total system memory have a dominant effect on algorithm design. In showing a fairly general simulation algorithm, we highlight the similarities and differences between these models.Comment: 15 page

    Reactions to uncertainty and the accuracy of diagnostic mammography.

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    BackgroundReactions to uncertainty in clinical medicine can affect decision making.ObjectiveTo assess the extent to which radiologists' reactions to uncertainty influence diagnostic mammography interpretation.DesignCross-sectional responses to a mailed survey assessed reactions to uncertainty using a well-validated instrument. Responses were linked to radiologists' diagnostic mammography interpretive performance obtained from three regional mammography registries.ParticipantsOne hundred thirty-two radiologists from New Hampshire, Colorado, and Washington.MeasurementMean scores and either standard errors or confidence intervals were used to assess physicians' reactions to uncertainty. Multivariable logistic regression models were fit via generalized estimating equations to assess the impact of uncertainty on diagnostic mammography interpretive performance while adjusting for potential confounders.ResultsWhen examining radiologists' interpretation of additional diagnostic mammograms (those after screening mammograms that detected abnormalities), a 5-point increase in the reactions to uncertainty score was associated with a 17% higher odds of having a positive mammogram given cancer was diagnosed during follow-up (sensitivity), a 6% lower odds of a negative mammogram given no cancer (specificity), a 4% lower odds (not significant) of a cancer diagnosis given a positive mammogram (positive predictive value [PPV]), and a 5% higher odds of having a positive mammogram (abnormal interpretation).ConclusionMammograms interpreted by radiologists who have more discomfort with uncertainty have higher likelihood of being recalled

    Search for axion-like particles using a variable baseline photon regeneration technique

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    We report the first results of the GammeV experiment, a search for milli-eV mass particles with axion-like couplings to two photons. The search is performed using a "light shining through a wall" technique where incident photons oscillate into new weakly interacting particles that are able to pass through the wall and subsequently regenerate back into detectable photons. The oscillation baseline of the apparatus is variable, thus allowing probes of different values of particle mass. We find no excess of events above background and are able to constrain the two-photon couplings of possible new scalar (pseudoscalar) particles to be less than 3.1x10^{-7} GeV^{-1} (3.5x10^{-7} GeV^{-1}) in the limit of massless particles.Comment: 5 pages, 4 figures. This is the version accepted by PRL and includes updated limit

    Expressivity of parameterized and data-driven representations in quality diversity search

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    Algorithms and the Foundations of Software technolog

    On Convergence of the Inexact Rayleigh Quotient Iteration with the Lanczos Method Used for Solving Linear Systems

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    For the Hermitian inexact Rayleigh quotient iteration (RQI), the author has established new local general convergence results, independent of iterative solvers for inner linear systems. The theory shows that the method locally converges quadratically under a new condition, called the uniform positiveness condition. In this paper we first consider the local convergence of the inexact RQI with the unpreconditioned Lanczos method for the linear systems. Some attractive properties are derived for the residuals, whose norms are Οk+1\xi_{k+1}'s, of the linear systems obtained by the Lanczos method. Based on them and the new general convergence results, we make a refined analysis and establish new local convergence results. It is proved that the inexact RQI with Lanczos converges quadratically provided that Οk+1≀Ο\xi_{k+1}\leq\xi with a constant Ο≄1\xi\geq 1. The method is guaranteed to converge linearly provided that Οk+1\xi_{k+1} is bounded by a small multiple of the reciprocal of the residual norm ∄rk∄\|r_k\| of the current approximate eigenpair. The results are fundamentally different from the existing convergence results that always require Οk+1<1\xi_{k+1}<1, and they have a strong impact on effective implementations of the method. We extend the new theory to the inexact RQI with a tuned preconditioned Lanczos for the linear systems. Based on the new theory, we can design practical criteria to control Οk+1\xi_{k+1} to achieve quadratic convergence and implement the method more effectively than ever before. Numerical experiments confirm our theory.Comment: 20 pages, 8 figures. arXiv admin note: text overlap with arXiv:0906.223
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