GUIV2026-059

Our group carries out its research activity in the field of experimental Particle Physics within the ATLAS experiment at the CERN LHC, covering in an integrated manner detector operation, its upgrade for the High-Luminosity phase (HL-LHC), and the scientific exploitation of the data. Our work includes key contributions to tracking, inner detector alignment and detector performance studies, as well as to data acquisition systems, trigger, and associated electronics. The group leads and actively participates in precision analyses of the Standard Model and in searches for new physics, with a particular emphasis on Higgs boson physics, top quark physics, the study of their couplings, and searches for long-lived particles. In addition, it maintains a strategic contribution to ATLAS distributed computing, including the development and operation of Tier-2 and Tier-3 infrastructures, and the use of advanced data analysis and machine learning techniques. The expertise acquired extends to the transfer of technologies and methodologies to applications aimed at addressing challenges of social relevance.

https://atlas.ific.uv.es/

• Explotar el potencial científico de los datos del LHC y el futuro HL-LHC mediante análisis de precisión del Modelo Estándar y búsquedas de nueva física con el detector ATLAS.
• Liderar y contribuir al desarrollo, operación y optimización del detector de trazas de ATLAS, incluyendo desarrollo y mejora de algoritmos de tracking y alineamiento y estudios de rendimiento en condiciones de alta luminosidad.
• Participar en la actualización del detector ATLAS para la fase del HL-LHC, con especial énfasis en el detector de trazas de microbandas de silicio ITk y en la electrónica de lectura.
• Desarrollar y liderar búsquedas de nueva física con firmas no convencionales, en particular partículas de vida larga, incluyendo el diseño de nuevas estrategias de reconstrucción y trigger.
• Contribuir de forma estratégica al computing distribuido de ATLAS, garantizando la explotación eficiente de grandes volúmenes de datos mediante infraestructuras Tier-2 y Tier-3.
• Aplicar técnicas avanzadas de análisis de datos y machine learning tanto a la física fundamental como a problemas tecnológicos y sociales, promoviendo la transferencia de conocimiento.

• Higgs boson and top quark physics.The group carries out precision analyses in the Higgs and top quark sectors, which are fundamental for characterizing the mechanism of mass generation and for exploring possible deviations from the Standard Model. These include measurements of cross sections and differential distributions, studies of couplings (including the top¿Higgs Yukawa coupling), and interpretations within effective field theories (EFT). These activities make use of advanced event selection techniques and machine learning to maximize sensitivity to new physics effects.
• Searches for new physics and leadership in long-lived particles.One of the group¿s strategic research lines is leadership in searches for phenomena beyond the Standard Model with unconventional experimental signatures. In particular, the group leads searches for long-lived particles, which require dedicated developments in trigger, reconstruction, and analysis, including displaced vertices, displaced jets, and out-of-time signals. These searches probe hidden sector scenarios, supersymmetry, exotic particles, and dark matter models, and are especially relevant in the context of the HL-LHC.
• Tracking, alignment and detector performance.The group has strong expertise in the tracking system and alignment of the ATLAS inner detector, ranging from the development and improvement of detector alignment algorithms and the control of systematic effects to studies of the impact of tracking on the reconstruction of physics objects. This line of work is key to maintaining detector performance under high-occupancy and high pile-up conditions, and to ensuring the quality of the data used in physics analyses.
• ATLAS detector upgrade for the HL-LHC.The group is actively involved in the upgrade of the ATLAS detector for the HL-LHC phase, with significant contributions to the new inner tracking detector (ITk) and to the readout electronics. The activities include the design, production, integration, quality assurance and validation of modules, as well as firmware developments and reconstruction algorithms adapted to the new experimental conditions.
• Distributed computing, software and machine learning.The group maintains a strategic contribution to ATLAS distributed computing, participating in the operation and evolution of Tier-2 and Tier-3 infrastructures and in the development of advanced data management and access models. In parallel, it develops and applies machine learning and deep learning techniques for physics analyses, simulation, reconstruction, and the reduction of computational costs, including the use of HPC resources and hardware accelerators.
• Technology transfer and applications to societal challenges.The group¿s expertise in advanced instrumentation, data acquisition, and large-scale analysis is transferred to applications beyond particle physics. Notable examples include the development of instrumentation for medical physics, as well as the application of machine learning techniques to socially relevant problems, such as monitoring critical infrastructures or studying natural phenomena with technological impact.

• Atomic, Molecular and Nuclear Physics