Thesis

Optimisation of data reduction of adaptive-optics assisted observations

• Call:

  IDPASC Portugal - PHD Programme 2019

• Academic Year:

  2019 / 2020

• Domain:

  Astrophysics

• Supervisor:

  Carlos M Correia

• Co-Supervisor:

  Paulo Garcia

• Institution:

  Universidade do Porto

• Host Institution:

  Universidade do Porto

• Abstract:

  The widespread deployment of adaptive-optics systems in existing and in foreseen telescopes is changing the paradigm of data analysis. Adaptive optics (AO) systems compensate for the blurring effects of the Earth’s turbulent atmosphere, called “seeing”, in real-time, giving superior spatial resolution over space-based alternatives at a fraction of the cost. AO systems have been deployed on nearly all of the world’s largest telescopes, including the European Very Large Telescope (VLT) and its 10m-class telescopes counterparts. The power of AO is now widely recognized and it will be built into the 1st-light instruments of ALL the next-generation giant telescopes -- the European ELT, the Giant Magellan Telescope and the Thirty Meter Telescope (Ramsay+ 2014, Matt+ 2006, Sanders+ 2014) with diameters up to 40m. Despite its effectiveness and undisputable gains, AO systems are complex and produce images with point-spread functions (PSFs) that that depend on many factors, like the flavour of AO that feeds each instrument, the local characteristics of the atmosphere, the field of view, the availability and adequacy of natural guide stars, etc. In other words, we went from relatively simple optical systems that produced low-resolution but stable and well-defined PSFs determined mainly by the local seeing and by the diameter of the telescope in classical observatories, to state-of-the-art AO-assisted systems that reach much closer to the full potential of the telescope in terms of spatial resolution but that produce PSFs that vary in time and space and that are more challenging to model (Veran+, 1997, Gilles+, 2012). The development of these systems represented a huge leap forward in astronomical observations, but it was not (yet) met with an equivalent development of data analysis algorithms. We are therefore at a point where breakthrough science with AO-assisted observations on current and future ground-based telescope requires new paradigms in data-analysis algorithms in order to extract the most precise measurements of photometric brightness, astrometric position, and morphology for planets, stars, and galaxies. Our team is leading a large effort to bridge this important gap between the technology and the science facilitated by AO assisted instruments. For this end, we are seeking a candidate to collaborate in one or several of the following fronts: 1. Exploring the parameter space of AO-corrected PSFs for the ELTs The student/fellow will evaluate the accuracy to which the PSF should be known to meet the most representative science cases on ELTs. 2. Parametric PSFs for standard photometry/astrometry software packages The student will investigate the coupling of reconstructed PSFs (from AO telemetry) and its parametric by-products and data analysis standard software for real/simulated observations. 3. PSF reconstruction from multi-Wavefront Sensor telemetry The student will develop and integrate efficient methods starting from telemetry to provide the reconstructed AO across the field for a few cases of AO correction systems. The candidate will be dedicated to the facilitation of the H2020-WP10 PSFR network by spending time with the ELT 1st light consortia to collect science requirements and turn them into meaningful PSF metrics that can be crunched by PSF reconstruction algorithm developers within the consortium. PROFILE Excellent candidates with astronomy, applied physics, mathematics, engineering backgrounds with strong signal processing and programming skills are encouraged to apply. NOTES The student will likely spend ~20% of his/her time in partner institutions as is the Lab Astrophysics Marseille, CENTRA in Lisbon, Durham University, JKU in Linz and others.