Presentations 

Group 13 Sep 2010 Noon2pm 
 Projects and timetable for the year.


Astrostat Haiku 27 Sep 2010 Noon2pm 
 Alanna Connors : Quantifying Doubt and Confidence in Image "Deconvolution"
 [.pptx] ; [.fits]
 Frank Primini : Computing Average Source Intensity for Xray Sources Observed in Multiple Xray Images
 [.pdf]
 Jennifer PossonBrown : Powerlaws and Solar Flares
 [.pdf] ; [.mov]
 Jaesub Hong : Looking for Xray Modulation without relying on Xray Modulation
 [.ppt]
 Kaisey Mandel : Hierarchical Bayesian Models for Type Ia Supernova Light Curves, Dust, and Cosmic Distances
 [.pdf]
 Pavlos Protopapas : Time Series Fitting
 [.ppt]


Pavlos Protopapas 18 Oct 2010 
 Fitting Time Series Parametrically
 Abstract: Determining periodic or quasi periodic signals,
finding low signaltonoise events and determining its nature
in large datasets of astronomical time series is the focus of this talk.
I will describe few astronomical transient phenomena as well as
current and upcoming new surveys that will exasparate the need of new
methodologies to identifying and fitting the nature of the signals. These
methods need to leverage statistical and machine learning
techniques to cope with the low signaltonoise ration and the stupendous
size of the datasets. The rest of the talk will be dedicated to
current efforts and open questions.
 [.ppt] ; [.mov]


Andreas Zezas (Crete) & Vinay Kashyap (CfA) 09 Nov 2010 11:30 am 
 logNlogS
 Abstract: We will discuss the use in Astronomy of
cumulative number distributions, typified as logNlogS curves.
These curves are useful to determine large scale information, and
even serve as useful constraints on cosmology. We will elaborate
on specific cases, as well as discuss biases and observational
complications. Finally, we will point to ways in which a hierarchical
analysis of the same datasets could be used to extract luminosity
functions.
 VK slides [.pdf]
 AZ slides [.ppt]


Aneta Siemiginowska (CfA) 16 Dec 2010 Pratt 12:30pm EST 
 Investigating gammaray properties of young compact radio sources
with Fermi.
 Abstract: Theoretical models predict that
a significant fraction of the energy of a young radio source should be
radiated in gammarays. However, these sources are distant and their
gammaray emission is weak. Therefore they could not have been
detected by gammaray observations before Fermi Gammaray Space
Telescope. The Fermi sensitivity reaches detection limits of many of
these sources, but there have been no reported Fermi detection of a
young radio source to date. In our project we explore available
Fermi/LAT observations and study observational properties of these
objects and will carry out a series of investigations of the data. I
will describe a concept of a full statistical model based on a
Bayesian approach to evaluate the gammaray flux distribution of young
radio sources. I also present some potential issues with this model
and open questions about our approach.


Kaisey Mandel (CfA) 25 Jan 2011 3:30pm EST 
 Hierarchical Bayesian Models for Type Ia Supernova Light Curves, Dust, and Cosmic Distances
 Abstract:
Type Ia supernovae (SN Ia) are the most precise cosmological distance
indicators and are important for measuring the acceleration of the Universe
and the properties of dark energy. To obtain the best distance estimates,
the photometric time series (apparent light curves) of SN Ia at multiple
wavelengths must be properly modeled. The observed data result from
multiple random and uncertain effects, such as measurement error, host
galaxy dust extinction and reddening, peculiar velocities, and distances.
Furthermore, the intrinsic, absolute light curves of SN Ia differ between
individual events: different SN Ia have different intrinsic luminosities,
colors and light curve shapes, and these properties are correlated in the
population. A hierarchical Bayesian model provides a natural statistical
framework for coherently accounting for these multiple random effects while
fitting individual SN Ia and the population distribution. I will discuss
the application of this statistical model to optical and nearinfrared data
for computing inferences about the dust, distances and intrinsic covariance
structure of SN Ia. Using this model, I demonstrate that the combination of
optical and NIR data improves the precision of SN Ia distance predictions by
about a factor of 2 compared to using optical data alone. Finally, I will
discuss some open research problems concerning statistical analysis of
supernova data and their application to cosmology.
 [astroph:1011.5910]
 Presentation slides [.pdf]


Nathan Stein (Harvard) 8 Feb 2011 3:30pm EST 
 Segregating solar features by temperature
 Abstract:
To investigate the thermal properties of the solar corona, images of
the Sun are observed in multiple wavelengths. Efficiently combining the
information from multiple images into a temperature map of the Sun is
necessary in order to take full advantage of the enormous amount of
data arriving as high spatial and temporal resolution images. I will
discuss a clustering method for identifying regions of the Sun with
similar thermal properties, while avoiding the computational expense of
reconstructing the temperature distribution in each pixel.
 Presentation slides [.pdf]


Ashish Mahabal (CalTech) 15 Feb 2011 
 Aspects of Transient Classification
 Abstract:
Various ongoing and forthcoming synoptic surveys provide a unique
opportunity to explore the variable sky. An ever growing number of
transients will be detected per night. A majority of these belong to
fairly well understoodclasses on which one need not waste the scarce
followup resources. As a result selecting which transients to follow
becomes more and more critical for understanding newer and/or rarer
classes. The inputs are diverse and not easy to make a cohesive sense
of especially when one is interested in the classification in as close
to realtime as possible. We will present various aspects of this
process, the current methodologies and understanding, and a sense of
where we are heading.
 Presentation slides [.pdf]


Jae Sub Hong (CfA) 29 Mar 2011 Noon 
 Looking for true modulation period through energy quantiles
 Abstract:
We have discovered 10 periodic Xray sources and 11 candidates in the
1 Ms chandra ACIS observation of the Limiting Window, a low extinction
region at 1.4 deg south of the Galactic center. Their Xray and optical
properties are consistent with those for magnetic cataclysmic variables
(MCVs), which presumably account for a large number (>3000) of the low
luminosity hard Xray sources in the Bulge. The sheer number of
the Bulge Xray sources found in the Galactic center region indicates the
importance of their nature in understanding the formation and evolutionary
history of the inner Galaxy. We used three search routines for finding
Xray periodicity: LombScargle routine, Buccheri's z2 statistics,
the Epoch Folding method. Multiple periods are found in some
sources, and it is often difficult to separate the true period from
its simple harmonics. We use energy quantiles in attempt to validate or
find the periodicity that truly represents the emission geometry.
 Presentation slides: [.pptx] ; [.pdf]


David Stenning (UC Irvine) 29 Mar 2011 1 pm 
 Automatic Classification of Sunspot Groups Using SOHO/MDI Magnetogram and WhiteLight Images
 Abstract:
While solar data is being generated at an unprecedented rate,
most sunspot classification is still done manually by experts. This is a
laborintensive process and, as with all manual procedures, is susceptible
to human observer biases. Using SOHO/MDI magnetogram and whitelight
images, we propose a system for automatically classifying sunspot groups
into four broad classes based on the Mount Wilson scheme. This scheme uses
magnetic activeregion structure as seen in magnetogram images,
specifically areas of opposite polarity magnetic flux, to classify sunspot
groups using simple rules. By utilizing techniques from mathematical
morphology, we extract features that can be used in classification
algorithms to produce an automatic sunspot classification procedure. I
will discuss the progress we have made as well as plans for future work.
 Presentation slides [.pdf]


Antonaldo Diaferio (Universita' degli Studi di Torino) 19 Apr 2011 Noon SciCen 705 
 The expansion history of the Universe: myths and facts
 Abstract:
Data from extensive surveys of highredshift type Ia supernovae and
gammaray bursts have usually been interpreted as a robust indication
that the Universe expansion had an initial deceleration phase
followed by the present acceleration phase. When analysed with a
proper Bayesian approach, this interpretation is not in fact as
robust as usually assumed. I show that the expansion history predicted
by conformal gravity, which is substantially different from the
standard model, can accommodate the data equally well. The Bayesian
evidence is required to discriminate between the two models.
 Diaferio, Ostorero, & Cardone, Gammaray bursts as cosmological probes: ΛCDM vs. conformal gravity, 2011,
arXiv:1103.5501
 Presentation: [.pdf]


Jin Xu (UC Irvine) 3 May 2011 
 pyBLoCXS
 Abstract:
 Slides [.pdf]


Brandon Kelly (CfA) 31 May 2011 Noon SciCen 705 706 
 Modeling active galactic nuclei variability with stochastic processes
 Abstract:
 I describe a statistical model for the Xray fluctuations of
accreting black holes. The model is formulated in the time domain
via a set of stochastic differential equations, and I describe a
Bayesian approach for performing statistical inference using the
model. Specifically, I model the Xray fluctuations as a mixture
of OrnsteinUhlenbeck processes with varying relaxation time scales.
The mixture of OUprocesses is derived as the solution to the
stochastic diffusion equation, enabling an astrophysical interpretation
of the results. The technique is not biased by red noise leak,
aliasing, irregular sampling, and measurement error, and is
computationally efficient. We apply our model to the Xray time
series of 10 local AGN and show that our model is both a good fit
to the data, and is able to recover previous results with increased
precision. We recover the previously known correlation between the
black hole mass and characteristic time scale of the Xray fluctuations,
and find a tight anticorrelation between the black hole mass and
the amplitude of the driving noise field in our model, which is
proportional to the amplitude of the high frequency Xray PSD.
 Slides [.ppt]


Paul Baines and Irina Udaltsova (UCDavis) 12 Jul 2011 9am PDT/Noon EDT SciCen 706 
 Bayesian estimation of logNlogS
 Abstract:
The study of source populations is often conducted using the
cumulative distribution of the number of sources detected at a given
sensitivity. The resulting "log(N>S)logS" distribution can be used
to compare and evaluate theoretical models for source populations
and their evolution. In practice, however, inferring properties of
source populations from observational data is complicated by the
presence of detectorinduced uncertainty and bias. This includes
background contamination, uncertainty on both intensity and location
of sources, and, most challenging, the issue of nondetections or
unobserved sources. Since the probability of a nondetection is a
function of the unobserved flux, the missing data mechanism is
nonignorable. We present a computationally efficient Bayesian
approach for inferring physical model parameters and the corrected
log(N>S)log(S) distribution for source populations. Our method
extends existing work in allowing for both nonignorable missing
data and an unknown number of unobserved sources. Importantly, our
method is also scalable in the number of observed sources, and
computationally insensitive to the number of missing sources. By
correcting for the nonignorable missing data mechanism and other
detection phenomena, we are able to obtain corrected estimates of
the flux and luminosity distribution of source populations.
 SCMA V poster [.pdf]
 Presentation slides (updated) [.pdf]


Mark Weber (SAO) 26 Jul 2011 Noon EDT SciCen 706 
 Characterizing Underconstrained DEM Analysis
 Abstract:
Differential emission measures (DEMs) are one of the principal ways
that solar astronomers derive physical properties of the optically
thin corona from observations. Imaging instruments (e.g., the
Atmospheric Imaging Assembly on the Solar Dynamics Observatory) have
several advantages over spectroscopic instruments, such as cadence,
field of view, and spatial resolution, but do not have enough
independent channels to adequately constrain the temperature
distributions of the observed plasmas. Thus, DEM analysis with these
data sets is an illposed, underconstrained linear algebra problem. I
discuss some of the shortcomings of solution techniques in the
literature; in particular, none of the extant methods provide a way to
distinguish and identify the infinite set of solutions to the
underconstrained problem as a subset of all possible DEMs, which has
consequences for physical interpretations. I present the ConvexHull
method of DEM analysis, which overcomes several of the pitfalls of DEM
analysis, and which also highlights an interesting aspect of the
instrument response functions that has implications for setting up a
Bayesian framework for error propagation. I have not yet set up such a
framework and look forward to some interesting discussion on that point.
 Presentation [.pptx]






Fall/Winter 20042005
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 20052006
van Dyk, D. / Ratner, M. / Jin, J. / Park, T. / CCW / Zezas, A. / Hong, J. / Siemiginowska, A. & Kashyap, V. / Meng, X.L. 
Fall/Winter 20062007
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 20072008
Connors, A., & Protopapas, P. / Steiner, J. / Baines, P. / Zezas, A. / Aldcroft, T.

Fall/Winter 20082009
H. Lee /
A. Connors, B. Kelly, & P. Protopapas /
P. Baines /
A. Blocker /
J. Hong /
H. Chernoff /
Z. Li /
L. Zhu (Feb) /
A. Connors (Pt.1) /
A. Connors (Pt.2) /
L. Zhu (Mar) /
E. Kolaczyk /
V. Liublinska /
N. Stein

Fall/Winter 20092010
A.Connors /
B.Kelly /
N.Stein, P.Baines /
D.Stenning / J. Xu / A.Blocker /
P.Baines, Y.Yu /
V.Liublinska, J.Xu, J.Liu /
X.L. Meng, et al. /
A. Blocker, et al. /
A. Siemiginowska /
D. Richard /
A. Blocker /
X. Xie /
X. Jin /
V. Liublinska /
L. Jing

AcadYr 20102011
Astrostat Haiku /
P. Protopapas /
A. Zezas & V. Kashyap /
A. Siemiginowska /
K. Mandel /
N. Stein /
A. Mahabal /
J.S. Hong /
D. Stenning /
A. Diaferio /
X. Jin /
B. Kelly /
P. Baines & I. Udaltsova /
M. Weber

AcadYr 20112012
