BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Instituto de Astrofísica de Andalucía - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.iaa.csic.es
X-WR-CALDESC:Eventos para Instituto de Astrofísica de Andalucía
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20251026T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20241202T093000
DTEND;TZID=Europe/Paris:20241202T133000
DTSTAMP:20260404T120814
CREATED:20241121T160454Z
LAST-MODIFIED:20250912T080541Z
UID:22484-1733131800-1733146200@www.iaa.csic.es
SUMMARY:PySnack 9: GASTLI
DESCRIPTION:PySnacks\nWithin the  Severo Ochoa Training Initiative of the IAA-CSIC we are offering short introductory practical courses about Python packages for astrophysical applications (PySnacks). We invite you to participate in the 4h course PySnack 9: GASTLI \nAbstract\nUnderstanding the interior composition of exoplanets is key to uncovering their formation and evolutionary histories\, especially their metal content. By comparing observed mass and radius measurements with interior structure and evolution models\, we can infer a planet’s metal mass fraction. With the advent of JWST\, CHEOPS\, TESS\, and the upcoming PLATO\, we are entering an era of unprecedented precision in exoplanet radius\, age\, and atmospheric metallicity measurements. \nTo harness this growing wealth of data\, we introduce GASTLI (GAS gianT modeL for Interiors) — a user-friendly\, open-source Python package designed to make interior modeling accessible. GASTLI is optimized for rapid computation of mass-radius and radius-luminosity-age relationships and enables interior composition retrievals to fit models to observed mass\, radius\, age\, and\, when available\, atmospheric metallicity. \nSupporting a diverse range of planetary compositions\, masses\, and irradiation conditions\, GASTLI is ideal for modeling planets from warm sub-Neptunes to hot gas giants. It incorporates state-of-the-art thermodynamic data and equations of state for rock\, water\, and hydrogen/helium\, alongside a customizable atmospheric grid feature\, ensuring accurate representation of high-pressure planetary envelopes. \nThis course will be taught by Lorena Acuña (MPIA-Heidelberg). \n 
URL:https://www.iaa.csic.es/evento/pysnacks-8-pybdsf-2/
LOCATION:IAA – CSIC\, Glorieta de la Astronomía\, Granada\, España
CATEGORIES:SO Training
ATTACH;FMTTYPE=image/png:https://www.iaa.csic.es/wp-content/uploads/2024/11/gastly.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20241212T103000
DTEND;TZID=Europe/Paris:20241212T163000
DTSTAMP:20260404T120814
CREATED:20241219T114506Z
LAST-MODIFIED:20250912T080537Z
UID:22536-1733999400-1734021000@www.iaa.csic.es
SUMMARY:PySnack 10: PROSE
DESCRIPTION:PySnacks\nWithin the  Severo Ochoa Training Initiative of the IAA-CSIC we are offering short introductory practical courses about Python packages for astrophysical applications (PySnacks). We invite you to participate in the 4h course PySnack 10: PROSE \nAbstract\nApproximately 75% of known exoplanets have been discovered by identifying transit signals in the light curves of their host stars. These discoveries start with the acquisition of raw images of the sky\, followed by the extraction of stellar time-series photometry. In this workshop\, we will process ground-based observations of the star TRAPPIST-1 to replicate the detection of its first exoplanet transit using original data from the TRAPPIST telescope. Participants will learn to calibrate raw images and extract TRAPPIST-1’s light curve using prose\, a Python package designed for modular image processing in astronomy. Finally\, we will apply nuance\, a detection algorithm tailored for identifying transits in noisy datasets. \nOverall\, participants will gain hands-on experience in image calibration\, light curve extraction\, and transit detection\, along with practical skills in using Python tools for astronomical data analysis.
URL:https://www.iaa.csic.es/evento/pysnack-10-prose/
LOCATION:IAA – CSIC\, Glorieta de la Astronomía\, Granada\, España
CATEGORIES:SO Training
ATTACH;FMTTYPE=image/png:https://www.iaa.csic.es/wp-content/uploads/2024/12/prosetransparent.png
END:VEVENT
END:VCALENDAR