The Galaxy Activity, Torus, and Outflow Survey (GATOS)

XII. Unveiling physical processes in local active galaxies. Unsupervised hierarchical clustering of JWST MIRI/MRS observations

¹ Centro de Astrobiología (CAB) CSIC-INTA, Camino Bajo del Castillo s/n, 28692 Villanueva de la Cañada, Madrid, Spain
² Universidad Internacional de la Rioja (UNIR), Av. de la Paz 137, 26006 Logroño, La Rioja, Spain
³ Instituto de Radioastrononomía y Astrofísica (IRyA), Universidad Nacional Autónoma de México, Antigua Carretera a Pátzcuaro 8701 Ex-Hda. San José de la Huerta, Morelia, Michoacán, 58089, Mexico
⁴ Instituto de Física Fundamental, CSIC, Calle Serrano 123, 28006 Madrid, Spain
⁵ Kavli Institute for Particle Astrophysics & Cosmology (KIPAC), Stanford University, Stanford, CA 94305, USA
⁶ Instituto de Astrofísica de Canarias, C/ Vía Láctea s/n, 38205 La Laguna, Tenerife, Spain
⁷ Departamento de Astrofísica, Universidad de La Laguna, 38205 La Laguna, Tenerife, Spain
⁸ Observatorio Astronómico Nacional (OAN-IGN) – Observatorio de Madrid, Alfonso XII, 3, 28014 Madrid, Spain
⁹ Department of Physics and Astronomy, The University of Texas at San Antonio, 1 UTSA Circle, San Antonio, Texas 78249, USA
¹⁰ Departmento de Física de la Tierra y Astrofísica, Fac. de CC Físicas, Universidad Complutense de Madrid, E-28040 Madrid, Spain
¹¹ Instituto de Física de Partículas y del Cosmos IPARCOS, Fac. de CC Físicas, Universidad Complutense de Madrid, E-28040 Madrid, Spain
¹² Observatoire de Paris, LUX, PSL University, Sorbonne Université, CNRS, F-75014 Paris, France
¹³ Collège de France, 11 Place Marcelin Berthelot, 75231 Paris, France
¹⁴ Institute of Astrophysics, Foundation for Research and Technology – Hellas (FORTH), Heraklion 70013, Greece
¹⁵ School of Sciences, European University Cyprus, Diogenes Street, Engomi 1516, Nicosia, Cyprus
¹⁶ European Space Agency, c/o Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
¹⁷ Department of Physics and Astronomy, University of Alaska Anchorage, Anchorage, AK 99508-4664, USA
¹⁸ Department of Physics, University of Alaska, Fairbanks, Alaska 99775-5920, USA
¹⁹ Telespazio UK for the European Space Agency (ESA), ESAC, Camino Bajo del Castillo s/n, 28692 Villanueva de la Cañada, Spain
²⁰ Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
²¹ 1142 Sunset Point Rd, Clearwater, Florida 33755, USA
²² Departamento de Física, CCNE, Universidade Federal de Santa Maria, Av. Roraima 1000, 97105-900 Santa Maria, RS, Brazil
²³ Centro de Astrobiología (CAB) CSIC-INTA, Ctra. de Ajalvir km 4 Torrejón de Ardóz, 28850, Madrid, Spain
²⁴ Department of Physics, University of Oxford, Keble Road, Oxford OX1 3RH, UK

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 12 September 2025
Accepted: 26 February 2026

Abstract

Context. With the rise of integral field spectroscopy (IFS), we are currently dealing with large amounts of spatially resolved data, whose analysis has become challenging, especially when observing complex objects such as nearby galaxies.

Aims. We aim to develop a method of automatically separating regions with different physical properties (ionisation, kinematics, etc.) within the central parts (1″ ∼ 160 pc, on average) of galaxies. This could allow us to better understand the systems and provide an initial characterisation of the main ionisation sources affecting its evolution.

Methods. We developed an unsupervised hierarchical clustering algorithm to analyse data cubes based on spectral similarity. It clusters spaxels together with similar spectra, which is useful to disentangle regions affected by different processes, such as ionisation sources. We applied this method to a sample of 15 nearby (distances < 100 Mpc) galaxies: 7 from the Galaxy Activity, Torus, and Outflow Survey (GATOS) and 8 archival sources, all observed with the medium-resolution spectrometer (MRS) of the Mid-Infrared Instrument (MIRI) on board the James Webb Space Telescope (JWST). The sample spans sources of various morphologies, active galactic nucleus (AGN) types, and/or starbursts. From the clusters, we computed their median spectrum and measured the line and continuum properties. We used these measurements to train random forest models and create several empirical mid-IR diagnostic diagrams for the MRS channel 3 wavelength range, ranging from 11.5 to 18 μm, which includes among others the bright [Ne II], [Ne III], and [Ne V] lines, several H₂ transitions, and PAH features.

Results. The clustering technique allows one to differentiate emission coming from an AGN, a nuclear starburst, the disc and star-forming (SF) regions in the galaxies, and other composite regions, potentially ionised by several sources simultaneously. This is supported by the results from the empirical diagnostic diagrams, which are indeed able to separate physically distinct regions. This innovative method serves as a tool to identify regions of interest in any data cube prior to an in-depth analysis of the sources. In a future work, we shall explore other wavelength ranges and a larger sample that would help us to obtain statistically significant conclusions.