MADCUBA

MADCUBA logo

Project webpage: https://cab.inta-csic.es/madcuba/

  • CAB contribution to SPICA, development of cryogenic instrumentation and multi-wavelength scientific exploitation, reference number PID2019-105552RB-C41, PI: Francisco Najarro de la Parra and Izaskun Jiménez Serra, funded by MIC
  • COOL (Cosmic Origins of Life; 2019-T1/TIC-15379), PI: Víctor M. Rivilla, funded by the Talent Attraction program for experienced PhDs of the Community of Madrid.
  • Spanish contribution to the Cryogenic Space Missions Spica and Athena, Herschel Postoperations and Multifrequency Scientific Exploitation, Project No.: ESP2017-86582-C4-1-R, PI: Francisco Najarro and Giovanni Miniutti, funded by MINECO.
  • Spanish contribution to mid- and far-infrared space missions: Participation in SPICA, Herschel post-operations and multi-frequency science exploitation, Project No.: ESP2013-47809-C3-1-R, PI: Francisco Najarro and Jesus Martin-Pintado, funded by MINECO.

Madrid Data CUB Analysis (MADCUBA) is an open software package developed in the Center of Astrobiology of Madrid (CSIC-INTA) to analyze astronomical datacubes and single spectra of molecular and recombination line emission obtained with the main astronomical facilities (ALMA, Herschel, VLA, NOEMA, IRAM 30m, APEX, GBT, Effelsberg…) The current telescopes, and in particular ALMA, generate extremely large datacubes (spatial, spectral and polarization). To derive the physical conditions of the molecular gas, its chemical complexity and the kinematics from the data cubes, we need a powerful analysis tools able to easily extract and efficiently analyze the information contained in them. MADCUBA has been designed to combine an user friendly interface and a powerful data analysis system for non-experts on molecular astrophyscis. It is able to deal with large datacubes and provide the tools needed to properly reduced and analize the molecular and recombination line data.

MADCUBA
Example of MADCUBA visualization of astronomical datacubes and molecular spectra.

External team

Sergio Martín (ESO)

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