Quantum correlations from Brownian diffusion of chaotic level-spacings

Quantum chaos is linked to Brownian diffusion of the underlying quantum energy level-spacing sequences. The level-spacings viewed as functions of their order execute random walks which imply uncorrelated random increments of the level-spacings while the integrability to chaos transition becomes a change from Poisson to Gauss statistics for the level-spacing increments. This universal nature of quantum chaotic spectral correlations is numerically demonstrated for eigenvalues from random tight binding lattices and for zeros of the Riemann zeta function.Comment: 4 pages, revtex file, 4 postscript file

Kernel density classification and boosting: an L2 sub analysis

Kernel density estimation is a commonly used approach to classification. However, most of the theoretical results for kernel methods apply to estimation per se and not necessarily to classification. In this paper we show that when estimating the difference between two densities, the optimal smoothing parameters are increasing functions of the sample size of the complementary group, and we provide a small simluation study which examines the relative performance of kernel density methods when the final goal is classification. A relative newcomer to the classification portfolio is “boosting”, and this paper proposes an algorithm for boosting kernel density classifiers. We note that boosting is closely linked to a previously proposed method of bias reduction in kernel density estimation and indicate how it will enjoy similar properties for classification. We show that boosting kernel classifiers reduces the bias whilst only slightly increasing the variance, with an overall reduction in error. Numerical examples and simulations are used to illustrate the findings, and we also suggest further areas of research

Recurrent triploidy due to a failure to complete maternal meiosis II: whole-exome sequencing reveals candidate variants

Triploidy is a relatively common cause of miscarriage; however, recurrent triploidy has rarely been reported. A healthy 34-year-old woman was ascertained because of 18 consecutive miscarriages with triploidy found in all 5 karyotyped losses. Molecular results in a sixth loss were also consistent with triploidy. Genotyping of markers near the centromere on multiple chromosomes suggested that all six triploid conceptuses occurred as a result of failure to complete meiosis II (MII). The proband's mother had also experienced recurrent miscarriage, with a total of 18 miscarriages. Based on the hypothesis that an inherited autosomal-dominant maternal predisposition would explain the phenotype, whole-exome sequencing of the proband and her parents was undertaken to identify potential candidate variants. After filtering for quality and rarity, potentially damaging variants shared between the proband and her mother were identified in 47 genes. Variants in genes coding for proteins implicated in oocyte maturation, oocyte activation or polar body extrusion were then prioritized. Eight of the most promising candidate variants were confirmed by Sanger sequencing. These included a novel change in the PLCD4 gene, and a rare variant in the OSBPL5 gene, which have been implicated in oocyte activation upon fertilization and completion of MII. Several variants in genes coding proteins playing a role in oocyte maturation and early embryonic development were also identified. The genes identified may be candidates for the study in other women experiencing recurrent triploidy or recurrent IVF failur

Temperatures of Fragment Kinetic Energy Spectra

Multifragmentation reactions without large compression in the initial state (proton-induced reactions, reverse-kinematics, projectile fragmentation) are examined, and it is verified quantitatively that the high temperatures obtained from fragment kinetic energy spectra and lower temperatures obtained from observables such as level population or isotope ratios can be understood in a common framework.Comment: LaTeX, 7 pages, 2 figures available from autho

Tensor-scalar gravity and binary-pulsar experiments

Some recently discovered nonperturbative strong-field effects in tensor-scalar theories of gravitation are interpreted as a scalar analog of ferromagnetism: "spontaneous scalarization". This phenomenon leads to very significant deviations from general relativity in conditions involving strong gravitational fields, notably binary-pulsar experiments. Contrary to solar-system experiments, these deviations do not necessarily vanish when the weak-field scalar coupling tends to zero. We compute the scalar "form factors" measuring these deviations, and notably a parameter entering the pulsar timing observable gamma through scalar-field-induced variations of the inertia moment of the pulsar. An exploratory investigation of the confrontation between tensor-scalar theories and binary-pulsar experiments shows that nonperturbative scalar field effects are already very tightly constrained by published data on three binary-pulsar systems. We contrast the probing power of pulsar experiments with that of solar-system ones by plotting the regions they exclude in a generic two-dimensional plane of tensor-scalar theories.Comment: 35 pages, REVTeX 3.0, uses epsf.tex to include 9 Postscript figure

Non-linear regression models for Approximate Bayesian Computation

Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable. However the methods that use rejection suffer from the curse of dimensionality when the number of summary statistics is increased. Here we propose a machine-learning approach to the estimation of the posterior density by introducing two innovations. The new method fits a nonlinear conditional heteroscedastic regression of the parameter on the summary statistics, and then adaptively improves estimation using importance sampling. The new algorithm is compared to the state-of-the-art approximate Bayesian methods, and achieves considerable reduction of the computational burden in two examples of inference in statistical genetics and in a queueing model.Comment: 4 figures; version 3 minor changes; to appear in Statistics and Computin

Search for the decay K+→π+ννˉK^+\to \pi^+ \nu \bar\nu in the momentum region Pπ<195 MeV/cP_\pi < 195 {\rm ~MeV/c}

We have searched for the decay $K^+ \to \pi^+ \nu \bar\nu$ in the kinematic region with pion momentum below the $K^+ \to \pi^+ \pi^0$ peak. One event was observed, consistent with the background estimate of $0.73\pm 0.18$. This implies an upper limit on $B(K^+ \to \pi^+ \nu \bar\nu)< 4.2\times 10^{-9}$ (90% C.L.), consistent with the recently measured branching ratio of $(1.57^{+1.75}_{-0.82}) \times 10^{-10}$, obtained using the standard model spectrum and the kinematic region above the $K^+ \to \pi^+ \pi^0$ peak. The same data were used to search for $K^+ \to \pi^+ X^0$, where $X^0$ is a weakly interacting neutral particle or system of particles with $150 < M_{X^0} < 250 {\rm ~MeV/c^2}$.Comment: 4 pages, 2 figure

Shared and selective neural correlates of inhibition, facilitation, and shifting processes during executive control

A network of prefrontal and parietal regions has been implicated in executive control processes. However, the extent to which individual regions within this network are engaged in component control processes, such as inhibition of task-irrelevant stimulus attributes or shifting (switching) between attentional foci, remains controversial. Participants (N = 17) underwent functional magnetic resonance imaging while performing a global–local task in which the global and local levels could facilitate or interfere with one another. Stimuli were presented in blocks in which participants either constantly shifted between the global and local levels, or consistently responded to one level only. Activations related to inhibition and shifting processes were observed in a large network of bilateral prefrontal, parietal, and basal ganglia regions. Region of interest analyses were used to classify each region within this network as being common to inhibition and shifting, or preferential to one component process. Several regions were classified as being preferential to inhibition, including regions within the dorsolateral and ventrolateral prefrontal cortex, the parietal lobes, and the temporal–parietal junction. A limited set of regions in the parietal lobes and left dorsolateral prefrontal cortex were classified as preferential to shifting. There was a very large set of regions displaying activation common to both inhibition and shifting processes, including regions within the dorsolateral prefrontal cortex, anterior cingulate, and basal ganglia. Several of these common regions were also involved during facilitation, suggesting that they are responsive to the number of task-salient channels of information, rather than purely to demands on control processes.National Institute of Mental Health (U.S.) (MH061426)National Institute on Aging (AG021847

IDS Based on Bio-inspired Models

Unsupervised projection approaches can support Intrusion Detection Systems for computer network security. The involved technologies assist a network manager in detecting anomalies and potential threats by an intuitive display of the progression of network traffic. Projection methods operate as smart compression tools and map raw, high-dimensional traffic data into 2-D or 3-D spaces for subsequent graphical display. The paper compares three projection methods, namely, Cooperative Maximum Likelihood Hebbian Learning, Auto-Associative Back-Propagation networks and Principal Component Analysis. Empirical tests on anomalous situations related to the Simple Network Management Protocol (SNMP) confirm the validity of the projection-based approach. One of these anomalous situations (the SNMP community search) is faced by these projection models for the first time. This work also highlights the importance of the time-information dependence in the identification of anomalous situations in the case of the applied methods

Young and Intermediate-age Distance Indicators

Distance measurements beyond geometrical and semi-geometrical methods, rely mainly on standard candles. As the name suggests, these objects have known luminosities by virtue of their intrinsic proprieties and play a major role in our understanding of modern cosmology. The main caveats associated with standard candles are their absolute calibration, contamination of the sample from other sources and systematic uncertainties. The absolute calibration mainly depends on their chemical composition and age. To understand the impact of these effects on the distance scale, it is essential to develop methods based on different sample of standard candles. Here we review the fundamental properties of young and intermediate-age distance indicators such as Cepheids, Mira variables and Red Clump stars and the recent developments in their application as distance indicators.Comment: Review article, 63 pages (28 figures), Accepted for publication in Space Science Reviews (Chapter 3 of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age