E. Rodrigues
A5023708186- Particle physics theoretical and experimental studies
- Quantum Chromodynamics and Particle Interactions
- High-Energy Particle Collisions Research
- Neutrino Physics Research
- Particle Detector Development and Performance
- Black Holes and Theoretical Physics
- Dark Matter and Cosmic Phenomena
- Computational Physics and Python Applications
- Particle Accelerators and Free-Electron Lasers
- Medical Imaging Techniques and Applications
- Atomic and Subatomic Physics Research
- Superconducting Materials and Applications
- Cosmology and Gravitation Theories
- Distributed and Parallel Computing Systems
- Nuclear physics research studies
- Radiation Detection and Scintillator Technologies
- Pulsars and Gravitational Waves Research
- Stochastic processes and statistical mechanics
- Advanced Data Storage Technologies
- Scientific Computing and Data Management
- Business and Management Studies
- International Science and Diplomacy
- Astrophysical Phenomena and Observations
- CCD and CMOS Imaging Sensors
- Academic Research in Diverse Fields
University of Liverpool
2020-2025
European Organization for Nuclear Research
2015-2024
École Polytechnique Fédérale de Lausanne
2017-2024
Istituto Nazionale di Fisica Nucleare, Sezione di Bologna
2023-2024
Universidade Federal do Rio de Janeiro
2011-2024
Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento
2023
Fulcrum Therapeutics (United States)
2023
University of Zurich
2013-2023
University of Bologna
2023
Centro Hospitalar de Entre o Douro e Vouga E.P.E.
2023
The Vertex Locator (VELO) is a silicon microstrip detector that surrounds the proton-proton interaction region in LHCb experiment. performance of during first years its physics operation reviewed. system operated vacuum, uses bi-phase CO2 cooling system, and sensors are moved to 7 mm from LHC beam for data taking. stability these characteristic features described, details material budget given. calibration timing processing algorithms implemented FPGAs described. fully characterised. have...
Machine learning is an important applied research area in particle physics, beginning with applications to high-level physics analysis the 1990s and 2000s, followed by explosion of event identification reconstruction 2010s. In this document we discuss promising future development areas machine a roadmap for their implementation, software hardware resource requirements, collaborative initiatives data science community, academia industry, training community science. The main objective connect...
Next-to-leading-order QCD analyses of the ZEUS data on deep inelastic scattering together with fixed-target have been performed, from which gluon and quark densities proton value strong coupling constant αs(MZ) were extracted. The study includes a full treatment experimental systematic uncertainties including point-to-point correlations. resulting in parton density functions are presented. A combined fit for yields agreement world average. derived alone indicate importance HERA determining...
Inclusive production of D*± (2010) mesons in deep inelastic scattering has been measured with the ZEUS detector at DESY HERA using an integrated luminosity 81.9 pb−1. The decay channel D*+→D0π+ D0→K−π+ and corresponding antiparticle were used to identify D* mesons. Differential cross sections 1.5<Q2<1000GeV2 0.02<y<0.7 kinematic region 1.5<pT(D*)<15GeV |η(D*)|<1.5 are compared different QCD calculations incorporating parametrizations parton densities proton. data show sensitivity gluon...
Machine Learning algorithms have played an important role in hadronic jet classification problems. The large variety of models applied to Large Hadron Collider data has demonstrated that there is still room for improvement. In this context Quantum a new and almost unexplored methodology, where the intrinsic properties quantum computation could be used exploit particles correlations improving performance. paper, we present brand approach identify if contains hadron formed by $b$ or $\bar{b}$...
Fine-tuning large language models (LLMs) to align with user preferences is challenging due the high cost of quality human annotations in Reinforcement Learning from Human Feedback (RLHF) and generalizability limitations AI Feedback. To address these challenges, we propose RLTHF, a human-AI hybrid framework that combines LLM-based initial alignment selective achieve full-human annotation minimal effort. RLTHF identifies hard-to-annotate samples mislabeled by LLMs using reward model's...
Inclusive jet differential cross sections have been measured in neutral current deep inelastic e+p scattering for boson virtualities Q2>125 GeV2. The data were taken using the ZEUS detector at HERA and correspond to an integrated luminosity of 38.6 pb−1. Jets identified Breit frame longitudinally invariant kT cluster algorithm. Measurements inclusive are presented as functions transverse energy (EBT,jet), pseudorapidity Q2, jets with EBT,jet>8 GeV. Next-to-leading-order QCD calculations...
A search for single-top production, ep --> etX, has been made with the ZEUS detector at HERA using an integrated luminosity of 130.1 pb-1. Events from both leptonic and hadronic decay channels W boson resulting top quark were sought. For mode, was events isolated high-energy leptons significant missing transverse momentum. three-jet in which two jets had invariant mass consistent that selected. No evidence production found. The results are used to constrain via flavour-changing neutral...
Scikit-HEP is a community-driven and community-oriented project with the goal of providing an ecosystem for particle physics data analysis in Python. toolset approximately twenty packages few “affiliated” packages. It expands typical Python tools physicists. Each package focuses on particular topic, interacts other toolset, where appropriate. Most are easy to install many environments; much work has been done this year provide binary “wheels” PyPI conda-forge The gaining interest momentum,...
Some of the biggest achievements modern era particle physics, such as discovery Higgs boson, have been made possible by tremendous effort in building and operating large-scale experiments like Large Hadron Collider or Tevatron. In these facilities, ultimate theory to describe matter at most fundamental level is constantly probed verified. These often produce large amounts data that require storing, processing, analysis techniques push limits traditional information processing schemes. Thus,...
Six of the key physics measurements that will be made by LHCb experiment, concerning CP asymmetries and rare B decays, are discussed in detail. The "road map" towards precision is presented, including use control channels other techniques to understand performance detector with first data from LHC.
Machine learning has been applied to several problems in particle physics research, beginning with applications high-level analysis the 1990s and 2000s, followed by an explosion of event identification reconstruction 2010s. In this document we discuss promising future research development areas for machine physics. We detail a roadmap their implementation, software hardware resource requirements, collaborative initiatives data science community, academia industry, training community science....