Recent advancements in monolithic AlGaAs/GaAs solar cells for space applications

High efficiency, two terminal, multijunction AlGaAs/GaAs solar cells were reproducibly made with areas of 0.5 sq cm. The multiple layers in the cells were grown by Organo Metallic Vapor Phase Epitaxy (OMVPE) on GaAs substrates in the n-p configuration. The upper AlGaAs cell has a bandgap of 1.93 eV and is connected in series to the lower GaAs cell (1.4 eV) via a metal interconnect deposited during post-growth processing. A prismatic coverglass is installed on top of the cell to reduce obscuration caused by the gridlines. The best 0.5 sq cm cell has a two terminal efficiency of 23.0 pct. at 1 sun, air mass zero (AM0) and 25 C. To date, over 300 of these cells were grown and processed for a manufacturing demonstration. Yield and efficiency data for this demonstration are presented. As a first step toward the goal of a 30 pct. efficient cell, a mechanical stack of the 0.5 sq cm cells described above, and InGaAsP (0.95 eV) solar cells was made. The best two terminal measurement to date yields an efficiency of 25.2 pct. AM0. This is the highest reported efficiency of any two terminal, 1 sun space solar cell

Stability of a Nonequilibrium Interface in a Driven Phase Segregating System

We investigate the dynamics of a nonequilibrium interface between coexisting phases in a system described by a Cahn-Hilliard equation with an additional driving term. By means of a matched asymptotic expansion we derive equations for the interface motion. A linear stability analysis of these equations results in a condition for the stability of a flat interface. We find that the stability properties of a flat interface depend on the structure of the driving term in the original equation.Comment: 14 pages Latex, 1 postscript-figur

Critical Dynamics of a Vortex Loop Model for the Superconducting Transition

We calculate analytically the dynamic critical exponent $z_{MC}$ measured in Monte Carlo simulations for a vortex loop model of the superconducting transition, and account for the simulation results. In the weak screening limit, where magnetic fluctuations are neglected, the dynamic exponent is found to be $z_{MC} = 3/2$. In the perfect screening limit, $z_{MC} = 5/2$. We relate $z_{MC}$ to the actual value of $z$ observable in experiments and find that $z \sim 2$, consistent with some experimental results

The Role of Mesotocin on Social Bonding in Pinyon Jays

The neuropeptide oxytocin influences mammalian social bonding by facilitating the building and maintenance of parental, sexual, and same‐sex social relationships. However, we do not know whether the function of the avian homologue mesotocin is evolutionarily conserved across birds. While it does influence avian prosocial behavior, mesotocin\u27s role in avian social bonding remains unclear. Here, we investigated whether mesotocin regulates the formation and maintenance of same‐sex social bonding in pinyon jays (Gymnorhinus cyanocephalus), a member of the crow family. We formed squads of four individually housed birds. In the first, “pair‐formation” phase of the experiment, we repeatedly placed pairs of birds from within the squad together in a cage for short periods of time. Prior to entering the cage, we intranasally administered one of three hormone solutions to both members of the pair: mesotocin, oxytocin antagonist, or saline. Pairs received repeated sessions with administration of the same hormone. In the second, “pair‐maintenance” phase of the experiment, all four members of the squad were placed together in a large cage, and no hormones were administered. For both phases, we measured the physical proximity between pairs as our proxy for social bonding. We found that, compared with saline, administering mesotocin or oxytocin antagonist did not result in different proximities in either the pair‐formation or pair‐maintenance phase of the experiment. Therefore, at the dosages and time frames used here, exogenously introduced mesotocin did not influence same‐sex social bond formation or maintenance. Like oxytocin in mammals, mesotocin regulates avian prosocial behavior; however, unlike oxytocin, we do not have evidence that mesotocin regulates social bonds in birds

Mesoscopic Analysis of Structure and Strength of Dislocation Junctions in FCC Metals

We develop a finite element based dislocation dynamics model to simulate the structure and strength of dislocation junctions in FCC crystals. The model is based on anisotropic elasticity theory supplemented by the explicit inclusion of the separation of perfect dislocations into partial dislocations bounding a stacking fault. We demonstrate that the model reproduces in precise detail the structure of the Lomer-Cottrell lock already obtained from atomistic simulations. In light of this success, we also examine the strength of junctions culminating in a stress-strength diagram which is the locus of points in stress space corresponding to dissolution of the junction.Comment: 9 Pages + 4 Figure

Discrete Model of Ideological Struggle Accounting for Migration

A discrete in time model of ideological competition is formulated taking into account population migration. The model is based on interactions between global populations of non-believers and followers of different ideologies. The complex dynamics of the attracting manifolds is investigated. Conversion from one ideology to another by means of (i) mass media influence and (ii) interpersonal relations is considered. Moreover a different birth rate is assumed for different ideologies, the rate being assumed to be positive for the reference population, made of initially non-believers. Ideological competition can happen in one or several regions in space. In the latter case, migration of non-believers and adepts is allowed; this leads to an enrichment of the ideological dynamics. Finally, the current ideological situation in the Arab countries and China is commented upon from the point of view of the presently developed mathematical model. The massive forced conversion by Ottoman Turks in the Balkans is briefly discussed.Comment: 24 pages, with 5 figures and 52 refs.; prepared for a Special issue of Advances in Complex System

Extracting galactic binary signals from the first round of Mock LISA Data Challenges

We report on the performance of an end-to-end Bayesian analysis pipeline for detecting and characterizing galactic binary signals in simulated LISA data. Our principal analysis tool is the Blocked-Annealed Metropolis Hasting (BAM) algorithm, which has been optimized to search for tens of thousands of overlapping signals across the LISA band. The BAM algorithm employs Bayesian model selection to determine the number of resolvable sources, and provides posterior distribution functions for all the model parameters. The BAM algorithm performed almost flawlessly on all the Round 1 Mock LISA Data Challenge data sets, including those with many highly overlapping sources. The only misses were later traced to a coding error that affected high frequency sources. In addition to the BAM algorithm we also successfully tested a Genetic Algorithm (GA), but only on data sets with isolated signals as the GA has yet to be optimized to handle large numbers of overlapping signals.Comment: 13 pages, 4 figures, submitted to Proceedings of GWDAW-11 (Berlin, Dec. '06

Incorporating prior knowledge improves detection of differences in bacterial growth rate

BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate

Fast Domain Growth through Density-Dependent Diffusion in a Driven Lattice Gas

We study electromigration in a driven diffusive lattice gas (DDLG) whose continuous Monte Carlo dynamics generate higher particle mobility in areas with lower particle density. At low vacancy concentrations and low temperatures, vacancy domains tend to be faceted: the external driving force causes large domains to move much more quickly than small ones, producing exponential domain growth. At higher vacancy concentrations and temperatures, even small domains have rough boundaries: velocity differences between domains are smaller, and modest simulation times produce an average domain length scale which roughly follows $L \sim t^{\zeta}$, where $\zeta$ varies from near .55 at 50% filling to near .75 at 70% filling. This growth is faster than the $t^{1/3}$ behavior of a standard conserved order parameter Ising model. Some runs may be approaching a scaling regime. At low fields and early times, fast growth is delayed until the characteristic domain size reaches a crossover length which follows $L_{cross} \propto E^{-\beta}$. Rough numerical estimates give $\beta= >.37$ and simple theoretical arguments give $\beta= 1/3$. Our conclusion that small driving forces can significantly enhance coarsening may be relevant to the YB$_2$Cu$_3$O$_{7- \delta}$ electromigration experiments of Moeckly {\it et al.}(Appl. Phys. Let., {\bf 64}, 1427 (1994)).Comment: 18 pages, RevTex3.

Detecting extreme mass ratio inspiral events in LISA data using the Hierarchical Algorithm for Clusters and Ridges (HACR)

One of the most exciting prospects for the Laser Interferometer Space Antenna (LISA) is the detection of gravitational waves from the inspirals of stellar-mass compact objects into supermassive black holes. Detection of these sources is an extremely challenging computational problem due to the large parameter space and low amplitude of the signals. However, recent work has suggested that the nearest extreme mass ratio inspiral (EMRI) events will be sufficiently loud that they might be detected using computationally cheap, template-free techniques, such as a time-frequency analysis. In this paper, we examine a particular time-frequency algorithm, the Hierarchical Algorithm for Clusters and Ridges (HACR). This algorithm searches for clusters in a power map and uses the properties of those clusters to identify signals in the data. We find that HACR applied to the raw spectrogram performs poorly, but when the data is binned during the construction of the spectrogram, the algorithm can detect typical EMRI events at distances of up to $\sim2.6$Gpc. This is a little further than the simple Excess Power method that has been considered previously. We discuss the HACR algorithm, including tuning for single and multiple sources, and illustrate its performance for detection of typical EMRI events, and other likely LISA sources, such as white dwarf binaries and supermassive black hole mergers. We also discuss how HACR cluster properties could be used for parameter extraction.Comment: 21 pages, 11 figures, submitted to Class. Quantum Gravity. Modified and shortened in light of referee's comments. Updated results consider tuning over all three HACR thresholds, and show 10-15% improvement in detection rat