Dec 4: Prof. Massimo Ricotti  (Univ. of Maryland)

“TBA”

TBA

Nov 20:  Dr. Andrew Fruchter (STScI)

“Gamma-Ray Bursts from a Safe Distance”

Gamma-Ray Bursts are explosions of nearly unrivalled brilliance.  They can be bright enough to be seen at cosmological distances with the naked eye and can appear to emit the energy of the rest mass of the sun in high-energy photons in a matter of seconds.   I will show evidence that most of these bursts, the so-called long, soft bursts, are produced by the collapse of extremely massive stars in galaxies unlike our own, but similar in many ways to our neighbors, the Magellanic clouds.  The astrophysical origin of a smaller subset of bursts, the short, hard bursts, remains a mystery, though these seem to be distributed much more like the general population of stars in the local universe.  Even if uncertainties surrounding their formation and emission mechanisms remain, both types of bursts may prove useful cosmological probes in the years ahead.

Nov 6: Dr.  Vivienne Wild (IAP, France)

“Timing the Starburst AGN Connection”

There are many theories successful in explaining the observed correlations between lack holes and their host galaxies. In turn, these theories play a crucial role in explaining many other observed aspects of the galaxy population.  However, observational measurements of the interaction of black holes with their hosts remain scarce. I will present results on the growth of black holes in 400 local galactic bulges which have experienced a strong burst of star formation in the past 600 Myr. I will show how the processes at work in this local starburst sample may well be relevant to the co-evolution of black holes and bulges over cosmic time.

Oct 16: Mr.  Krzysztof Nalewajko (Nicolaus Copernicus Astronomical Center)

“Energy dissipation mechanisms in blazers”

I discuss the relevance of studying energy dissipation mechanisms for understanding the emission of blazars. The model of internal shocks has been proven to explain most of the observed activity in blazars. Recently, two phenomena have turned our attention to alternative models. A peculiar outburst of knot HST-1 in the jet of nearby galaxy M87 is most probably a manifestation of reconfinement shocks. The studies of typical length scales, dissipation efficiency and polarization of emission from reconfinement shocks are reported. Observations of fast TeV flares call for processes acting in magnetically dominated inner jet regions. A model of minijets, based on energy dissipation via magnetic reconnection, is presented.

Oct 9: Dr. Robert Preece (Univ. of Alabama, Huntsville)

“GRB Observations with the Fermi Gamma-Ray Space Telescope”

After the first 14 months of operations, the Fermi Gamma-Ray Space Telescope has observed over 320 GRBs, including more than 10 by the ground-breaking Large Area Telescope. As with each new capability, the new observations are re-writing the book about what we thought we knew about GRBs as well as raising new questions. In particular, the joint spectroscopy from the two instruments, covering roughly 6 decades in energy, has revealed some remarkable surprises. In particular, there are some interesting limits that can be placed on the level of violation of Lorentz Invariance by high-energy photons.

Oct 2: Prof. Josh Bloom (UC Berkeley)

“Transients in the Wide-Field Synoptic Era”

The advent of precursor experiments to the Large Synoptic Survey Telescope (LSST) Project  herald a fundamental transition in time-domain astronomy: the data acquisition rates simply swamp the traditional capabilities of astronomers to perform and react to discoveries. New tools are required to abstract humans out of the real-time loop in order to extract novel science from such datastreams. I will discuss the some of scientific aims of the Palomar Transients Factory, the Synoptic All-Sky Infrared Survey (SASIR) and LSST, with a particular focus on rarities and synergies with gravity wave projects. I will also discuss our new NSF Cyber-enabled Discovery Initiative effort to build a computational framework, based in part on parallelized machine-learning algorithms, for classifying time-series data in the context of discovery and follow-up.