Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userHide and seek between Andromedas halo, disk, and giant stream
110
0
0.0
(
0
)
Authors
Gisella Clementini
Ask ChatGPT about the research
No Arabic abstract
Photometry in B, V (down to V ~ 26 mag) is presented for two 23 x 23 fields of the Andromeda galaxy (M31) that were observed with the blue channel camera of the Large Binocular Telescope during the Science Demonstration Time. Each field covers an area of about 5.1kpc x 5.1kpc at the distance of M31 ((m-M)o ~ 24.4 mag), sampling, respectively, a northeast region close to the M31 giant stream (field S2), and an eastern portion of the halo in the direction of the galaxy minor axis (field H1). The stream field spans a region that includes Andromedas disk and the giant stream, and this is reflected in the complexity of the color magnitude diagram of the field. One corner of the halo field also includes a portion of the giant stream. Even though these demonstration time data were obtained under non-optimal observing conditions the B photometry, acquired in time-series mode, allowed us to identify 274 variable stars (among which 96 are bona fide and 31 are candidate RR Lyrae stars, 71 are Cepheids, and 16 are binary systems) by applying the image subtraction technique to selected portions of the observed fields. Differential flux light curves were obtained for the vast majority of these variables. Our sample includes mainly pulsating stars which populate the instability strip from the Classical Cepheids down to the RR Lyrae stars, thus tracing the different stellar generations in these regions of M31 down to the horizontal branch of the oldest (t ~ 10 Gyr) component.
rate research
Read More
We train embodied agents to play Visual Hide and Seek where a prey must navigate in a simulated environment in order to avoid capture from a predator. We place a variety of obstacles in the environment for the prey to hide behind, and we only give the agents partial observations of their environment using an egocentric perspective. Although we train the model to play this game from scratch, experiments and visualizations suggest that the agent learns to predict its own visibility in the environment. Furthermore, we quantitatively analyze how agent weaknesses, such as slower speed, effect the learned policy. Our results suggest that, although agent weaknesses make the learning problem more challenging, they also cause more useful features to be learned. Our project website is available at: http://www.cs.columbia.edu/ ~bchen/visualhideseek/.
Signaling pathways and networks determine the ability to communicate in systems ranging from living cells to human society. We investigate how the network structure constrains communication in social-, man-made and biological networks. We find that human networks of governance and collaboration are predictable on teat-a-teat level, reflecting well defined pathways, but globally inefficient. In contrast, the Internet tends to have better overall communication abilities, more alternative pathways, and is therefore more robust. Between these extremes the molecular network of Saccharomyces cerevisea is more similar to the simpler social systems, whereas the pattern of interactions in the more complex Drosophilia melanogaster, resembles the robust Internet.
We use $sim$83,000 star-forming galaxies at $0.04<z<0.3$ from the Sloan Digital Sky Survey to study the so-called fundamental metallicity relation (FMR) and report on the disappearance of its anti-correlation between metallicity and star formation rate (SFR) when using the new metallicity indicator recently proposed by Dopita et al. In this calibration, metallicity is primarily sensitive to the emission line ratio [NII]$lambda$6584 / [SII]$lambdalambda$6717, 6731 that is insensitive to dilution by pristine infalling gas that may drive the FMR anti-correlation with SFR. Therefore, we conclude that the apparent disappearance of the FMR (using this new metallicity indicator) does not rule out its existence.
We report the results of our follow-up campaign of the peculiar supernova ASASSN-15no, based on optical data covering ~300 days of its evolution. Initially the spectra show a pure blackbody continuum. After few days, the HeI 5876 A transition appears with a P-Cygni profile and an expansion velocity of about 8700 km/s. Fifty days after maximum, the spectrum shows signs typically seen in interacting supernovae. A broad (FWHM~8000 km/s) Halpha becomes more prominent with time until ~150 days after maximum and quickly declines later on. At these phases Halpha starts to show an intermediate component, which together with the blue pseudo-continuum are clues that the ejecta begin to interact with the CSM. The spectra at the latest phases look very similar to the nebular spectra of stripped-envelope SNe. The early part (the first 40 days after maximum) of the bolometric curve, which peaks at a luminosity intermediate between normal and superluminous supernovae, is well reproduced by a model in which the energy budget is essentially coming from ejecta recombination and 56Ni decay. From the model we infer a mass of the ejecta Mej = 2.6 Msun; an initial radius of the photosphere R0 = 2.1 x 10^14 cm; and an explosion energy Eexpl = 0.8 x 10^51 erg. A possible scenario involves a massive and extended H-poor shell lost by the progenitor star a few years before explosion. The shell is hit, heated and accelerated by the supernova ejecta. The accelerated shell+ejecta rapidly dilutes, unveiling the unperturbed supernova spectrum below. The outer ejecta start to interact with a H-poor external CSM lost by the progenitor system about 9 -- 90 years before the explosion.
The goal of an infection source node (e.g., a rumor or computer virus source) in a network is to spread its infection to as many nodes as possible, while remaining hidden from the network administrator. On the other hand, the network administrator aims to identify the source node based on knowledge of which nodes have been infected. We model the infection spreading and source identification problem as a strategic game, where the infection source and the network administrator are the two players. As the Jordan center estimator is a minimax source estimator that has been shown to be robust in recent works, we assume that the network administrator utilizes a source estimation strategy that can probe any nodes within a given radius of the Jordan center. Given any estimation strategy, we design a best-response infection strategy for the source. Given any infection strategy, we design a best-response estimation strategy for the network administrator. We derive conditions under which a Nash equilibrium of the strategic game exists. Simulations in both synthetic and real-world networks demonstrate that our proposed infection strategy infects more nodes while maintaining the same safety margin between the true source node and the Jordan center source estimator.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
