Lecture 17 – AIPS and other animals

1. Lecture 17 – AIPS and other animals • Some thoughts about the design of big astronomical software packages. • Packages to analyse radio interferometer data. • AIPS description. • High-energy astronomy.

2. Astronomy data reduction packages • Software which implements (often complex) algorithms to calibrate and process (sometimes very large) volumes of data from astronomical instruments. DATA Journal of Very Good Research Science

3. Design criteria (my opinions): • User interface is crucial – but difficult. • Principles of good design have been worked out – but you cannot ‘re-educate’ users. You have to cater to their prejudices. • Trustability • Again users and designers may have different ideas about when code deserves to be trusted! • Who should write the code – professional software engineers, or astronomers? • Professional software engineers give a good product – robust, maintainable, ‘trustable’ in their eyes – but it may not be what the users want. There is also a high incidence of manic zealotry among SEs.

4. Design criteria (my opinions): • Astronomers have intimate knowledge of what they want – but are not usually professional coders – although since coding is ‘easy to learn but hard to master’, they may not be enough aware of their deficiencies in this respect. • Solution: code should be written by professionals, but under close supervision/consultation with astronomers. • Code should not be ‘owned’ by a single person. • Portable installation.

5. Design criteria (my opinions): Application programs or ‘tasks’ Common code in well-documented libraries User-contributed applications. A well-documented Applications Programmer Interface (API) Data in a well-documented file format.

6. Design criteria (my opinions): • How finely to divide up the work between tasks? • People seem to have different opinions. In some packages there are giant tasks which seem to allow you to do almost anything by judicious choice among a zoo of parameters. • On the whole though I prefer tasks which each do something fairly simple. • Then join them up in a script if more complicated single-command processing is necessary.

7. Interferometry reduction packages: • Astronomical Image Processing System (AIPS) • Started 1978; 1.4 M lines of code; hosted by NRAO. Fortran 77 but highly ‘tweaked’ for speed. • Miriad • 80s? Designed to process ATCA data (Australia). • CASA (née AIPS++) • Started about 2004 (building upon the AIPS++ suite which was started in the 90s but abandoned in controversial circumstances). Designed for ALMA and eVLA. C++, but python scripting interface. • MeqTrees • First release 2007. Hosted by ASTRON (Netherlands). Implements more rigorous interferometer theory.

8. AIPS • http://www.aips.nrao.edu/ • AIPS is showing its age in many ways but it is still the ‘default package’ for most interferometry data reduction. A huge number of man-years of experience on AIPS has been accumulated and astronomers have come to trust it deeply. • For the casual user, its drawbacks are: • There is a very large zoo of tasks. Almost certainly there is one which will do your required job: the problem is finding it. • Many tasks have a very large zoo of parameters.

9. AIPS • The parameter interface is rudimentary. As is usual with even moderately complicated systems of parameters, some parameters control whether others are read or not. In AIPS, these logical relations are often obscure. It is therefore difficult for the casual user to be confident that all needed parameters have been set, and no angst has been spent on setting unnecessary ones. • AIPS has its own shell, its own private file system, and in general AIPS forces you to play by its rules. You cannot easily get into your data and fiddle with it.

10. AIPS • By far the best way to learn AIPS is by experience processing real data, under the supervision of an expert user. • Alas... there are no expert users at UCT. • This is a pity, because here in SA we will shortly have a ground-breaking interferometer in our own backyard - MeerKAT. Opportunities will be there for the taking! • But this is also a good opportunity to move away from AIPS to something a bit more modern. • Why learn anything about AIPS then? • Because it is the only package I have had any experience with! • And because there are many similarities across packages.

11. High-Energy Astronomy • Means x-rays and gamma rays. • It’s convenient at this end of the spectrum to concentrate on the particle part of the quantum wave-particle duality. • So we usually talk about the energy of the photons which make up the radiation, rather than their wavelength or frequency. • A convenient energy unit is the electron volt (eV). • Confusingly, x-ray fluxes are often cited in ergs. • 1 eV ~ 1.6 ×10-19 joules ~ 1.6 ×10-12 ergs. • From E=hν, 1 eV ~ 2.42 ×1014 Hz.

12. High-Energy Astronomy • X-rays: roughly speaking, from ~100 to ~105 eV. • We speak of hard (= high energy) vs soft x-rays. • Gamma: anything higher. • Physical sources: as the name ‘high energy’ implies, very energetic events tend to generate x-rays and gamma rays. • Thermal radiation if the temperature is >106 K – eg: • the sun’s corona ( soft x-rays) • Black Hole accretion disk ( hard x-rays) • Nuclear fusion ( soft x-rays) • Matter falling into a gravity well. • Supernova ( hard x-rays, gammas) • GRB (?) ( gamma rays) • It is interesting that radio and x-ray images often follow similar brightness distributions. • Because hot plasma  relativistic synchrotron emission.

13. X-ray Observatories • You need to be in space, because the atmosphere efficiently absorbs x-rays. • Most of the currently interesting results are coming from: • Chandra (good images, so-so spectra) • XMM-Newton (so-so images, good spectra) • SWIFT (looks mostly at GRB afterglows) although there are several more. • How do you make an image from x-rays? Don’t they go through everything? So how can you make a reflector?

14. X-ray Observatories - mirrors • Wolter grazing-incidence mirrors: • reflectivity of any EM radiation gets higher for a low angle of incidence. Double reflection Can nest many shells of differing diameter. Paraboloid Hyperboloid Behaves like a thin lens set here.

15. X-ray Observatories - detectors • Charge Coupled Devices (CCDs) are used, just as for optical. The workings are slightly different though. e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- e- ...then read out. At optical wavelengths: At x-ray wavelengths: e- e- e- e- e- e- e- e- e- e- e- e- e- ...then read out. Time

16. X-ray Observatories - detectors • Basic substance of the CCD is silicon – but ‘doped’ with impurities which alter its electronic structure. • There are several sorts, eg: • Metal Oxide Semiconductor (MOS) • pn • The CCD surface is divided into an array of pixels. • A photon striking the material ejects some electrons which sit around waiting to be harvested. • The number of ejected electrons is proportional to the energy of the photon.

17. X-ray Observatories - detectors • CCD operation is in frame cycles. Long accumulation time Short readout time

18. X-ray Observatories - detectors • CCDs have to be read out sequentially (slow). Columns Rows Digitizer (ADC) Out Readout row

19. X-ray Observatories - detectors • The readout operation consists of the following steps: • For each CCD row, starting with that nearest the readout row, move the charges into the next lowest row. • In the readout row, starting at the pixel nearest the output, shift the charges into the next lowest pixel. • Convert the analog charge quantity (it is an integer number of electrons, but such a large integer that we can ignore quantum ‘graininess’) to a digital number. • This is done in an Analog to Digital Converter (ADC). • Send that number to the outside world.

20. X-ray Observatories - detectors • For x-ray detection, we want to arrange the frame duration so that we expect no more than 1 x-ray per pixel per frame. • Why? Because if we can be pretty sure that all the charge per pixel per frame comes from a single x-ray, we can determine the energy of the x-ray.  x-ray spectroscopy. • XMM example: • Spatial resolution is ~1 arcsec (fractional ~10-3). • Spectral resolution is ~100 eV (fractional ~10-2). • Time resolution is ~1 second (fractional ~10-5).