| Presentations |
Alanna Connors (Eureka Sci), Pavlos Protopapas (IIC/CfA)
18 Sep 2007
SciCen 111 706 |
- BUILDING NEW WAYS OF "PAYING ATTENTION":
- Interdisciplinary Astronomy, Physics, and Statistics
- Abstract:
- The California-Harvard AstroStatistics Collaboration is now in its
tenth year (*). We will set the framework by briefly introducing the
projects from the past, and showing examples of current challenges.
The statistics challenges range from deceptively simple (confidence
limits on ratios and rates of very low count Poisson processes) to
many-layered (understanding multi-scale images, spectra,
time-variations from complicated instrumental measurements of the
sky). The applications can be literally cosmic (structure and
evolution of matter and the universe); and the pictures
spectacular. Come join our free-wheeling discussions of the
growing boundaries of twenty-first century astronomy, physics,
and statistics.
- (*) In our understanding, we are currently the longest-running
interdisciplinary group in the Harvard College of Arts and
Sciences. If anyone knows differently, we would be very
interested in finding out!
- Presentation
- Alanna Connors [.pdf]
|
Group
25-26 Sep 2007 |
- Projects
|
Group
16 Oct 2007 |
- proposals
|
Group
23 Oct 2007 |
- proposals
|
Group
30 Oct 2007 |
- proposals
|
Jack Steiner (CfA)
13 Nov 2007
27 Nov 2007 |
- Spinning Stellar Black Holes
- Abstract:
- Astronomers have been studying the properties of black hole
binaries for decades, but it is only within the last few years that it
has become possible to measure black hole spin. Spin is crucially
linked to many exciting frontiers of astrophysics including
gravitational wave astronomy, quasar and stellar mass black hole jets,
the evolution of super-massive black holes, and possibly gamma-ray
bursts. Our group has been pioneering the use of X-ray continuum
fitting to measure black hole spins, and has published results on four
black hole X-ray binary systems. We are now in the process of
developing a robust methodology for our work. I will be presenting an
overview of our current methods, illustrating several statistical
challenges we face, and posing a few questions to my statistically savvy
colleagues.
- [.pdf]
|
Group
18-19 Dec 2007 |
- Projects
|
Paul Baines, et alia
05 Feb 2008 |
- Ages of stellar populations from color-magnitude diagrams;
discussion of papers from astro-ph
|
Group
26 Feb 2008 |
- Projects
|
Andreas Zezas (CfA)
11 Mar 2008
11am EDT |
- Derivation and measurement of LogN-LogS distributions
- Abstract:
- Distributions of the number of observed sources as a function of their
intensity (LogN-LogS) is one of the standard tools for studies of
source populations and setting constrains on their cosmological
evolution. I will briefly present a few examples to demonstrate their
importance for astrophysical studies. I will discuss in detail how they
are derived and the sources of bias and uncertainty in determining
their shape. Finally I will present the most commonly used methods for
their study and I will introduce the concept of a Bayesian fitting
method developed by the Astrostatistics group (mainly Nondas Sourlas
and David van Dyk).
- Presentation [ppt]
|
Group
08 Apr 2008 |
- Projects
- Abstract: To discuss some pressing astrostatistical problems
that may be of interest to stat grad students.
|
Tom Aldcroft
22 Apr 2008 |
- X-ray Stacking
- Abstract:
X-ray stacking provides a way to dig deeper into the ever-growing
archives of X-ray data and estimate the mean properties of sources
that are too faint to detect individually. My interest in this
technique comes from the Chandra Multiwavelength Project (ChaMP),
which is a very large archival survey that covers over 30 sq. degrees
with good optical coverage (dedicated optical imaging / spectroscopy
and Sloan Digital Sky Survey). Unfortunately the heterogeneity of the
ChaMP complicates the process so I'm exploring some variations on the
stacking theme. My talk will start with an overview of the
technique as commonly practiced by astronomers and then discuss
potential problems and a Monte-Carlo method for estimating the derived
parameter distributions. Then I'll talk about stacking in the ChaMP
and bring up some simple ideas for estimating physically interesting
parameters using this dataset.
- [.pdf]
|
Group
06 May 2008 |
- stacking, error propagation on non-linear integrals, etc.
- Abstract:
|
|
-
|
Fall/Winter 2004-2005
Siemiginowska, A. / Connors, A. / Kashyap, V. / Zezas, A. / Devor, J. / Drake, J. / Kolaczyk, E. / Izem, R. / Kang, H. / Yu, Y. / van Dyk, D. |
Fall/Winter 2005-2006
van Dyk, D. / Ratner, M. / Jin, J. / Park, T. / CCW / Zezas, A. / Hong, J. / Siemiginowska, A. & Kashyap, V. / Meng, X.-L. |
Fall/Winter 2006-2007
Lee, H. / Connors, A. / Protopapas, P. / McDowell, J., / Izem, R. / Blondin, S. / Lee, H. / Zezas, A., & Lee, H. / Liu, J.C. / van Dyk, D. / Rice, J.
|
Fall/Winter 2007-2008
Connors, A., & Protopapas, P. / Steiner, J. / Baines, P. / Zezas, A. / Aldcroft, T.
|