Universal Parametric Correlations of Eigenfunctions in Chaotic and Disordered Systems

This paper establishes the universality of parametric correlations of eigenfunctions in chaotic and weakly disordered systems. We demonstrate this universality in the framework of the gaussian random matrix process and obtain predictions for a number of parametric correlators, one of them analytically. We present numerical evidence from different models that verifies our predictions.Comment: 11 pages, RevTeX, 2 uuencoded Postscript figure

Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization. This so-called Augmented Autoencoder has several advantages over existing methods: It does not require real, pose-annotated training data, generalizes to various test sensors and inherently handles object and view symmetries. Instead of learning an explicit mapping from input images to object poses, it provides an implicit representation of object orientations defined by samples in a latent space. Our pipeline achieves state-of-the-art performance on the T-LESS dataset both in the RGB and RGB-D domain. We also evaluate on the LineMOD dataset where we can compete with other synthetically trained approaches. We further increase performance by correcting 3D orientation estimates to account for perspective errors when the object deviates from the image center and show extended results.Comment: Code available at: https://github.com/DLR-RM/AugmentedAutoencode

The Perturbed Static Path Approximation at Finite Temperature: Observables and Strength Functions

We present an approximation scheme for calculating observables and strength functions of finite fermionic systems at finite temperature such as hot nuclei. The approach is formulated within the framework of the Hubbard-Stratonovich transformation and goes beyond the static path approximation and the RPA by taking into account small amplitude time-dependent fluctuations around each static value of the auxiliary fields. We show that this perturbed static path approach can be used systematically to obtain good approximations for observable expectation values and for low moments of the strength function. The approximation for the strength function itself, extracted by an analytic continuation from the imaginary-time response function, is not always reliable, and we discuss the origin of the discrepancies and possible improvements. Our results are tested in a solvable many-body model.Comment: 37 pages, 8 postscript figures included, RevTe

Finite temperature effects in Coulomb blockade quantum dots and signatures of spectral scrambling

The conductance in Coulomb blockade quantum dots exhibits sharp peaks whose spacings fluctuate with the number of electrons. We derive the temperature-dependence of these fluctuations in the statistical regime and compare with recent experimental results. The scrambling due to Coulomb interactions of the single-particle spectrum with the addition of an electron to the dot is shown to affect the temperature-dependence of the peak spacing fluctuations. Spectral scrambling also leads to saturation in the temperature dependence of the peak-to-peak correlator, in agreement with recent experimental results. The signatures of scrambling are derived using discrete Gaussian processes, which generalize the Gaussian ensembles of random matrices to systems that depend on a discrete parameter -- in this case, the number of electrons in the dot.Comment: 14 pages, 4 eps figures included, RevTe

Universal Parametric Correlations of Conductance Peaks in Quantum Dots

We compute the parametric correlation function of the conductance peaks in chaotic and weakly disordered quantum dots in the Coulomb blockade regime and demonstrate its universality upon an appropriate scaling of the parameter. For a symmetric dot we show that this correlation function is affected by breaking time-reversal symmetry but is independent of the details of the channels in the external leads. We derive a new scaling which depends on the eigenfunctions alone and can be extracted directly from the conductance peak heights. Our results are in excellent agreement with model simulations of a disordered quantum dot.Comment: 12 pages, RevTex, 2 Postscript figure

Semiclassical Analysis of Extended Dynamical Mean Field Equations

The extended Dynamical Mean Field Equations (EDMFT) are analyzed using semiclassical methods for a model describing an interacting fermi-bose system. We compare the semiclassical approach with the exact QMC (Quantum Montecarlo) method. We found the transition to an ordered state to be of the first order for any dimension below four.Comment: RevTex, 39 pages, 16 figures; Appendix C added, typos correcte

Universal Correlations of Coulomb Blockade Conductance Peaks and the Rotation Scaling in Quantum Dots

We show that the parametric correlations of the conductance peak amplitudes of a chaotic or weakly disordered quantum dot in the Coulomb blockade regime become universal upon an appropriate scaling of the parameter. We compute the universal forms of this correlator for both cases of conserved and broken time reversal symmetry. For a symmetric dot the correlator is independent of the details in each lead such as the number of channels and their correlation. We derive a new scaling, which we call the rotation scaling, that can be computed directly from the dot's eigenfunction rotation rate or alternatively from the conductance peak heights, and therefore does not require knowledge of the spectrum of the dot. The relation of the rotation scaling to the level velocity scaling is discussed. The exact analytic form of the conductance peak correlator is derived at short distances. We also calculate the universal distributions of the average level width velocity for various values of the scaled parameter. The universality is illustrated in an Anderson model of a disordered dot.Comment: 35 pages, RevTex, 6 Postscript figure

‘I think I'm more free with them'—Conflict, Negotiation and Change in Intergenerational Relations in African Families Living in Britain

While the family is increasingly being recognised as pivotal to migration, there remain too few studies examining how migration impacts on intergenerational relationships. Although traditional intergenerational gaps are intensified by migration, arguably there has been an over-emphasis on the divisions between ‘traditional’ parents and ‘modern’ children at the expense of examining the ways in which both generations adapt. As Foner and Dreby [2011. “Relations Between the Generations in Immigrant Families.” Annual Review of Sociology 37: 545–564] stress, the reality of post-migration intergenerational relations is inevitably more complex, requiring the examination of both conflict and cooperation. This article contributes to this growing literature by discussing British data from comparative projects on intergenerational relations in African families (in Britain, France and South Africa). It argues that particular understandings can be gained from examining the adaptation of parents and parenting strategies post-migration and how the reconfiguration of family relations can contribute to settlement. By focusing on how both parent and child generations engage in conflict and negotiation to redefine their relationships and expectations, it offers insight into how families navigate and integrate the values of two cultures. In doing so, it argues that the reconfiguration of gender roles as a result of migration offers families the space to renegotiate their relationships and make choices about what they transmit to the next generation

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies