Study of high voltage solar array configurations with integrated power control electronics

Solar array electrical configurations for voltage regulatio

3D simulations of self-propelled, reconstructed jellyfish using vortex methods

We present simulations of the vortex dynamics associated with the self-propelled motion of jellyfish. The geometry is obtained from image segmentation of video recordings from live jellyfish. The numerical simulations are performed using three-dimensional viscous, vortex particle methods with Brinkman penalization to impose the kinematics of the jellyfish motion. We study two types of strokes recorded in the experiment1. The first type (stroke A) produces two vortex rings during the stroke: one outside the bell during the power stroke and one inside the bell during the recovery stroke. The second type (stroke B) produces three vortex rings: one ring during the power stroke and two vortex rings during the recovery stroke. Both strokes propel the jellyfish, with stroke B producing the highest velocity. The speed of the jellyfish scales with the square root of the Reynolds number. The simulations are visualized in a fluid dynamics video.Comment: 1 page, 1 figur

Critical Current 0-π\pi Transition in Designed Josephson Quantum Dot Junctions

We report on quantum dot based Josephson junctions designed specifically for measuring the supercurrent. From high-accuracy fitting of the current-voltage characteristics we determine the full magnitude of the supercurrent (critical current). Strong gate modulation of the critical current is observed through several consecutive Coulomb blockade oscillations. The critical current crosses zero close to, but not at, resonance due to the so-called 0-$\pi$ transition in agreement with a simple theoretical model.Comment: 5 pages, 4 figures, (Supplementary information available at http://www.fys.ku.dk/~hij/public/nl_supp.pdf

Meteorological application of Apollo photography Final report

Development of meteorological information and parameters based on cloud photographs taken during Apollo 9 fligh

Superconductor-Nanowire Devices from Tunneling to the Multichannel Regime: Zero-Bias Oscillations and Magnetoconductance Crossover

We present transport measurements in superconductor-nanowire devices with a gated constriction forming a quantum point contact. Zero-bias features in tunneling spectroscopy appear at finite magnetic fields, and oscillate in amplitude and split away from zero bias as a function of magnetic field and gate voltage. A crossover in magnetoconductance is observed: Magnetic fields above ~ 0.5 T enhance conductance in the low-conductance (tunneling) regime but suppress conductance in the high-conductance (multichannel) regime. We consider these results in the context of Majorana zero modes as well as alternatives, including Kondo effect and analogs of 0.7 structure in a disordered nanowire.Comment: Supplemental Material here: https://dl.dropbox.com/u/1742676/Churchill_Supplemental.pd

Electron transport in single wall carbon nanotube weak links in the Fabry-Perot regime

We fabricated reproducible high transparency superconducting contacts consisting of superconducting Ti/Al/Ti trilayers to gated single-walled carbon nanotubes (SWCNTs). The reported semiconducting SWCNT have normal state differential conductance up to $3e^2/h$ and exhibit clear Fabry-Perot interference patterns in the bias spectroscopy plot. We observed subharmonic gap structure in the differential conductance and a distinct peak in the conductance at zero bias which is interpreted as a manifestation of a supercurrent. The gate dependence of this supercurrent as well as the excess current are examined and compared to a coherent theory of superconducting point contacts with good agreement.Comment: 10 pages, 4 figure

Time-varying Learning and Content Analytics via Sparse Factor Analysis

We propose SPARFA-Trace, a new machine learning-based framework for time-varying learning and content analytics for education applications. We develop a novel message passing-based, blind, approximate Kalman filter for sparse factor analysis (SPARFA), that jointly (i) traces learner concept knowledge over time, (ii) analyzes learner concept knowledge state transitions (induced by interacting with learning resources, such as textbook sections, lecture videos, etc, or the forgetting effect), and (iii) estimates the content organization and intrinsic difficulty of the assessment questions. These quantities are estimated solely from binary-valued (correct/incorrect) graded learner response data and a summary of the specific actions each learner performs (e.g., answering a question or studying a learning resource) at each time instance. Experimental results on two online course datasets demonstrate that SPARFA-Trace is capable of tracing each learner's concept knowledge evolution over time, as well as analyzing the quality and content organization of learning resources, the question-concept associations, and the question intrinsic difficulties. Moreover, we show that SPARFA-Trace achieves comparable or better performance in predicting unobserved learner responses than existing collaborative filtering and knowledge tracing approaches for personalized education