The CIEMAT particle physics group (CIEMAT-FP) has been awarded with the María de Maeztu Unit of Excellence accreditation that distinguishes the best research groups that stand out for the relevance and impact of their research outcomes at an international level, significantly contributing to expand the frontiers of knowledge and to the leadership of Spanish science.

Our group belongs to the Basic Research Department at CIEMAT, and is composed by the Particle Physics Division, the Astroparticle Physics Division and the Scientific Computing Unit.

CIEMAT-FP participates in large international experiments at the forefront of knowledge and technology in Particle and Astroparticle Physics, Cosmology, detector R&D and Scientific Computing. These are the current research lines:

  • Hadron Collider Physics at the Energy Frontier with the CMS experiment at LHC (CERN).
  • Neutrino oscillation physics in the Double Chooz (France), WA105 (CERN) and DUNE (Fermilab) experiments.
  • Direct search for dark matter with the ArDM experiment at the Canfranc underground laboratory and DarkSide at LNGS.
  • Cosmic-ray physics with the AMS experiment at the International Space Station.
  • Very-high energy gamma-ray astronomy with the Cerenkov Telescope Array (CTA) at Observatorio del Roque de los Muchachos (ORM).
  • Dark energy studies with DES at Cerro Tololo and PAU at ORM building extensive galaxy surveys. 
  • Galaxy evolution: its relation with molecular cloud and star formation and the role of high energy processes in the context of the Starbursts (Estallidos) project.
  • Detector R&D: development and tests of muon detectors and highly segmented calorimeters for LHC upgrade and future particle colliders (CMS & CALICE).
  • Data-intensive high throughput computing at the Worldwide LHC Computing Grid (WLCG). Development of advanced computing techniques, integration and utilization of distributed and highly parallel computing technologies, providing the infrastructure and support for the processing and analysis of large and complex datasets.