High Performance Lyot and PIAA Coronagraphy for Arbitrarily shaped Telescope Apertures

Two high performance coronagraphic approaches compatible with segmented and obstructed telescope pupils are described. Both concepts use entrance pupil amplitude apodization and a combined phase and amplitude focal plane mask to achieve full coronagraphic extinction of an on-axis point source. While the first concept, named Apodized Pupil Complex Mask Lyot Coronagraph (APCMLC), relies on a transmission mask to perform the pupil apodization, the second concept, named Phase-Induced Amplitude Apodization complex mask coronagraph (PIAACMC), uses beam remapping for lossless apodization. Both concepts theoretically offer complete coronagraphic extinction (infinite contrast) of a point source in monochromatic light, with high throughput and sub-lambda/D inner working angle, regardless of aperture shape. The PIAACMC offers nearly 100% throughput and approaches the fundamental coronagraph performance limit imposed by first principles. The steps toward designing the coronagraphs for arbitrary apertures are described for monochromatic light. Designs for the APCMLC and the higher performance PIAACMC are shown for several monolith and segmented apertures, such as the apertures of the Subaru Telescope, Giant Magellan Telescope (GMT), Thirty Meter Telescope (TMT), the European Extremely Large Telescope (E-ELT) and the Large Binocular Telescope (LBT). Performance in broadband light is also quantified, suggesting that the monochromatic designs are suitable for use in up to 20% wide spectral bands for ground-based telescopes.Comment: 19 pages, 12 figures, accepted for publication in Ap

Dynamical chiral symmetry breaking in sliding nanotubes

We discovered in simulations of sliding coaxial nanotubes an unanticipated example of dynamical symmetry breaking taking place at the nanoscale. While both nanotubes are perfectly left-right symmetric and nonchiral, a nonzero angular momentum of phonon origin appears spontaneously at a series of critical sliding velocities, in correspondence with large peaks of the sliding friction. The non-linear equations governing this phenomenon resemble the rotational instability of a forced string. However, several new elements, exquisitely "nano" appear here, with the crucial involvement of Umklapp and of sliding nanofriction.Comment: To appear in PR

Personalized Pancreatic Tumor Growth Prediction via Group Learning

Tumor growth prediction, a highly challenging task, has long been viewed as a mathematical modeling problem, where the tumor growth pattern is personalized based on imaging and clinical data of a target patient. Though mathematical models yield promising results, their prediction accuracy may be limited by the absence of population trend data and personalized clinical characteristics. In this paper, we propose a statistical group learning approach to predict the tumor growth pattern that incorporates both the population trend and personalized data, in order to discover high-level features from multimodal imaging data. A deep convolutional neural network approach is developed to model the voxel-wise spatio-temporal tumor progression. The deep features are combined with the time intervals and the clinical factors to feed a process of feature selection. Our predictive model is pretrained on a group data set and personalized on the target patient data to estimate the future spatio-temporal progression of the patient's tumor. Multimodal imaging data at multiple time points are used in the learning, personalization and inference stages. Our method achieves a Dice coefficient of 86.8% +- 3.6% and RVD of 7.9% +- 5.4% on a pancreatic tumor data set, outperforming the DSC of 84.4% +- 4.0% and RVD 13.9% +- 9.8% obtained by a previous state-of-the-art model-based method

Influence of flow confinement on the drag force on a static cylinder

The influence of confinement on the drag force $F$ on a static cylinder in a viscous flow inside a rectangular slit of aperture $h_0$ has been investigated from experimental measurements and numerical simulations. At low enough Reynolds numbers, $F$ varies linearly with the mean velocity and the viscosity, allowing for the precise determination of drag coefficients $\lambda_{||}$ and $\lambda_{\bot}$ corresponding respectively to a mean flow parallel and perpendicular to the cylinder length $L$. In the parallel configuration, the variation of $\lambda_{||}$ with the normalized diameter $\beta = d/h_0$ of the cylinder is close to that for a 2D flow invariant in the direction of the cylinder axis and does not diverge when $\beta = 1$. The variation of $\lambda_{||}$ with the distance from the midplane of the model reflects the parabolic Poiseuille profile between the plates for $\beta \ll 1$ while it remains almost constant for $\beta \sim 1$. In the perpendicular configuration, the value of $\lambda_{\bot}$ is close to that corresponding to a 2D system only if $\beta \ll 1$ and/or if the clearance between the ends of the cylinder and the side walls is very small: in that latter case, $\lambda_{\bot}$ diverges as $\beta \to 1$ due to the blockage of the flow. In other cases, the side flow between the ends of the cylinder and the side walls plays an important part to reduce $\lambda_{\bot}$: a full 3D description of the flow is needed to account for these effects

Heuristic Search over a Ranking for Feature Selection

In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited feature set for distinguishing experiment classes in high dimensional data sets. Our method is based on the relevance and redundancy idea, in the sense that a ranked-feature is chosen if additional information is gained by adding it. This heuristic leads to considerably better accuracy results, in comparison to the full set, and other representative feature selection algorithms in twelve well–known data sets, coupled with notable dimensionality reduction

Digging into acceptor splice site prediction : an iterative feature selection approach

Feature selection techniques are often used to reduce data dimensionality, increase classification performance, and gain insight into the processes that generated the data. In this paper, we describe an iterative procedure of feature selection and feature construction steps, improving the classification of acceptor splice sites, an important subtask of gene prediction. We show that acceptor prediction can benefit from feature selection, and describe how feature selection techniques can be used to gain new insights in the classification of acceptor sites. This is illustrated by the identification of a new, biologically motivated feature: the AG-scanning feature. The results described in this paper contribute both to the domain of gene prediction, and to research in feature selection techniques, describing a new wrapper based feature weighting method that aids in knowledge discovery when dealing with complex datasets

A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation

Aircraft engine manufacturers collect large amount of engine related data during flights. These data are used to detect anomalies in the engines in order to help companies optimize their maintenance costs. This article introduces and studies a generic methodology that allows one to build automatic early signs of anomaly detection in a way that is understandable by human operators who make the final maintenance decision. The main idea of the method is to generate a very large number of binary indicators based on parametric anomaly scores designed by experts, complemented by simple aggregations of those scores. The best indicators are selected via a classical forward scheme, leading to a much reduced number of indicators that are tuned to a data set. We illustrate the interest of the method on simulated data which contain realistic early signs of anomalies.Comment: Proceedings of the 14th Industrial Conference, ICDM 2014, St. Petersburg : Russian Federation (2014

Near Infrared Adaptive Optics Imaging of QSO Host Galaxies

We report near-infrared (primarily H-band) adaptive optics (AO) imaging with the Gemini-N and Subaru Telescopes, of a representative sample of 32 nearby (z<0.3) QSOs selected from the Palomar-Green (PG) Bright Quasar Survey (BQS), in order to investigate the properties of the host galaxies. 2D modeling and visual inspection of the images shows that ~36% of the hosts are ellipticals, \~39% contain a prominent disk component, and ~25% are of undetermined type. 30% show obvious signs of disturbance. The mean M_H(host) = -24.82 (2.1L_H*), with a range -23.5 to -26.5 (~0.63 to 10 L_H*). At <L_H*, all hosts have a dominant disk component, while at >2 L_H* most are ellipticals. "Disturbed" hosts are found at all M_H(host), while "strongly disturbed" hosts appear to favor the more luminous hosts. Hosts with prominent disks have less luminous QSOs, while the most luminous QSOs are almost exclusively in ellipticals or in mergers (which presumably shortly will be ellipticals). At z<0.13, where our sample is complete at B-band, we find no clear correlation between M_B(QSO) and M_H(host). However, at z>0.15, the more luminous QSOs (M_B<-24.7), and 4/5 of the radio-loud QSOs, have the most luminous H-band hosts (>7L_H*), most of which are ellipticals. Finally, we find a strong correlation between the "infrared-excess", L_IR/L_BB, of QSOs with host type and degree of disturbance. Disturbed and strongly disturbed hosts and hosts with dominant disks have L_IR/L_BB twice that of non-disturbed and elliptical hosts, respectively. QSOs with "disturbed" and "strongly-disturbed" hosts are also found to have morphologies and mid/far-infrared colors that are similar to what is found for "warm" ultraluminous infrared galaxies, providing further evidence for a possible evolutionary connection between both classes of objects.Comment: 80 pages, accepted for publication in ApJ Supp

Vortex lattices in strong type-II superconducting two-dimensional strips

We show how to calculate semi-analytically the dense vortex state in strong type-II superconducting nanostructures. For the specific case of a strip, we find vortex lattice solutions which also incorporate surface superconductivity. We calculate the energy cost to displace individual vortex rows parallel to the surfaces and find that this energy oscillates with the magnetic field. Remarkably, we also find that, at a critical field $H^*$ below $H_{c2}$, this ''shear'' energy becomes strictly zero for the surface rows due to an unexpected mismatch with the bulk lattice.Comment: Title, abstract, and some text paragraphs have been rewritte