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Beam-based impedance measurement of HL-LHC low-impedance collimators
No full textThe objective of the High Luminosity Large Hadron Collider (HL-LHC) upgrade is to attain an instantaneous luminosity that is 5 times greater than the design value of the LHC. This requires nearly 2 times higher beam intensity compared to the operational LHC value during Run 2 (2015–2018). Higher bunch intensity makes the beam more prone to coherent instabilities. To keep beam stability under control and preserve beam quality, it is therefore necessary to reduce the machine beam coupling impedance. The collimation system of the LHC is presently responsible for a significant portion of the total machine impedance budget. In this context, during the LHC long-shutdown 2 (LS2), the LHC machine has been upgraded with newly engineered low-impedance collimators whose absorbing jaws are made of molybdenum-graphite (MoGr) compared to the previously used carbon fiber composite (CFC). Secondary collimators are also coated with molybdenum (Mo) to further boost conductivity. In order to validate the benefits of the impedance reduction targeted at the collimators and to identify possible nonconformities, we performed a series of tune shift measurements on the newly installed primary and secondary collimators with LHC beams and quantified the agreement with predictions. As expected, the results show a significant reduction in the collimators’ impedance contribution. Additionally, the remaining discrepancy between measurements and predictions is investigated with 3D numerical simulations by using the Wakefield Solver of Computer Simulation Technology
A Generalisable Generative Model for Multi-Detector Calorimeter Simulation
No full textCollider experiments, such as those at the Large Hadron Collider, use the Geant4 toolkit to simulate particle-detector interactions with high accuracy. However, these experiments increasingly require larger amounts of simulated data, leading to huge computing cost. Generative machine learning methods could offer much faster calorimeter shower simulations by directly emulating detector responses. In this work, we present CaloDiT-2, a diffusion model which uses transformer blocks. As is the case for other models explored for this task, it can be applied to specific geometries, however its true strength lies in its generalisation capabilities. Our approach allows pre-training on multiple detectors and rapid adaptation to new ones, which we demonstrate on the LEMURS dataset. It reduces the effort required to develop accurate models for novel detectors or detectors which are under development and have geometries that are changed frequently, requiring up to 25x less data and 20x less training time. To the best of our knowledge, this is the first pre-trained model to be published that allows adaptation in the context of particle shower simulations, with the model also included in the Geant4 toolkit. We also present results on benchmarks on Dataset-2 from the community-hosted CaloChallenge, showing that our models provide one of the best tradeoffs between accuracy and speed from the published models. Our contributions include a mechanism for the creation of detector-agnostic data representations, architectural modifications suitable for the data modality, a pre-training and adaptation strategy, and publicly released datasets and pre-trained models for broad use
Combined Higgs boson measurements and their interpretations with the ATLAS experiment
No full textPrecision measurements of Higgs boson couplings and kinematic properties can be performed using the data collected by the ATLAS experiment, leveraging a variety of final states and production modes to probe different regions of phase space with increasing accuracy. By combining these measurements, the strengths of individual channels are maximally exploited, providing the most stringent global constraints on Higgs boson properties. This talk presents the latest combination of Higgs boson measurements by the ATLAS experiment, with results reported in terms of production modes, branching fractions, Simplified Template Cross Sections, and coupling modifiers. The results are based on proton-proton collision data collected at =13 TeV during Run 2 of the LHC
The upgrade of the ATLAS Trigger and Data Acquisition system for the High Luminosity LHC
No full textThe ATLAS experiment at CERN is currently carrying out a major upgrade programme for the High-Luminosity LHC era, to be installed following the end of the current Run-3 in 2026. In order to deliver an order of magnitude more data than previous LHC runs, 14 TeV protons will collide with an instantaneous luminosity of up to , resulting in much higher pileup and data rates than the current experiment was designed to handle. While this is essential to realise the physics programme, it presents a huge challenge for the detector, trigger, data acquisition and computing. The detector upgrades themselves also present new requirements and opportunities for the trigger and data acquisition system. We will discuss the motivation for the upgrade, the architecture of the trigger and data acquisition system for Run-4, and recent progress on the design, technology and construction of the system
Optimizing Antihydrogen Production via Slow Plasma Merging
No full textWe measure the time-dependent temperature and density distribution of antiprotons and positrons while slowly combining them to make antihydrogen atoms in a nested Penning-Malmberg trap. The total antihydrogen yield and the number of atoms escaping the trap as a beam are greatest when the positron temperature is lowest and when antiprotons enter the positron plasma at the smallest radius. We control these parameters by changing the rate at which we lower the electrostatic barrier between the antiproton and positron plasmas and by heating the positrons. With the optimal settings, we produce antihydrogen atoms per -minute run, surpassing the previous state of the art--- atoms in minutes---by a factor of .We measure the time-dependent temperature and density distribution of antiprotons and positrons while slowly combining them to make antihydrogen atoms in a nested Penning-Malmberg trap. The total antihydrogen yield and the number of atoms escaping the trap as a beam are greatest when the positron temperature is lowest and when antiprotons enter the positron plasma at the smallest radius. We control these parameters by changing the rate at which we lower the electrostatic barrier between the antiproton and positron plasmas and by heating the positrons. With the optimal settings, we produce antihydrogen atoms per -minute run, surpassing the previous state of the art -- atoms in minutes -- by a factor of
Measurement of the SEU rate and demonstration of automated recovery for Kintex-7 FPGA on TGC readout boards in the ATLAS Experiment at HL-LHC
No full textReliable operation of electronics in the high-radiation environment of the ATLAS cavern is essential for long-term physics data collection through the HL-LHC period. In particular, FPGAs (AMD Kintex-7 FPGAs) on Thin Gap Chamber (TGC) readout boards (PS boards) are susceptible to Single Event Upsets (SEUs). To address this challenge, a robust recovery system was developed to detect and automatically correct soft errors. We present in-situ measurements of the SEU rate and recovery demonstration for the Kintex-7 FPGA, performed in the actual ATLAS cavern during Run 3. These results provide a direct validation of the radiation tolerance and recovery mechanisms required for the operation at HL-LHC and an insight for future high-energy physics experiments. In 2024, we placed the PS board at around from the beam axis at with the board surface parallel to the beam axis, and conducted the measurement and demonstration during pp collisions at . For the data taking of an integrated luminosity of , we observed 133 single-bit and 5 multi-bit errors in the configuration memory of the Kintex-7 FPGA. In 2025, we placed the PS board at around from the beam axis at with the board surface perpendicular to the beam axis, as planned for HL-LHC. We observed 86 single-bit, 7 multi-bit, and 5 unrecoverable bit errors for an integrated luminosity of . All single-bit and multi-bit errors were automatically corrected by the Soft Error Mitigation (SEM) controller implemented in the Kintex-7 FPGA. The errors unrecoverable by the SEM controller were recovered via FPGA reconfiguration in an automatic manner under control of a dedicated external board
A Novel Low Sidelobe Phased Array Synthesis Technique Using Uniform Transmit and Thinned Receive Array
No full textThe radar systems specify the peak sidelobe levels (SLLs) of the two-way antenna array pattern, which is the product of the patterns of the transmit and receive antenna arrays. The presence of high sidelobes near the main beam of the two-way array pattern can cause interference and ground clutter of the radar system, thereby degrading overall performance. This paper presents a novel technique for synthesizing a two-way phased array antenna pattern that utilizes a uniform transmit and a thinned receive array. Specifically, we propose a centerdominant sparse edge receive array architecture, where all elements in the central region remain continuously active, while only a few elements are activated at both edges of the array to achieve thinning. The proposed antenna array has a peak SLL of , representing a improvement at the cost of a reduction in directivity compared to conventional arrays, where the peak SLL achieved is . Furthermore, the proposed array shows an improvement of and in SLL and directivity, respectively, compared to the state-of-the-art solutions