327,827 research outputs found
Partial Teleportation of Entanglement in the Noisy Environment
Partial teleportation of entanglement is to teleport one particle of an
entangled pair through a quantum channel. This is conceptually equivalent to
quantum swapping. We consider the partial teleportation of entanglement in the
noisy environment, employing the Werner-state representation of the noisy
channel for the simplicity of calculation. To have the insight of the many-body
teleportation, we introduce the measure of correlation information and study
the transfer of the correlation information and entanglement. We find that the
fidelity gets smaller as the initial-state is entangled more for a given
entanglement of the quantum channel. The entangled channel transfers at least
some of the entanglement to the final state.Comment: 8 pages, 2 figure
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets
This paper introduces new algorithms and data structures for quick counting
for machine learning datasets. We focus on the counting task of constructing
contingency tables, but our approach is also applicable to counting the number
of records in a dataset that match conjunctive queries. Subject to certain
assumptions, the costs of these operations can be shown to be independent of
the number of records in the dataset and loglinear in the number of non-zero
entries in the contingency table. We provide a very sparse data structure, the
ADtree, to minimize memory use. We provide analytical worst-case bounds for
this structure for several models of data distribution. We empirically
demonstrate that tractably-sized data structures can be produced for large
real-world datasets by (a) using a sparse tree structure that never allocates
memory for counts of zero, (b) never allocating memory for counts that can be
deduced from other counts, and (c) not bothering to expand the tree fully near
its leaves. We show how the ADtree can be used to accelerate Bayes net
structure finding algorithms, rule learning algorithms, and feature selection
algorithms, and we provide a number of empirical results comparing ADtree
methods against traditional direct counting approaches. We also discuss the
possible uses of ADtrees in other machine learning methods, and discuss the
merits of ADtrees in comparison with alternative representations such as
kd-trees, R-trees and Frequent Sets.Comment: See http://www.jair.org/ for any accompanying file
Iterated smoothed bootstrap confidence intervals for population quantiles
This paper investigates the effects of smoothed bootstrap iterations on
coverage probabilities of smoothed bootstrap and bootstrap-t confidence
intervals for population quantiles, and establishes the optimal kernel
bandwidths at various stages of the smoothing procedures. The conventional
smoothed bootstrap and bootstrap-t methods have been known to yield one-sided
coverage errors of orders O(n^{-1/2}) and o(n^{-2/3}), respectively, for
intervals based on the sample quantile of a random sample of size n. We sharpen
the latter result to O(n^{-5/6}) with proper choices of bandwidths at the
bootstrapping and Studentization steps. We show further that calibration of the
nominal coverage level by means of the iterated bootstrap succeeds in reducing
the coverage error of the smoothed bootstrap percentile interval to the order
O(n^{-2/3}) and that of the smoothed bootstrap-t interval to O(n^{-58/57}),
provided that bandwidths are selected of appropriate orders. Simulation results
confirm our asymptotic findings, suggesting that the iterated smoothed
bootstrap-t method yields the most accurate coverage. On the other hand, the
iterated smoothed bootstrap percentile method interval has the advantage of
being shorter and more stable than the bootstrap-t intervals.Comment: Published at http://dx.doi.org/10.1214/009053604000000878 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Instanton solutions mediating tunneling between the degenerate vacua in curved space
We investigate the instanton solution between the degenerate vacua in curved
space. We show that there exist -symmetric solutions not only in de
Sitter but also in both flat and anti-de Sitter space. The geometry of the new
type of solutions is finite and preserves the symmetry. The nontrivial
solution corresponding to the tunneling is possible only if gravity is taken
into account. The numerical solutions as well as the analytic computations
using the thin-wall approximation are presented. We expect that these solutions
do not have any negative mode as in the instanton solution.Comment: Some typos are corrected and references are added with respect to the
published version. 17pages, 11fi
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Serial persistence in individual real estate returns in the UK
Persistence of property returns is a topic of perennial interest to fund managers as it suggests that choosing those properties that will perform well in the future is as simple as looking at those that performed well in the past. Consequently, much effort has been expended to determine if such a rule exists in the real estate market. This paper extends earlier studies in US, Australian, and UK markets in two ways. First, this study applies the same methodology originally used in Young and Graff (1996) making the results directly comparable with those in the US and Australian property markets. Second, this study uses a much longer and larger database covering all commercial property data available from the Investment Property Databank (IPD), for the years 1981 to 2002 for as many as 216,758 individual property returns. While the performance results of this study mimic the US and Australian results of greater persistence in the extreme first and fourth quartiles, they also evidence persistence in the moderate second and third quartiles, a notable departure from previous studies. Likewise patterns across property type, location, time, and holding period are remarkably similar leading to the conjecture that behaviors in the practice of commercial real estate investment management are themselves deeply rooted and persistent and perhaps influenced for good or ill by agency effect
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