4,163 research outputs found
Entanglement and quantum combinatorial designs
We introduce several classes of quantum combinatorial designs, namely quantum
Latin squares, cubes, hypercubes and a notion of orthogonality between them. A
further introduced notion, quantum orthogonal arrays, generalizes all previous
classes of designs. We show that mutually orthogonal quantum Latin arrangements
can be entangled in the same way than quantum states are entangled.
Furthermore, we show that such designs naturally define a remarkable class of
genuinely multipartite highly entangled states called -uniform, i.e.
multipartite pure states such that every reduction to parties is maximally
mixed. We derive infinitely many classes of mutually orthogonal quantum Latin
arrangements and quantum orthogonal arrays having an arbitrary large number of
columns. The corresponding multipartite -uniform states exhibit a high
persistency of entanglement, which makes them ideal candidates to develop
multipartite quantum information protocols.Comment: 14 pages, 3 figures. Comments are very welcome
Uncovering ED: A Qualitative Analysis of Personal Blogs Managed by Individuals with Eating Disorders
Previous studies have investigated the potential harmful effects of pro-eating disorder (ED) websites. Websites, such as personal blogs, may contain eating disorder content that may hold important information as well and must be considered. Fifteen blogs hosted by the site âTumblrâ were qualitatively analyzed. Each blog owner was anonymous and all were female. Ten main themes were extracted using grounded theory: interaction, negative self-worth, mind and body disturbances, pictures, eating disorders, suicide, diet, exercise, stats, and recovery. Additional themes also appeared in the study. Results indicate that although each individual blog is unique to its owner, common concepts existed among the majority. The implications for the information in the ED blogs and directions for future research are discussed
A Qualitative Exploration of Emerging Adultsâ and Parentsâ Perspectives on Communicating Adulthood Status
In this study the authors examine parent - child communication in Emerging Adulthood. Thirty - seven college students and one or both of their parents completed written questionnaires assessing whether the parent had verbally communicated or did some action to acknowledge the Emerging Adultâs maturity. Communication about changes in the parent - child relationship, as well as the Emerging Adultâs decision - making abilities, obligations to the family, and financial responsibilities were also assessed. The responses to the open ended questions were qualitatively analyzed using grounded theory. The findings indicated that the Emerging Adultsâ and parentsâ responses were very similar, and the overwhelming majority reported that there had indeed been an acknowledgment from the parents to indicate Emerging Adulthood status, although this was not always verbally communicated; sometimes it was indicated through the parentsâ behavior.
Fast spatial simulation of extreme high-resolution radar precipitation data using INLA
We develop a methodology for modelling and simulating high-dimensional
spatial precipitation extremes, using a combination of the spatial conditional
extremes model, latent Gaussian models and integrated nested Laplace
approximations (INLA). The spatial conditional extremes model requires data
with Laplace marginal distributions, but precipitation distributions contain
point masses at zero that complicate necessary standardisation procedures. We
propose to model conditional extremes of nonzero precipitation only, while
separately modelling precipitation occurrences. The two models are then
combined to create a complete model for extreme precipitation. Nonzero
precipitation marginals are modelled using a combination of latent Gaussian
models with gamma and generalised Pareto likelihoods. Four different models for
precipitation occurrence are investigated. New empirical diagnostics and
parametric models are developed for describing components of the spatial
conditional extremes model. We apply our framework to simulate spatial
precipitation extremes over a water catchment in Central Norway, using
high-density radar data. Inference on a 6000-dimensional data set is performed
within hours, and the simulated data capture the main trends of the observed
data well
Introduction A Hellenic Modernism: Greek Theatre and Italian Fascism
The introduction to the special issue explores the central place of Greek theatre within the culture of Italian Fascism. Building on scholarship from the so-called cultural turn in the study of fascism, which variously identified fascism with a form of modernism, it demonstrates that a dialogue between modernism and classicism was fully at work in the performances of ancient drama occurring all over the Italian peninsula and in the colonies in North Africa. The term âHellenic modernismâ is introduced here to underline the fusion of Greek theatre with distinctively modernist traits during the ventennio and provide an analytical tool for investigating the role of classical performances and spectacles within Fascismâs programme of cultural and national renewal
An Efficient Workflow for Modelling High-Dimensional Spatial Extremes
A successful model for high-dimensional spatial extremes should, in
principle, be able to describe both weakening extremal dependence at increasing
levels and changes in the type of extremal dependence class as a function of
the distance between locations. Furthermore, the model should allow for
computationally tractable inference using inference methods that efficiently
extract information from data and that are robust to model misspecification. In
this paper, we demonstrate how to fulfil all these requirements by developing a
comprehensive methodological workflow for efficient Bayesian modelling of
high-dimensional spatial extremes using the spatial conditional extremes model
while performing fast inference with R-INLA. We then propose a post hoc
adjustment method that results in more robust inference by properly accounting
for possible model misspecification. The developed methodology is applied for
modelling extreme hourly precipitation from high-resolution radar data in
Norway. Inference is computationally efficient, and the resulting model fit
successfully captures the main trends in the extremal dependence structure of
the data. Robustifying the model fit by adjusting for possible misspecification
further improves model performance
A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations
Measurement error (ME) and missing values in covariates are often unavoidable
in disciplines that deal with data, and both problems have separately received
considerable attention during the past decades. However, while most researchers
are familiar with methods for treating missing data, accounting for ME in
covariates of regression models is less common. In addition, ME and missing
data are typically treated as two separate problems, despite practical and
theoretical similarities. Here, we exploit the fact that missing data in a
continuous covariate is an extreme case of classical ME, allowing us to use
existing methodology that accounts for ME via a Bayesian framework that employs
integrated nested Laplace approximations (INLA), and thus to simultaneously
account for both ME and missing data in the same covariate. As a useful
by-product, we present an approach to handle missing data in INLA, since this
corresponds to the special case when no ME is present. In addition, we show how
to account for Berkson ME in the same framework. In its broadest generality,
the proposed joint Bayesian framework can thus account for Berkson ME,
classical ME, and missing data, or for any combination of these in the same or
different continuous covariates of the family of regression models that are
feasible with INLA. The approach is exemplified using both simulated and real
data. We provide extensive and fully reproducible Supplementary Material with
thoroughly documented examples using {R-INLA} and {inlabru}
Feynman graphs and the large dimensional limit of multipartite entanglement
We are interested in the properties of multipartite entanglement of a system
composed by -level parties (qudits).
Focussing our attention on pure states we want to tackle the problem of the
maximization of the entanglement for such systems. In particular we effort the
problem trying to minimize the purity of the system. It has been shown that not
for all systems this function can reach its lower bound, however it can be
proved that for all values of a can always be found such that the lower
bound can be reached.
In this paper we examine the high-temperature expansion of the distribution
function of the bipartite purity over all balanced bipartition considering its
optimization problem as a problem of statistical mechanics. In particular we
prove that the series characterizing the expansion converges and we analyze the
behavior of each term of the series as .Comment: 29 pages, 11 figure
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