Ricardo Perez Martinez

    Astronomer

     

    Main Research Fields

    • Galaxy evolution across cosmic times. Influence of the environment in galaxies (Galaxy Clusters, Groups and Voids).
    • Emission line galaxies.
    • Multiwavelenth studies, from X-rays to Far Infrared. SED fitting.
    • Advanced techniques of cross-matching catalogues.
    • Machine learning methods of galaxy classification.

    Keywords

    • Galaxy evolution.
    • Galaxy Clusters.
    • Star formation.
    • Machine Learning.

    Ongoing collaborations

    • Galaxy Cluster Evolution Survey (GLACE)

    An ESO/GTC large program observing clusters in the redshift range from 0.4 to 1.2 using the Tunable Filter mode of OSIRIS at GTC, together with data from infrared observatories like Herschel and Spitzer. Done in collaboration with IAC, IRAM, IFCA, CAB and IAA.

    • OSIRIS Tunable Emission Line Object Survey (OTELO)

    A pencil bean survey in an area of the extended GROTH field aiming to detect emission line galaxies and study their characteristics and evolution across the cosmic times. Done in collaboration with IAC, IRAM, IFCA, CAB and IAA.

    • Lockman SpReSO survey.

    A deep spectroscopic survey in the Lockman hole aiming to analyse the full spectra of galaxies in a wide range of redshifts. Done in collaboration with IA-UNAM, IAC, IRAM, IFCA, CAB and IAA.

    • Environment Driven Galaxy Evolution (EDGE)

    A study of low surface brightness sources in a sample of galaxy clusters in the 0.18 - 0.45 redshift range. The main goal of the project is to detect the influence of the environment in the star formation rate and/or AGN activity in their earliest stages. Done in collaboration with UCM, CEFCA and U. Valladolid.

    • Machine learning applied to cluster galaxy classification. (ML-GC)
    • A project to develop machine learning techniques to establish cluster memberships of galaxies using the Hubble Frontier Fields data and X-ray extended emission maps, mainly from XMM-Newton. Done in collaboration with CEFCA, U. Valladolid and IFCA.

    Publications

    Articles in ADS

    Organization of workshops and conferences:

    PhD supervision:

    • Star forming galaxies at z~0.8 and their infrared properties. PhD Candidate: R Navarro. Universidad Complutense de Madrid
    • Machine learning methodologies for cluster galaxy classification. PhD candidate: S. de Castro. Universidad Complutense de Madrid.

    MSci Thesis and Interships supervision (last three)  

    • Machine learning methods to detect satellite trails in infrared HST images. 2024. A. González. Universdad Politécnica de Madrid. Intership at ISDEFE. 
    • Machine Learning techniques applied to galaxy classification in overdense environments. 2024. G. Valé. MSci at Universidad Complutense de Madrid.
    • A study of the H$\alpha$ luminosity function and the star formation rate in the Abell 2390 cluster. 2022. B. Calleja. MSci at Universidad Complutense de Madrid.

    Other activities

    • Head of Astrophysics and Space Science, ISDEFE.
    • Member of the Space Science Faculty Board, ESA.

    Project/mission at ESA