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Two-Loop Anomalous Dimensions in the LEFT: Dimension-Six Four-Fermion Operators in NDR
No full textWe derive the complete set of two-loop anomalous dimensions describing the mixing of four-fermion operators in the Low Energy Effective Field Theory (LEFT). The calculation is performed in Naive Dimensional Regularization with anticommuting (the NDR scheme), and the results are given in the "JMS basis" of dimension-six operators. The derivation relies on known results for UV poles in two-loop diagrams in QCD, which are then used to derive the two-loop Anomalous Dimension Matrix (ADM) for the full set of four-fermion operators including , and corrections. The method employed is an extension of a common approach to deal with traces containing in NDR. Our results have been implemented in the public code DsixTools. We also discuss and provide the results in the LEFT with 5, 4 and 3 active quark flavors
Extension of the Discrete Electron Transport Capabilities of the Geant4-DNA Toolkit to MeV Energies
No full textThe discrete physics models available in the Geant4-DNA Monte Carlo toolkit are a subject of continuous evolution and improvement in order to meet the needs of state-of-the-art radiobiological research for medical and space applications. The current capabilities of Geant4-DNA for event-by-event electron transport extend up to 1 MeV. In this work, Geant4-DNA’s most accurate electron inelastic model for sub-keV energies is improved and extended up to 10 MeV via the Relativistic Plane Wave Born Approximation and other theoretical considerations. Benchmark simulations of the electronic stopping power and range of electrons in liquid water using the new model show almost excellent agreement (at the few % level) with the recommendations of the International Commission on Radiation Units and Measurements (ICRU) up to 10 MeV, offering notable improvement (by a factor of ~2) over the default Geant4-DNA inelastic model and an order-of-magnitude higher electron limit. The present development will allow Geant4-DNA users to perform electron track-structure simulations up to 10 MeV, thus, covering a wider range of radiotherapeutic applications (including FLASH-RT) as well as space applications involving MeV electrons which are not currently reachable
xFitter Updates: Probing Z Boson Couplings with Forward-Backward Asymmetry
No full textWe present recent updates in the xFitter software framework for global fits of parton distribution functions in high-energy physics. Our focus is on investigating the sensitivity to boson couplings using the forward-backward asymmetry in Drell-Yan production. By utilizing an effective approach and simulated data, we assess the accuracy of these couplings, specifically considering the full LHC data sample. Furthermore, we compare our results with predictions for future colliders, providing insights into their potential impact on understanding boson interactions.We present recent updates in the xFitter software framework for global fits of parton distribution functions in high-energy physics. Our focus is on investigating the sensitivity to Z boson couplings using the forward-backward asymmetry in Drell-Yan production. By utilizing an effective approach and simulated data, we assess the accuracy of these couplings, specifically considering the full LHC data sample. Furthermore, we compare our results with predictions for future colliders, providing insights into their potential impact on understanding Z boson interactions
Timing characterization of MALTA and MALTA2 pixel detectors using Micro X-ray source
No full textThe MALTA monolithic active pixel detector is developed to address the challenges anticipated in future high-energy physics detectors. As part of its characterization, we conducted fast-timing studies necessary to provide a figure of merit for this family of monolithic pixel detectors. MALTA has a metal layer in front-end electronics, and the conventional laser technique is not suitable for fast timing studies due to the reflection of the laser from the metallic surface. X-rays have been employed as a more effective alternative for penetration through these layers. The triggered X-ray set-up is designed to study timing measurements of monolithic detectors. The timing response of the X-ray set-up is characterized using an LGAD. The timing response of the MALTA and MALTA2 pixel detectors is studied, and the best response time of MALTA2 pixel detectors is measured at about 2 ns
Short Summaries of the ATS Seminars in 2024
No full textFive ATS seminars took place in 2024 (https://indico.cern.ch/category/2725/). Short summaries were prepared after each seminar (except for the seminar which took place in June and which was devoted to the IPAC-2024 CERN oral contributions). Once approved by the ATS management, the short summaries were uploaded on the indico site. The purpose of this short note is to collect these four summaries in a unique document
Searches For Beyond The Standard Model Physics Using Challenging And Long-lived Signatures With The ATLAS Detector
No full textVarious theories beyond the Standard Model predict new, long-lived particles with unique signatures which are difficult to reconstruct and for which estimating the background rates is also a challenge. Signatures from displaced and/or delayed decays anywhere from the inner detector to the muon spectrometer, as well as those of new particles with fractional or multiple values of the charge of the electron or high mass stable charged particles are all examples of experimentally demanding signatures. The talk will focus on the most recent results using 13 TeV pp collision data collected by the ATLAS detecto
QDIPS: Deep Sets Network for FPGA investigated for high speed inference on ATLAS
No full textWe adapted DIPS (Deep Impact Parameter Sets), a deep sets neural network flavour tagging algorithm previously used in ATLAS offline low-level flavour tagging and online b-jet trigger preselections, for use on FPGA with the aim to assess its performance and resource costs. Deep sets network architec- tures have useful applications in finding correlations in unordered and variable length data input. Its use on FPGA would open up accelerated machine learning in areas where the input has no fixed length or order. We compare an aggres- sively downscaled for-FPGA DIPS algorithm performance to the CPU-based full precision performance, and explore the associated FPGA resource costs