We investigate the LHC phenomenology of a vector dark-sector effective theory containing two neutral massive vector states, both odd under a dark-parity symmetry. The lightest state is stable and provides a dark-matter candidate, while the leading interactions with the Standard Model arise from dimension-six operators involving the hypercharge field strength. In the prompt-decay regime considered in this work, the heavier state can decay radiatively, leading to a γ + jets + E_T^miss signature when the two dark vectors are produced in association with QCD radiation. We study this topology at the LHC through a cut-based analysis, comparing an inclusive missing-transverse-momentum selection with a three-bin strategy that retains coarse shape information. The binned analysis is found to substantially improve the expected reach and probes regions of the parameter space compatible with the observed relic abundance in the standard freeze-out scenario. We also discuss the freeze-in interpretation and the limitations associated with the effective field theory description at high masses.

Data from particle physics experiments are unique and are often the result of a very large investment of resources. Given the potential scientific impact of these data, which goes far beyond the immediate priorities of the experimental collaborations that obtain them, it is imperative that the collaborations and the wider particle physics community publish and preserve sufficient information to ensure that this impact can be realised, now and into the future. The information to be published and preserved includes the algorithms, statistical information, simulations and the recorded data. This publication and preservation requires significant resources, and should be a strategic priority with commensurate planning and resource allocation from the earliest stages of future facilities and experiments.

ATLAS is the largest experiment at the LHC accelerator complex in CERN. It is situated at one of the collision points in the accelerator tunnel. The experiment consists of a collection of specialized sub-detectors designed to characterize the particles generated by collisions in the LHC. One of these specialized detectors is the liquid argon (LAr) calorimeter, which contains approximately 187k sensor cells used to characterize electromagnetic showers. The LAr calorimeter has a high cell density, which, combined with the high collision rates and the mechanical and electronic structure of the detector readout, leads to crosstalk (XT) effects between adjacent sensor cells. Crosstalk degrades the accuracy of energy and time reconstruction for incoming particles. To address this challenge, an electromagnetic shower simulator based on the ATLAS LAr calorimeter was developed, along with a machine learning approach to mitigate the XT effects. The results demonstrate that the energy and time-of-flight of particles can be reconstructed very closely to the desired values. The proposed approach reduces the error fluctuations in energy estimation by at least 37 times compared to the standard algorithm. Additionally, it decreases the error fluctuations in time estimation by three orders of magnitude.

This chapter presents an AI-based approach to the systemic collection of user experience data for further analysis. This is an important task because user feedback is essential in many use cases, such as serious games, tourist and museum applications, food recognition applications, and other software based on Augmented Reality (AR). For AR game-based learning environments user feedback can be provided as Multimodal Learning Analytics (MMLA) which has been emerging in the past years as it exploits the fusion of sensors and data mining techniques. A wide range of sensors have been used by MMLA experiments, ranging from those collecting students' motoric (relating to muscular movement) and physiological (heart, brain, skin, etc.) behaviour, to those capturing social (proximity), situational, and environmental (location, noise) contexts in which learners are placed. Recent research achievements in this area have resulted in several techniques for gathering user experience data, including eye-movement tracking, mood tracking, facial expression recognition, etc. As a result of user's activity monitoring during AR-based software use, it is possible to obtain temporal multimodal data that requires rectifying, fusion, and analysis. These procedures can be based on Artificial Intelligence, Fuzzy logic, algebraic systems of aggregates, and other approaches. This chapter covers theoretical and practical aspects of handling AR user's experience data, in particular, MMLA data. The chapter gives an overview of sensors, tools, and techniques for MMLA data gathering as well as presenting several approaches and methods for user experience data processing and analysis.

Em física experimental de altas energias, e preciso lidar com um grande volume de informações, sendo grande parte delas proveniente do ruído de fundo que dificulta a caracterização dos fenômenos de interesse particular de um dado experimento. Deste modo, e necessário um complexo processo de seleção online de eventos (trigger). No ATLAS, maior experimento do LHC (Large Hadron Collider), o sistema de trigger opera em duas etapas de seleção sequenciais, denominadas primeiro e alto nível. No caso de elétrons, importantes como mensageiros da nova física que se deseja observar, o sistema de trigger se apoia fortemente no sistema de calorimetria, que mede a energia da partícula incidente. Neste trabalho, e proposto um método de calibração de energia baseado em um conjunto de arvores de decisão com reforço por gradiente (Gradient Boosted Decision Trees Ensemble – GBDTE) para melhorar a acuidade da estimativa da energia na etapa rápida do trigger de alto nível do experimento ATLAS. Com esse método proposto, e possível reduzir os requisitos computacionais e aumentar a eficiencia na seleção de partículas eletromagnéticas, como elétrons.

Calorimeters play an important role in high-energy physics experiments. Their design includes electronic instrumentation, signal processing chain, computing infrastructure, and also a good understanding of their response to particle showers produced by the interaction of incoming particles. This is usually supported by full simulation frameworks developed for specific experiments so that their access is restricted to the collaboration members only. Such restrictions limit the general-purpose developments that aim to propose innovative approaches to signal processing, which may include machine learning and advanced stochastic signal processing models. This work presents the Lorenzetti Showers, a general-purpose framework that mainly targets supporting novel signal reconstruction and triggering strategies using segmented calorimeter information. This framework fully incorporates developments down to the signal processing chain level (signal shaping, energy estimation, and noise mitigation techniques) to allow advanced signal processing approaches in modern calorimetry and triggering systems. The developed framework is flexible enough to be extended in different directions. For instance, it can become a tool for the phenomenology community to go beyond the usual detector design and physics process generation approaches. Program summary Program Title: Lorenzetti Showers CPC Library link to program files: https://doi .org /10 .17632 /sy64367452 .1 Developer's repository link: https://github .com /lorenzetti -hep /lorenzetti Licensing provisions: GPLv3 Programming language: Python, C++. Nature of problem: In experimental high-energy physics, simulation is essential for experiment preparation, design and interpretations of ongoing acquisitions. Especially for calorimeters, an accurate simulation that can describe detector geometry, behavior to different physics processes and signal generation close to the readout electronics and data acquisition levels is required to properly develop signal processing and computational methods. Such detectors may face very challenging demands arising from the new designs, such as pileup mitigation and noise reduction tasks under unprecedented levels. In this sense, simulation requirements continuously increase in complexity and performance, because new physics searches require large datasets and accurate modeling to experimental effects. Solution method: The Lorenzetti Showers is an integrated software framework that provides complete calorimeter information close enough to the electronic readout chain. Thus, the proposed framework allows users to access cell readout values, configurable sensor pulse-shapes, crosstalk modeling, and different energy estimation methods. It aims at supporting designs that target low or high pileup operation conditions in an easy-to-use modular structure. The developed framework is based on Pythia 8 (particle generation) and Geant4 (interactions with the calorimeter technique under analysis). An efficient data recording structure was used to allow full access to the Lorenzetti Showers outputs. In summary, the Lorenzetti Showers tool provides to the scientific community a user-friendly, flexible, user-oriented, and low-level calorimeter simulation framework. Additional comments including restrictions and unusual features: The framework current version provides the implementation of a generic segmented calorimeter (electromagnetic and hadronic sections), which may be modified by the user, if desired. It allows the generation of particles interactions using Pythia 8 (native) or any generator compatible with the HepMC format (which may be integrated using an external input file) and propagation through a user-configurable calorimeter using Geant4.(c) 2023 Elsevier B.V. All rights reserved.

A bstract A search for the exclusive decays of the Higgs and Z bosons to a ϕ or ρ meson and a photon is performed with a pp collision data sample corresponding to an integrated luminosity of up to 35 . 6 fb −1 collected at $$ \sqrt{s}=13 $$ s = 13 TeV with the ATLAS detector at the CERN Large Hadron Collider. These decays have been suggested as a probe of the Higgs boson couplings to light quarks. No significant excess of events is observed above the background, as expected from the Standard Model. Upper limits at 95% confidence level were obtained on the branching fractions of the Higgs boson decays to ϕ γ and ρ γ of 4 . 8 × 10 −4 and 8 . 8 × 10 −4 , respectively. The corresponding 95% confidence level upper limits for the Z boson decays are 0 . 9 × 10 −6 and 25 × 10 −6 for ϕ γ and ρ γ, respectively.

A search for leptoquarks decaying into the bτ final state is performed using Run 2 proton-proton collision data from the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb−1 at √(s) = 13 TeV recorded by the ATLAS detector. The benchmark models considered in this search are vector leptoquarks with electric charge of 2/3e and scalar leptoquarks with an electric charge of 4/3e. No significant excess above the Standard Model prediction is observed, and 95

The total and differential Higgs boson production cross-sections are measured through a combined statistical analysis of the H → ZZ* → 4ℓ and H → γγ decay channels. The results are based on a dataset of 139 fb−1 of proton–proton collisions at a centre-of-mass energy of 13 TeV, recorded by the ATLAS detector at the Large Hadron Collider. The measured total Higgs boson production cross-section is 55.5_-3.8^+4.0 pb, consistent with the Standard Model prediction of 55.6 ± 2.5 pb. All results from the two decay channels are compatible with each other, and their combination agrees with the Standard Model predictions. A combined statistical interpretation of the measured fiducial cross-sections as a function of the Higgs boson transverse momentum is performed in order to probe the Yukawa couplings to the bottom and charm quarks. A similar interpretation is performed by including also the constraints from the measurements of Higgs boson production in association with a W or Z boson in the H → bb and cc decay channels.

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The s=13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb−1. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV.

Particle physics experiments deal with a huge volume of information and a complex sequential processing chain for online selection (trigger) of events. In the ATLAS experiment at the Large Hadron Collider (LHC), the trigger system is responsible for choosing the events that will be recorded on permanent media for future analysis and operates sequentially in two levels of selection. The estimated value of energy deposited by particles in the detector is an important parameter for the online selection process. In this work, a calibration method based on gradient boosted decision trees ensemble is proposed to improve the quality of the energy estimated in the second trigger stage of the ATLAS detector. With the proposed method it is possible, at the same time, to reduce computational requirements and increase the selection efficiency of electromagnetic particles (electrons).

The first measurement of longitudinal decorrelations of harmonic flow amplitudes v_{n} for n=2-4 in Xe+Xe collisions at sqrt[s_{NN}]=5.44  TeV is obtained using 3  μb^{-1} of data with the ATLAS detector at the LHC. The decorrelation signal for v_{3} and v_{4} is found to be nearly independent of collision centrality and transverse momentum (p_{T}) requirements on final-state particles, but for v_{2} a strong centrality and p_{T} dependence is seen. When compared with the results from Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV, the longitudinal decorrelation signal in midcentral Xe+Xe collisions is found to be larger for v_{2}, but smaller for v_{3}. Current hydrodynamic models reproduce the ratios of the v_{n} measured in Xe+Xe collisions to those in Pb+Pb collisions but fail to describe the magnitudes and trends of the ratios of longitudinal flow decorrelations between Xe+Xe and Pb+Pb. The results on the system-size dependence provide new insights and an important lever arm to separate effects of the longitudinal structure of the initial state from other early and late time effects in heavy-ion collisions.

O ATLAS é o maior experimento do complexo do acelerador de partículas LHC no CERN. Está localizado em um dos pontos de colisão no túnel do acelerador e é composto de um conjunto de sub-detectores especializados para caracterizar as partículas produzidas nas colisões do LHC. Um desses detectores especializados é o calorímetro de Argônio Líquido (LAr), com cerca de 187k sensores para rastreamento e registro de chuveiros eletromagnéticos. O LAr tem uma granularidade fina e alta densidade de células que em associação com as altas taxas de colisão, estrutura mecânica e eletrônica e o sistema de leitura do detector produz efeitos de crosstalk (XT) entre células dificultando o processo de reconstrução da energia e do tempo de de voo da partícula incidente. Para tratar este desafio, foi um desenvolvido um simulador de chuveiro eletromagnético de partículas baseado no calorímetro LAr do ATLAS, junto com uma abordagem de aprendizagem de máquina para mitigar os efeitos do XT. Os resultados indicam que para altas energias a reconstrução se aproxima dos valores alvo e, por outro lado, em baixas energias é necessário um método especializado para tratar e normalizar os dados antes de aplicar uma rede neural para reconstruir os valores das energias.

Procrastination is a widespread self-regulatory failure. It consists in voluntarily delaying work despite expecting to be worse-off the day after. Procrastination impacts students’ performance and well-being. Therefore it is argued that universities could and should play a more active role in helping freshmen improve their time management. We designed an intervention to scaffold regular work for large university classes in a platform-independent, easily scalable, and transferable manner. Our intervention consisted in sending a weekly e-mail reminding to complete chapter quizzes. These quizzes were closing shortly after the end of the chapter. The content of the reminder e-mails varied across our five experimental groups to additionally include different types of personalised advice. We performed the intervention during one month on 1130 freshmen of a blended university course. We study whether regularly sending e-mails improves work regularity and final performance. We also study the impact the e-mail content on work regularity and performance. As a result, we show that simple e-mail reminders were able to improve regularity in filling quizzes, the total number of quizzes filled, and the progress in overall performance. We also show that e-mail content matters and that complex personalised advice was counter-productive in our intervention.

This paper presents a search for direct top squark pair production in events with missing transverse momentum plus either a pair of jets consistent with Standard Model Higgs boson decay into b-quarks or a same-flavour opposite-sign dilepton pair with an invariant mass consistent with a Z boson. The analysis is performed using the proton–proton collision data at \n$$\\sqrt{s}=13$$\n\n TeV collected with the ATLAS detector during the LHC Run-2, corresponding to an integrated luminosity of 139 fb\n$$^{-1}$$\n\n. No excess is observed in the data above the Standard Model predictions. The results are interpreted in simplified models featuring direct production of pairs of either the lighter top squark (\n$$\\tilde{t}_1$$\n\n) or the heavier top squark (\n$$\\tilde{t}_2$$\n\n), excluding at 95% confidence level \n$$\\tilde{t}_1$$\n\n and \n$$\\tilde{t}_2$$\n\n masses up to about 1220 and 875 GeV, respectively.

Single-cell analysis allows biologists to gain huge insight into cell differentiation and tissue structuration. Randomness of differentiation, both in vitro and in vivo, of pluripotent (multipotent) stem cells is now demonstrated to be mainly based on stochastic gene expression. Nevertheless, it remains necessary to incorporate this inherent stochasticity of developmental processes within a coherent scheme. We argue here that the theory called ontophylogenesis is more relevant and better fits with experimental data than alternative theories which have been suggested based on the notions of self-organization and attractor states. The ontophylogenesis theory considers the generation of a differentiated state as a constrained random process: randomness is provided by the stochastic dynamics of biochemical reactions while the environmental constraints, including cell inner structures and cell-cell interactions, drive the system toward a stabilized state of equilibrium. In this conception, biological organization during development can be seen as the result of multiscale constraints produced by the dynamical organization of the biological system which retroacts on the stochastic dynamics at lower scales. This scheme makes it possible to really understand how the generation of reproducible structures at higher organization levels can be fully compatible with probabilistic behavior at the lower levels. It is compatible with the second law of thermodynamics but allows the overtaking of the limitations exhibited by models only based on entropy exchanges which cannot cope with the description nor the dynamics of the mesoscopic and macroscopic organization of biological systems.

This note summarizes the activities and the scientific and technical perspectives of the Laboratoire de Physique Nucleaire et de Hautes Energies (LPNHE) at Sorbonne University, Paris. Although the ESPP is specifically aimed at particle physics, we discuss in this note in parallel the three scientific lines developed at LPNHE (Particle Physics, Astroparticles, Cosmology), first with the current scientific activities, then for the future activities. However, our conclusions and recommendations are focused on the particle physics strategy.

The production cross-sections for W +/- and Z bosons are measured using ATLAS data corresponding to an integrated luminosity of 4.0 pb-1 collected at a centre-ofmass energy v s = 2.76 TeV. The deca ...

the detector resolution in invariant comparable to the B 0-B0 mass difference, a single fit determines the signal yields for both decay modes. This results in a measurement of the branching fraction B(B° → ß + ß - ) = (3.2— q) x 10-9 and an upper limit B ( B 0 → ß +ß - ) < 4.3 x 10-10 at 95% confidence level. The result is combined with the Run 1 ATLAS result, yielding B(B° → B +B - ) = (2.8— ) x 10-9 and B ( B 0 → ß +ß - ) < 2.1 x 10-10 at 95% confidence level. The combined result is consistent with the Standard Model prediction within 2.4 standard deviations in the B ( B 0 → ^ +^ - )-B(B° → B +B - ) plane.