The population of massive stars in R136 from HST/FOC UV observations

New ultraviolet (1300 A, 3400 A),HST FOC observations have been used to derive the UV color-magnitude diagram (CMD) of R136, with the main scientific goal of studying the upper end of the stellar mass function at ultraviolet wavelengths where the color degeneracy encountered in visual CMDs is less severe. The CMD has been compared to a set of theoretical isochrones, which have been computed using the latest generation of evolutionary models and model atmospheres for early type stars. Wolf-Rayet stars are included. Comparison of theTheoretical andobserved CMD suggests that there are no stars brighter than M₁₃₀–11. We use the observed main sequence turn-off and the known spectroscopic properties of the stellar population to derive constraints on the most probable age of R136. The presence of WNL stars and the lack of red supergiants suggests a most likely age of 3±1 Myr. A theoretical isochrone of 3±1 Myr is consistent with the observed stellar content of R136 if the most massive stars have initial masses around 50 M.Bases on Observations with the NASA/ESA Hubble Space Telescope, obtained at the STScI, which is operated by AURA, Inc., under NASA contract NAS5-26555.Astrophysics Division, Space Science Department, ESA     

Tracking multiple objects with particle filtering

We address the problem of multitarget tracking (MTT) encountered in many situations in signal or image processing. We consider stochastic dynamic systems detected by observation processes. The difficulty lies in the fact that the estimation of the states requires the assignment of the observations to the multiple targets. We propose an extension of the classical particle filter where the stochastic vector of assignment is estimated by a Gibbs sampler. This algorithm is used to estimate the trajectories of multiple targets from their noisy bearings, thus showing its ability to solve the data association problem. Moreover this algorithm is easily extended to multireceiver observations where the receivers can produce measurements of various nature with different frequencies.     

Magnetar spectra and twisted magnetospheres

The huge potential drop between the footpoints of the closed field lines in the twisted magnetospheres of magnetars may accelerate electrons up to very high energies, γ ? 10⁶. On the other hand, the comparison between the observed spectra of magnetars and spectra obtained by accurate theoretical models seems to favor of a picture in which the magnetosphere is filled by “slow” electrons (v ? 0.8c), rather than by ultra-relativistic particles.     

Modeling the broadband persistent emission of magnetars

In this paper, we discuss our first attempts to model the broadband persistent emission of magnetars within a self-consistent, physical scenario. We present the predictions of a synthetic model that we calculated with a new Monte Carlo 3D radiative code. The basic idea is that soft thermal photons (e.g. emitted by the star surface) can experience resonant cyclotron upscattering by a population of relativistic electrons treated in the twisted magnetosphere. Our code is specifically tailored to work in the ultra-magnetized regime; polarization and QED effects are consistently accounted for, as well different configurations for the magnetosphere. We discuss the predicted spectral properties in the 0.1–1000 keV range, the polarization properties, and we present the model application to a sample of magnetars soft X-ray spectra.     

The Magnetic Electron Ion Spectrometer (MagEIS) Instruments Aboard the Radiation Belt Storm Probes (RBSP) Spacecraft

This paper describes the Magnetic Electron Ion Spectrometer (MagEIS) instruments aboard the RBSP spacecraft from an instrumentation and engineering point of view. There are four magnetic spectrometers aboard each of the two spacecraft, one low-energy unit (20–240 keV), two medium-energy units (80–1200 keV), and a high-energy unit (800–4800 keV). The high unit also contains a proton telescope (55 keV–20 MeV). The magnetic spectrometers focus electrons within a selected energy pass band upon a focal plane of several silicon detectors where pulse-height analysis is used to determine if the energy of the incident electron is appropriate for the electron momentum selected by the magnet. Thus each event is a two-parameter analysis, an approach leading to a greatly reduced background. The physics of these instruments are described in detail followed by the engineering implementation. The data outputs are described, and examples of the calibration results and early flight data presented.     

Experimental and theoretical burning of solid rocket propellants near the pressure deflagration limit

Burning of composite solid rocket propellants near the pressure deflagration limit (PDL) was studied experimentally in two different test chambers. The propellant tested was a nonmetallized ammonium perchlorate-based composite propellant (AP 84/CTPB 16). Measurements were taken of the regression rate, oscillations frequency and flame luminosity. Self-sustained oscillations were detected near the PDL that matched reasonably well the predictions of the analytical nonlinear stability theory and of the numerically solved nonlinear mathematical model. Both experimental and numerical results show the burning rate oscillations near the PDL due to statically unstable burning, that is the only combustion regime possible below a certain pressure. When pressure is further reduced the amplitude of the oscillations increases and their frequency decreases, until extinction follows abruptly below a pressure that corresponds to the PDL.     

The comprehensive aerospace index (CASI): Tracking the economic performance of the aerospace industry

In this paper, we described the Comprehensive AeroSpace Index (CASI), a financial index aimed at representing the economic performance of the aerospace industry. CASI is build upon a data set of approximately 20 years of daily close prices set, from January 1987 to June 2007, from a comprehensive sample of leading aerospace-related companies with stocks negotiated on the New York Exchange (NYSE) and on the over-the-counter (OTC) markets. We also introduced the sub-indices CASI-AERO, for aeronautical segment, and CASI-SAT, for satellite segment, and considered the relation between them. These three indices are compared to others aerospace indices and to more traditional general financial indices like DJIA, S&P500 and Nasdaq. Our results have shown that the CASI is an index that describes very well the aerospace sector behavior, since it is able to reflect the aeronautical segment comportment as well as the satellite one. Therefore, in this sense, it can be considered as a representative index of the aerospace sector. Moreover, the creation of two sub-indices, the CASI-AERO and the CASI-SAT, allows to elucidate capital movements within the aerospace sector, particularly those of speculative nature, like the dot.com bubble and crash of 1998–2001.     

Propagation of non-linear ion-sound pulses in dusty plasma waveguides

There are a lot of objects in space associated with dusty plasma inclusions. Such inclusions may bear a prolonged shape and behave as waveguides for ion-sound waves. In the case of space plasmas, the dust particles can possess both negative charge, due to electron attachment, and positive one, due to photoionization. In this paper the propagation of linear and non-linear ion-sound wave pulses in the dusty plasma waveguides, possessing positive charge, is studied. It has been demonstrated that non-linear dynamics of baseband pulse propagation in plasma waveguide possesses essentially non-solitonic behavior. Namely, propagation of a long ion-sound pulse leads to an excitation of a shock-like wave but not a stable localized nonlinear pulse. Also, when a Korteveg–de Vries (KdV) soliton is incident onto the dusty plasma waveguide, some part of the soliton energy is captured by the waveguide and transformed into a multi-pulse structure. Additionally, an interaction of dusty plasma inclusions with KdV soliton can lead to the occurrence of transverse instabilities of the soliton and its eventual destruction.     

Fixed membrane wings for micro air vehicles: Experimental characterization,numerical modeling,and tailoring

Fixed wing micro air vehicles (wingspan between 10 and 15 cm) are aerodynamically challenging due to the low Reynolds number regime (10⁴–10⁵) they operate in. The low aspect ratio wings (typically used to maximize area under a size constraint) promote strong tip vortices, and are susceptible to rolling instabilities. Wind gusts can be of the same order of magnitude as the flight speed (10–15 m/s). Standard control surfaces on an empennage must be eliminated for size considerations and drag reduction, and the range of stable center of gravity locations is only a few millimeters long. Membrane aeroelasticity has been identified as a tenable method to alleviate these issues: flexible wing structures with geometric twist (adaptive washout for gust rejection, delayed stall) and aerodynamic twist (adaptive inflation for high lift, larger stability margins) are both considered here. Recent investigations in static aeroelastic characterization, including flight loads, wing deformation, flow structures, aeroelastic-tailoring studies through laminate orientation, as well as unconventional techniques based on membrane pre-tension, are reviewed. Multi-objective optimization aimed at improving lift, drag, and pitching moment considerations is also discussed.     

Using TensorFlow-based Neural Network to estimate GNSS single frequency ionospheric delay (IONONet)

In the last 20?years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2?m.