Dipole-Allowed Direct Band Gap Silicon Superlattices

Silicon is the most popular material used in electronic devices. However, its poor optical properties owing to its indirect band gap nature limit its usage in optoelectronic devices. Here we present the discovery of super-stable pure-silicon superlattice structures that can serve as promising materials for solar cell applications and can lead to the realization of pure Si-based optoelectronic devices. The structures are almost identical to that of bulk Si except that defective layers are intercalated in the diamond lattice. The superlattices exhibit dipole-allowed direct band gaps as well as indirect band gaps, providing ideal conditions for the investigation of a direct-to-indirect band gap transition. The transition can be understood in terms of a novel conduction band originating from defective layers, an overlap between the valence- and conduction-band edge states at the interface layers, and zone folding with quantum confinement effects on the conduction band of non-defective bulk-like Si. The fact that almost all structural portions of the superlattices originate from bulk Si warrants their stability and good lattice matching with bulk Si. Through first-principles molecular dynamics simulations, we confirmed their thermal stability and propose a possible method to synthesize the defective layer through wafer bonding

Application of Artificial Neural Network to Search for Gravitational-Wave Signals Associated with Short Gamma-Ray Bursts

We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts. The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability is improved by the artificial neural network in comparison to the conventional detection statistic. Therefore, this algorithm increases the distance at which a gravitational-wave signal could be observed in coincidence with a gamma-ray burst. In order to demonstrate the performance, we also evaluate a few seconds of gravitational-wave data segment using the trained networks and obtain the false alarm probability. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short gamma-ray bursts.Comment: 30 pages, 10 figure

Optimizing Parameters of Information-Theoretic Correlation Measurement for Multi-Channel Time-Series Datasets in Gravitational Wave Detectors

Data analysis in modern science using extensive experimental and observational facilities, such as a gravitational wave detector, is essential in the search for novel scientific discoveries. Accordingly, various techniques and mathematical principles have been designed and developed to date. A recently proposed approximate correlation method based on the information theory is widely adopted in science and engineering. Although the maximal information coefficient (MIC) method remains in the phase of improving its algorithm, it is particularly beneficial in identifying the correlations of multiple noise sources in gravitational-wave detectors including non-linear effects. This study investigates various prospects for determining MIC parameters to improve the reliability of handling multi-channel time-series data, reduce high computing costs, and propose a novel method of determining optimized parameter sets for identifying noise correlations in gravitational wave data.Comment: 11 pages, 8 figure

Identifying and diagnosing coherent associations and causalities between multi-channels of the gravitational wave detector

The gravitational-wave detector is a very complicated and sensitive collection of advanced instruments, which is influenced not only by the mutual interaction between mechanical/electronics systems but also by the surrounding environment. Thus, it is necessary to categorize and reduce noises from many channels interconnected by such instruments and environment for achieving the detection of gravitational waves because it enhances to increase of a signal-to-noise ratio and reduces false alarms from coincident loud events. For this reason, it is of great importance to identify some coherent associations between complicated channels. This study presents a way of identifying (non-) linear couplings between interconnected channels by using some correlation coefficients, which are applied to practical issues such as noises by hardware injection test, lightning strokes, and air compressor vibrations gravitational-wave detector.Comment: 10 pages, 8 figures, and 2 table

Surface and bottom temperature and salinity climatology along the continental shelf off the Canadian and U.S. East Coasts

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Continental Shelf Research 124 (2016): 165-181, doi:10.1016/j.csr.2016.06.005.A new hydrographic climatology has been created for the continental shelf region, extending from the Labrador shelf to the Mid-Atlantic Bight. The 0.2-degree climatology combines all available observations of surface and bottom temperature and salinity collected between 1950 and 2010 along with the location, depth and date of these measurements. While climatological studies of surface and bottom temperature and salinity have been presented previously for various regions along the Canadian and U.S. shelves, studies also suggest that all these regions are part of one coherent system. This study focuses on the coherent structure of the mean seasonal cycle of surface and bottom temperature and salinity and its variation along the shelf and upper slope. The seasonal cycle of surface temperature is mainly driven by the surface heat flux and exhibits strong dependency on latitude (r≈−0.9). The amplitude of the seasonal cycle of bottom temperature is rather dependent on the depth, while the spatial distribution of bottom temperature is correlated with latitude. The seasonal cycle of surface salinity is influenced by several components, such as sea-ice on the northern shelves and river discharge in the Gulf of St. Lawrence. The bottom salinity exhibits no clear seasonal cycle, but its spatial distribution is highly correlated with bathymetry, thus Slope Water and its intrusion on the shelf can be identified by its relatively high salinity compared to shallow, fresher shelf water. Two different regimes can be identified, especially on the shelf, separated by the Laurentian Channel: advection influences the phasing of the seasonal cycle of surface salinity and bottom temperature to the north, while in the southern region, river runoff and air-sea heat flux forcing are dominant, especially over the shallower bathymetry.Support from NSF OCE PO to Y-OK (OCE-1242989 and OCE-1435602) and SJL (OCE-1332666)

Pointing all around you : selection performance of mouse and ray-cast pointing in full-coverage displays

Funding: SurfNet (NSERC, Canada), EPSRC (Small Equipment Grant).As display environments become larger and more diverse - now often encompassing multiple walls and room surfaces - it is becoming more common that users must find and manipulate digital artifacts not directly in front of them. There is little understanding, however, about what techniques and devices are best for carrying out basic operations above, behind, or to the side of the user. We conducted an empirical study comparing two main techniques that are suitable for full-coverage display environments: mouse-based pointing, and ray-cast `laser' pointing. Participants completed search and pointing tasks on the walls and ceiling, and we measured completion time, path lengths and perceived effort. Our study showed a strong interaction between performance and target location: when the target position was not known a priori the mouse was fastest for targets on the front wall, but ray-casting was faster for targets behind the user. Our findings provide new empirical evidence that can help designers choose pointing techniques for full-coverage spaces.Postprin