Damage production in atomic displacement cascades in beryllium

AbstractThe paper presents the results of a molecular dynamics simulation of cascade damage production in beryllium caused by self-ion recoils in the energy range of 0.5–3keV. It is demonstrated that point defects are produced in Be preferentially in well-separated subcascades generated by secondary and higher order recoils. A linear dependence of the point defect number on the primary recoil energy is obtained with the slope that corresponds to formal atom displacement energy of ∼21eV. Most of the damage is created as single defects and the relatively high part of created point defects (∼50%) survives the correlated recombination following the ballistic cascade stage and becomes freely-migrating

Multiscale modelling of hydrogen behaviour on beryllium (0001) surface

Beryllium is proposed to be a neutron multiplier and plasma facing material in future fusion devices. Therefore, it is crucial to acquire an understanding of the microscopic mechanisms of tritium accumu- lation and release as a result of transmutation processes that Be undergoes under neutron irradiation. A multiscale simulation of ad- and desorption of hydrogen isotopes on the beryllium (0 0 01) surface is developed. It consists of ab initio calculations of certain H adsorption configurations, a suitable clus- ter expansion approximating the energies of arbitrary configurations, and a kinetic Monte Carlo method for dynamic simulations of adsorption and desorption. The processes implemented in the kinetic Monte Carlo simulation are deduced from further ab initio calculations comprising both, static relaxation as well as molecular dynamics runs. The simulation is used to reproduce experimental data and the results are compared and discussed. Based on the observed results, proposals for a refined model are made

The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. METHODS: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. FINDINGS: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). INTERPRETATION: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden

Study of Z → llγ decays at √s = 8 TeV with the ATLAS detector

This paper presents a study of Z → llγ decays with the ATLAS detector at the Large Hadron Collider. The analysis uses a proton–proton data sample corresponding to an integrated luminosity of 20.2 fb−1 collected at a centre-ofmass energy √s = 8 TeV. Integrated fiducial cross-sections together with normalised differential fiducial cross-sections, sensitive to the kinematics of final-state QED radiation, are obtained. The results are found to be in agreement with stateof-the-art predictions for final-state QED radiation. First measurements of Z → llγ γ decays are also reported

Constraints on spin-0 dark matter mediators and invisible Higgs decays using ATLAS 13 TeV pp collision data with two top quarks and missing transverse momentum in the final state

This paper presents a statistical combination of searches targeting final states with two top quarks and invisible particles, characterised by the presence of zero, one or two leptons, at least one jet originating from a b-quark and missing transverse momentum. The analyses are searches for phenomena beyond the Standard Model consistent with the direct production of dark matter in pp collisions at the LHC, using 139 fb−1 of data collected with the ATLAS detector at a centre-of-mass energy of 13 TeV. The results are interpreted in terms of simplified dark matter models with a spin-0 scalar or pseudoscalar mediator particle. In addition, the results are interpreted in terms of upper limits on the Higgs boson invisible branching ratio, where the Higgs boson is produced according to the Standard Model in association with a pair of top quarks. For scalar (pseudoscalar) dark matter models, with all couplings set to unity, the statistical combination extends the mass range excluded by the best of the individual channels by 50 (25) GeV, excluding mediator masses up to 370 GeV. In addition, the statistical combination improves the expected coupling exclusion reach by 14% (24%), assuming a scalar (pseudoscalar) mediator mass of 10 GeV. An upper limit on the Higgs boson invisible branching ratio of 0.38 (0.30+0.13−0.09) is observed (expected) at 95% confidence level

Search for heavy Majorana or Dirac neutrinos and right-handed W gauge bosons in final states with charged leptons and jets in pp collisions at √s = 13 TeV with the ATLAS detector

A search for heavy right-handed Majorana or Dirac neutrinos NR and heavy right-handed gauge bosons WR is performed in events with energetic electrons or muons, with the same or opposite electric charge, and energetic jets. The search is carried out separately for topologies of clearly separated final-state products (“resolved” channel) and topologies with boosted final states with hadronic and/or leptonic products partially overlapping and reconstructed as a large-radius jet (“boosted” channel). The events are selected from pp collision data at the LHC with an integrated luminosity of 139 fb−1 collected by the ATLAS detector at √s = 13 TeV. No significant deviations from the Standard Model predictions are observed. The results are interpreted within the theoretical framework of a left-right symmetric model, and lower limits are set on masses in the heavy righthanded WR boson and NR plane. The excluded region extends to about m(WR) = 6.4 TeV for both Majorana and Dirac NR neutrinos at m(NR) < 1 TeV. NR with masses of less than 3.5 (3.6) TeV are excluded in the electron (muon) channel at m(WR) = 4.8 TeV for the Majorana neutrinos, and limits of m(NR) up to 3.6 TeV for m(WR) = 5.2 (5.0) TeV in the electron (muon) channel are set for the Dirac neutrinos. These constitute the most stringent exclusion limits to date for the model considered

Deep generative models for fast photon shower simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques