Black Board Lectures of the Year 2016

Lecture 1: Radio Interferometry SS 2016

Prof. F. Bertoldi, Prof. P. Schilke and Prof. M. Kramer, PD R. Mauersberger, Dr. S. Mühl

The course "Radio Interferometry: Methods and Science" offers a hands-on overview of major aspects of radio/mm/submm interferometry for master students, PhD students and senior astronomers. The lectures start with a general introduction to radio interferometry and data reduction, followed by an overview of various fields of research and the special observing modes that they require, given by experts of the respective fields. The latest developments of selected world-leading radio/mm/submm interferometers will be presented as well.

The course also comprises a hands-on tutorial, where participants learn how to reduce interferometric data with the Common Astronomy Software Applications (CASA) package.

On 13 April, we will collect the email addresses of all participants to set up a mailing list that we will use to circulate updates, material and other information related to the course. If you can't attend on 13 April, but are interested in participating in the course, please contact us before 17 April.

We will offer remote access to the lectures and tutorials on a best-efforts basis (maximum 5 remote locations). If you would like to follow the course from a remote location, please contact us before 01 April.

Note: the lectures start on 13 April 2016!

Preliminary Schedule

13.04.

10:15 - 11:45

Introduction to interferometry I

R. Mauersberger

12:00 - 13:00

CASA (introduction, installation)

S. Mühle

20.04.

10:15 - 11:45

Introduction to interferometry II

R. Mauersberger

12:00 - 13:00

CASA (first steps, trouble-shooting)

S. Mühle, R. Schaaf

27.04.

10:15 - 11:45

Calibration

A. Sánchez-Monge

12:00 - 13:00

CASA (data inspection and editing I)

Karim/Magnelli

04.05.

10:15 - 11:45

Imaging

A. Sánchez-Monge

12:00 - 13:00

CASA (data inspection and editing II)

Karim/Magnelli

11.05.

10:15 - 11:45

Spectral line interferometry

S. Mühle

12:00 - 13:00

CASA (calibration I)

Karim/Magnelli

18.05.

10:15 - 11:45

no lecture

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12:00 - 13:00

no tutorial

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25.05.

10:15 - 11:45

no lecture (Dies academicus)

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12:00 - 13:00

no tutorial

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01.06.

10:15 - 11:45

Polarimetry

Y. Pidopryhora

12:00 - 13:00

CASA (calibration II)

Karim/Magnelli

08.06.

10:15 - 11:45

VLBI

Olaf Wucknitz

12:00 - 13:00

data reduction in AIPS

S. Mühle

15.06.

10:15 - 11:45

ALMA

S. Mühle

12:00 - 13:00

CASA (imaging I)

Karim/Magnelli

22.06.

10:15 - 11:45

SKA

M. Kramer

12:00 - 13:00

CASA (imaging II)

Karim/Magnelli

29.06.

10:15 - 11:45

LOFAR

A. Horneffer

12:00 - 13:00

CASA (analysis tools I)

Karim/Magnelli

06.07.

10:15 - 11:45

Proposal Preparation

S. Mühle

12:00 - 13:00 CASA (analysis tool II) Karim/Magnelli
13.07. 10:15 - 11:45 buffer
12:00 - 13:00 CASA (questions session) Karim/Magnelli
20.07. 10:15 - 11:45 student presentations all

Lecture 2: Statistics & Data Modeling Bootcamp | Douglas Applegate (AIfA)

Overview

Perhaps you have been told to “fit a model to the data.” But how do you actually do that? Should you use least­squares, maximum likelihood, or MCMC? What is the difference, anyway? What software should you use? How do you know if what you are doing actually describes the data or proves something? Is a different model better? We will aim to answer these questions in this bootcamp. Each session will be a hybrid of lecture, discussion, and computer­based exercises where you will learn both theoretical background and practical skills that will immediately transfer to your research.

Learning Objectives

By the end of the bootcamp, you should be able to

  • check the validity and correctness of statistical methods
  • recognize where Gaussian approximations break down, and choose appropriate alternative algorithms and modeling strategies
  • employ appropriate algorithms, such as minimizing chi­squared fits and running Markov Chain Monte Carlo (MCMC) simulations to calculate parameter estimates and uncertainties
  • evaluate the quality of a model fit, and quantitatively compare different models

Important: Laptops & Special Software are Required

  • Please bring a laptop to each session. 
  • Before the first class, setup access to the full Python Scientific Computing Stack by:
    • installing Anaconda for free from https://store.continuum.io/cshop/anaconda/ on your laptop (preferred)

­­ or ­­

    • signing up for a free account at https://www.wakari.io/waka


Essential parts of each class will be taught through computer­based exercises that you will complete in pairs.

Why exercises? Practice and get immediate feedback, which will enable you to learn practical skills. Plus, you can use working code you write in class on your research data immediately.

Why pairs? Save your sanity. By programming in pairs, you will catch software bugs that would otherwise leave you sitting there, confused and frustrated. Learn new tips and tricks from a wide pool of your colleagues by switched who you pair­program with each day.

Schedule

Lecture 1: May 10 at 14:00 in 0.01: Introduction to Scientific Python. Only for those unfamiliar with Python, Numpy, Matplotlib, and IPython Notebooks  | video

Lecture 2: May 11 at 14:00 in 0.02: Simulating data, fitting lines, and where the basics begin to break | video

Lecture 3: May 12 at 14:00 in 0.02: Probability, probability distributions,confidence intervals, maximum likelihood  | video

Lecture 4: May 13 at 14:00 in 0.02: Probability, probability distributions,confidence intervals, maximum likelihood | video 

Lecture 5: May 17 at 14:00 in 0.01: Model checking, central limit theorem, fitting linear models with Gaussian statistics | video 

Lecture 6: May 18 at 14:00 in 0.02: Markov Chain Monte Carlo basics, unbinned maximum likelihood models | video

Lecture 7: May 19 at 14:00 in 0.02: Model Selection, p­-values, and the look-­elsewhere effect | video

Lecture 8: May 20 at 14:00 in 0.02: Wrapping up | video

Lecture 3: HYDRODYNAMIC AND MAGNETOHYDRODYNAMIC TURBULENCE AND DYNAMOS FOR ASTROPHYSICISTS

SS 2016/Anvar Shukurov

Lectures on Sept 20, 21, 22 at 10:00 in Room 0.012 AIfA:

video day 1 part 1 | part 2 

video day 2 part 1 | part 2

video day 3 part 1 | part 2

slides



OUTLINE OF SYLLABUS

Introduction to random functions
    Correlation and structure functions
    Ensemble, volume and time averaging. Ergodicity
    Fourier spectra

Phenomenology of fluid turbulence
    Energy conservation
    Spectral energy transfer
    Kolmogorov's theory
    Turbulent diffusion
    
Interstellar turbulence
    Energy sources
    Observational signatures
    Parameters of interstellar turbulence
    The role of turbulence in galaxies
    
Magnetohydrodynamic turbulence
    Isotropic Alfven wave turbulence
    Anisotropic Alfven wave turbulence

Dynamos
    The necessity of dynamo action in astrophysics
    Fast and slow dynamos
    Turbulent dynamos
    Mean-field dynamos in galaxies
    Fluctuation dynamos
    Seed magnetic fields


FURTHER READING
Especially useful texts are marked with asterisk

A. HYDRODYNAMIC TURBULENCE

*M. Van Dyke, An Album of Fluid Motion. Parabolic Press, Stanford,
1982

*U. Frisch, Turbulence. The Legacy of A. N. Kolmogorov. Cambridge
Univ. Press, Cambridge, 1995

*H. Tennekes & J. L. Lumley, A First Course in Turbulence. MIT Press,
Cambridge, MA, 1972

J. Jimenez, Turbulence. In Perspectives in Fluid Dynamics. A
Collective Introduction to Current Research. Ed. by
G. K. Batchelor, H. K. Moffatt & M. G. Worster. Cambridge Univ.
Press, Cambridge, 2000

A. S. Monin & A. M. Yaglom, Statistical Fluid Mechanics. Vols 1 & 2.
Ed. by J. Lumley. MIT Press, Cambridge, MA, 1971 & 1975

S. Panchev, Random Functions and Turbulence. Pergamon Press,
Oxford, 1971

B. MAGNETOHYDRODYNAMIC TURBULENCE

D. Biskamp, Magnetohydrodynamic Turbulence. Cambridge Univ.
Press, Cambridge, 2003

C. ASTROPHYSICAL TURBULENCE

*M.-M. Mac Low & R. S. Klessen, Control of star formation by
supersonic turbulence. Rev. Mod. Phys., 76, 125–194, 2004
(astro-ph/030193)

*B. G. Elmegreen & J. Scalo, Interstellar turbulence I: Observations
and processes. Ann. Rev. Astron. Astrophys., 2004 (astro-ph/0404451)

*J. Scalo & B. G. Elmegreen, Interstellar turbulence II: Implications and
effects. Ann. Rev. Astron. Astrophys., 2004 (astro-ph/0404452)

. . . and references therein    

 
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