Hierarchical sinuous-antenna phased array for millimeter wavelengths

We present the design, fabrication and measured performance of a hierarchical sinuous-antenna phased array coupled to superconducting transition-edge-sensor (TES) bolometers for millimeter wavelengths. The architecture allows for dual-polarization wideband sensitivity with a beam width that is approximately frequency-independent. We report on measurements of a prototype device, which uses three levels of triangular phased arrays to synthesize beams that are approximately constant in width across three frequency bands covering a 3:1 bandwidth. The array element is a lens-coupled sinuous antenna. The device consists of an array of hemispherical lenses coupled to a lithographed wafer, which integrates TESs, planar sinuous antennas and microwave circuitry including band-defining filters. The approximately frequency-independent beam widths improve coupling to telescope optics and keep the the sensitivity of an experiment close to optimal across a broad frequency range. The design can be straightforwardly modified for use with non-TES lithographed cryogenic detectors such as kinetic inductance detectors (KIDs). Additionally, we report on the design and measurements of a broadband 180-degree hybrid that can simplify the design of future multichroic focal planes including but not limited to hierarchical phased arrays.Comment: 5 pages, 12 figure

Anatomy-specific classification of medical images using deep convolutional nets

Automated classification of human anatomy is an important prerequisite for many computer-aided diagnosis systems. The spatial complexity and variability of anatomy throughout the human body makes classification difficult. "Deep learning" methods such as convolutional networks (ConvNets) outperform other state-of-the-art methods in image classification tasks. In this work, we present a method for organ- or body-part-specific anatomical classification of medical images acquired using computed tomography (CT) with ConvNets. We train a ConvNet, using 4,298 separate axial 2D key-images to learn 5 anatomical classes. Key-images were mined from a hospital PACS archive, using a set of 1,675 patients. We show that a data augmentation approach can help to enrich the data set and improve classification performance. Using ConvNets and data augmentation, we achieve anatomy-specific classification error of 5.9 % and area-under-the-curve (AUC) values of an average of 0.998 in testing. We demonstrate that deep learning can be used to train very reliable and accurate classifiers that could initialize further computer-aided diagnosis.Comment: Presented at: 2015 IEEE International Symposium on Biomedical Imaging, April 16-19, 2015, New York Marriott at Brooklyn Bridge, NY, US

Tissue signals imprint ILC2 identity with anticipatory function.

Group 2 innate lymphoid cells (ILC2s) are distributed systemically and produce type 2 cytokines in response to a variety of stimuli, including the epithelial cytokines interleukin (IL)-25, IL-33, and thymic stromal lymphopoietin (TSLP). Transcriptional profiling of ILC2s from different tissues, however, grouped ILC2s according to their tissue of origin, even in the setting of combined IL-25-, IL-33-receptor-, and TSLP-receptor-deficiency. Single-cell profiling confirmed a tissue-organizing transcriptome and identified ILC2 subsets expressing distinct activating receptors, including the major subset of skin ILC2s, which were activated preferentially by IL-18. Tissue ILC2 subsets were unaltered in number and expression in germ-free mice, suggesting that endogenous, tissue-derived signals drive the maturation of ILC2 subsets by controlling expression of distinct patterns of activating receptors, thus anticipating tissue-specific perturbations occurring later in life

Surface-driven electronic structure in LaFeAsO studied by angle resolved photoemission spectroscopy

We measured the electronic structure of an iron arsenic parent compound LaFeAsO using angle resolved photoemission spectroscopy (ARPES). By comparing with a full-potential Linear Augmented PlaneWave calculation we show that the extra large Gamma hole pocket measured via ARPES comes from electronic structure at the sample surface. Based on this we discuss the strong polarization dependence of the band structure and a temperature-dependent hole-like band around the M point. The two phenomena give additional evidences for the existence of the surface-driven electronic structure.Comment: 6 pages, 6 figure

A conservation-based method for simulating the inspiral of binary black holes

We present a new approach to studying the evolution of massive black hole binaries in a stellar environment. By imposing conservation of total energy and angular momentum in scattering experiments, we find the dissipation forces that are exerted on the black holes by the stars, and thus obtain the decaying path of the binary from the classical dynamical friction regime down to subparsec scales. Our scheme lies between scattering experiments and N-body simulations. While still resolving collisions between stars and black holes, it is fast enough and allows to use a large enough number of particles to reach a smooth and convergent result. We studied both an equal mass and a 10:1 mass ratio binaries under various initial conditions. We show that while an equal mass binary stalls at a nearly circular orbit, a runaway growth of eccentricity occurs in the unequal mass case. This effect reduces the timescale for black hole coalescence through gravitational radiation to well below the Hubble time, even in spherical and gasless systems formed by dry mergers.Comment: 11 pages, 9 figure

QuantumATK: An integrated platform of electronic and atomic-scale modelling tools

QuantumATK is an integrated set of atomic-scale modelling tools developed since 2003 by professional software engineers in collaboration with academic researchers. While different aspects and individual modules of the platform have been previously presented, the purpose of this paper is to give a general overview of the platform. The QuantumATK simulation engines enable electronic-structure calculations using density functional theory or tight-binding model Hamiltonians, and also offers bonded or reactive empirical force fields in many different parametrizations. Density functional theory is implemented using either a plane-wave basis or expansion of electronic states in a linear combination of atomic orbitals. The platform includes a long list of advanced modules, including Green's-function methods for electron transport simulations and surface calculations, first-principles electron-phonon and electron-photon couplings, simulation of atomic-scale heat transport, ion dynamics, spintronics, optical properties of materials, static polarization, and more. Seamless integration of the different simulation engines into a common platform allows for easy combination of different simulation methods into complex workflows. Besides giving a general overview and presenting a number of implementation details not previously published, we also present four different application examples. These are calculations of the phonon-limited mobility of Cu, Ag and Au, electron transport in a gated 2D device, multi-model simulation of lithium ion drift through a battery cathode in an external electric field, and electronic-structure calculations of the composition-dependent band gap of SiGe alloys.Comment: Submitted to Journal of Physics: Condensed Matte

Effect of atomic layer deposition on the quality factor of silicon nanobeam cavities

In this work we study the effect of thin-film deposition on the quality factor (Q) of silicon nanobeam cavities. We observe an average increase in the Q of 38±31% in one sample and investigate the dependence of this increase on the initial nanobeam hole sizes. We note that this process can be used to modify cavities that have larger than optimal hole sizes following fabrication. Additionally, the technique allows the tuning of the cavity mode wavelength and the incorporation of new materials, without significantly degrading Q

Monolithic device for modelocking and stabilization of frequency combs

We demonstrate a device that integrates a III–V semiconductor saturable absorber mirror with a graphene electro-optic modulator, which provides a monolithic solution to modelocking and noise suppression in a frequency comb. The device offers a pure loss modulation bandwidth exceeding 5 MHz and only requires a low voltage driver. This hybrid device provides not only compactness and simplicity in laser cavity design, but also small insertion loss, compared to the previous metallic-mirror-based modulators. We believe this work paves the way to portable and fieldable phase-coherent frequency combs