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DTSTART;VALUE=DATE:20240930
DTEND;VALUE=DATE:20241005
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SUMMARY:ERIS 2024 Tenth European Radio Interferometry School
DESCRIPTION:The tenth edition of the European Radio Interferometry School\, ERIS2024\, will be held in Granada\, Spain\, from Monday September 30th to Friday October 4th\, 2024. ERIS will provide a week of lectures and tutorials on how to achieve scientific results from radio interferometry. The school is co-organised by the Instituto de Astrofísica de Andalucía (IAA-CSIC) and JIVE – Joint Institute for VLBI ERIC. This school is sponsored by the OPTICON-RadioNET Pilot project and the Severo Ochoa training program of the IAA-CSIC. \nThe topics covered by the lectures/tutorials will include: \n\n   Calibration and imaging of continuum\, spectral line and polarization data\n   Low frequency (LOFAR domain)\, cm-wave (e-MERLIN domain)\, decimetre-wave (HI/OH domain)\, high frequency (ALMA/IRAM domain)\, and VLBI interferometry\n   Extracting the information from astronomical data and interpreting the results\n   Choosing the most suitable array and observing plan for your project.
URL:https://www.iaa.csic.es/evento/eris-2024-tenth-european-radio-interferometry-school/
LOCATION:IAA – CSIC\, Glorieta de la Astronomía\, Granada\, España
CATEGORIES:SO Training
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DTSTART;TZID=Europe/Paris:20241031T103000
DTEND;TZID=Europe/Paris:20241031T233000
DTSTAMP:20260405T172826
CREATED:20241118T175450Z
LAST-MODIFIED:20250912T080550Z
UID:22426-1730370600-1730417400@www.iaa.csic.es
SUMMARY:PySnacks 8: PyBDSF
DESCRIPTION:The Python Blob Detector and Source Finder (PyBDSF) is a CASA-based software designed for source detection in radio-interferometric images. Originally developed for the Low Frequency Array (LOFAR)\, PyBDSF is designed to work on a wide range of scales\, cataloguing different types of sources and allowing post-extraction filtering depending on the user’s scientific purposes. PyBDSF works on images produced by any radio-interferometer. In short\, PyBDSF loads the image in fits or CASA format\, computes some basic image statistics (rms and mean)\, and calculates a threshold to separate source from noise pixels with different algorithms that can be chosen by the user. Then\, the program identifies islands of emission which are fitted with one or multiple Gaussians. The resulting source catalogue\, which can be written into different formats (ascii\, fits\, txt\,…) for subsequent analysis\, provides key source properties such as astrometry\, integrated and peak fluxes\, source geometry\, etc. In addition\, internally derived images (rms noise maps\, Gaussian residual and models\, etc) are written in commonly used formats (fits or CASA) if specified by the user. It is possible to work with PyBDSF interactively in a terminal\, or via Python scripts or notebooks. PyBDSF can work with all Stokes parameters and compute the polarisation percentage and angle for each source. Also\, PyBDSF can compute the spectral indices of both extended and unresolved sources provided a frequency cube is input. Finally\, PyBDSF can estimate the PSF spatial variation across the image and correct it. This is of special interest for low frequency observations (such as those of LOFAR) which are more prominently affected by ionospheric effects.
URL:https://www.iaa.csic.es/evento/pysnacks-8-pybdsf/
LOCATION:IAA – CSIC\, Glorieta de la Astronomía\, Granada\, España
CATEGORIES:SO Training
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