Presentations 

Workshop 20 Sep 2017 10am4pm EDT Phillips Auditorium at CfA 
 AstroStat Day
 10:00am  12:10pm : Siemiginowska, Vikhlinin, Finkbeiner, Portillo, Daylan, Speagle, B. Johnson
 12:30pm  1:30pm : Reeves, Winter
(SolarStat, in conjunction with HEAD Lunch Talks)
 2:00pm  4:00pm : Grindlay, M. Johnson, Blackburn, Bouman, Avelino, Zucker
 4:00pm  5:00pm : Discussion


Josh Speagle (CfA) 26 Sep 2017 1:07pm EDT Pratt (PerkinG, CfA) 
 Dynamic Nested Sampling
 Nested Sampling is a relatively new method for estimating the Bayesian evidence (with the posterior estimated as a byproduct) that integrates over the posterior by sampling in nested "shells" of constant likelihood. Its ability to sample from complex, multimodal distributions in a flexible yet efficient way combined with several available sampling packages has contributed to its growing popularity in (astro)physics. In this talk I will outline the basic motivation and theory behind Nested Sampling, derive various statistical properties associated with the method, and discuss how it is applied in practice. I will then talk about how the overall framework can be extended in Dynamic Nested Sampling to accommodate adding samples "dynamically" during the course of a run. These samples can be allocated to maximize arbitrary objective functions, allowing Dynamic Nested Sampling to function as a posteriororiented sampling method such as MCMC but with the added benefit of welldefined stopping criteria. I will end by applying Dynamic Nested Sampling to a variety of synthetic and realworld problems using an opensource Python package I've been developing (dynesty).
 Presentation slides [.pdf]
 See also: MultiNest ; PolyChord [url


Gabriel Collin (MIT) 21 Nov 2017 1:07pm EST Pratt (PerkinG, CfA) 
 Searching for the origin of astrophysical neutrinos using a nonPoissonian statistical method
 Abstract: The IceCube neutrino observatory was designed to detect astrophysical neutrinos, which originate from outside of our solar system. IceCube has detected candidate astrophysical events, and measured a diffuse flux, but the source of these neutrinos so far remains unknown. Current approaches look for "hot spots" of neutrino events in the sky. It is also possible to describe a population of sources in terms of the number of observed events, forming a nonPoissonian statistical distribution. This distribution was used to show that the excess of gamma rays measured by FermiLAT around the galactic center was likely due to point sources rather than decaying dark matter. In this talk, I will present the application of this statistical method to the search for point sources in IceCube.
 Evidence for Unresolved GammaRay Point Sources in the Inner Galaxy, Lee et al. arxiv:1506.05124 [.url]
 NPTfit github.com/bsafdi/NPTFit [.url]


Katy McKeough & Shihao Yang (Harvard) 28 Nov 2017 1:07pm EST SciCen 706 
 Defining regions that contain Xray jets in highredshift quasars
 Abstract:
Using only the Xray observation of a quasar and a jet, we are interested in creating an outline around an extended source (jet). Astronomers are interested in delineating jets from their quasar source and background radiation. This is particularly difficult in images of high redshift jets taken in Xray where there are a limited number of pixel counts. McKeough et al. 2016 and Stein et al. 2015 proposes a method where jets are detected using previously defined regions of interest (ROI). However, we do not always have supplementary information to predetermine these ROI and the size and shape can greatly affect flux/luminosity measurements and power of detection. Low Count Image Reconstruction and Analysis (LIRA) has been tremendously successful in analyzing low counts images and extracting structure smeared out by the PSF. However, the intensities derived using it are pixellated. That is, LIRA is unaware of correlations that may exist between adjacent pixels in the real image. In order to group pixels of a similar nature, we impose a successor or postmodel on the output of LIRA. We adopt the Ising model, which has been used extensively in Condensed Matter Physics to model electron spin states, as a prior on assigning the pixels to either the background or the ROI.
 Presentation slides [.pdf]


Katy McKeough & Luis Campos (Harvard) 12 Dec 2017 12:37pm EST CfA Library 
 Ask A Statistician: An oppportunity for astronomers at the CfA to ask statistics questions of statisticians; from the mundane to the philosophical, bring your statistics problems to be discussed by the panel
 We will be going through several applications of statistics in astronomy. Each application will serve as the backdrop for discussing a different statistical technique. We will suggest partial solutions or new directions for each of these proposed issues that we hope will stimulate further questions and discussion.
The following examples are:
 Propagating asymmetrical error bars via parametric bootstrap.
 Correlation between two time series observations.
 Using external information as a prior in Bayesian inference.
 Explanation of shrinkage.
 Detection significance with multiple hypothesis testing.
 Presentation Slides [url]
 JamesStein Estimator R model [.rmd]


Michelle Ntampaka (CfA) 23 Jan 2018 1:07pm EDT SciCen 706 
 Constraining Sigma8 and OmegaMatter with the Velocity Distribution Function
 Abstract: I will present the Velocity Distribution Function (VDF), a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements. In this new method, the probability distribution of velocities for each cluster in the sample are summed to create a new test statistic, which can be measured more directly and precisely than the more standard halo mass function, and can be robustly predicted with cosmological simulations which capture the dynamics of subhalos or galaxies. I will present preliminary constraints on sigma8 and omegamatter from spectroscopic observations of the HeCSSZ clusters.


Herman Marshall (MIT) 06 Feb 2018 1:07pm EDT SciCen 706 
 Xray Polarimetry





