Suchergebnisse

In recent years, the GeCo Laboratory has undertaken numerous projects to digitalize vast and complex buildings; the specific nature of the different projects has resulted in a case-by-case approach, each time working on past experiences and updating not only the hardware and software tools but also the management and processing methods. This paper presents the workflow followed for the survey of the Fortress of Saint John the Baptist in Florence, an on-going interdisciplinary project. Presently Florence's main trade fair congress centre, at the same time it hosts various buildings that bear witness to the fortress's life-history, combining constructions from the Medici and Lorraine eras with recently built exhibition facilities. Now new research has been required due to the realization of new pavilions and the regeneration of the whole complex. This has included a critical survey, material testing, diagnostic investigations and stratigraphic analyses to define the building's state of preservation. The working group comprises specialists from different institutions, amongst which the Italian Military Geographic Institute, the University of Florence, the National Research Council Institute for the Preservation and Enhancement of the Cultural Heritage, and the Florence City Council.

In recent years, the GeCo Laboratory has undertaken numerous projects to digitalize vast and complex buildings; the specific nature of the different projects has resulted in a case-by-case approach, each time working on past experiences and updating not only the hardware and software tools but also the management and processing methods. This paper presents the workflow followed for the survey of the Fortress of Saint John the Baptist in Florence, an on-going interdisciplinary project. Presently Florence's main trade fair congress centre, at the same time it hosts various buildings that bear witness to the fortress's life-history, combining constructions from the Medici and Lorraine eras with recently built exhibition facilities. Now new research has been required due to the realization of new pavilions and the regeneration of the whole complex. This has included a critical survey, material testing, diagnostic investigations and stratigraphic analyses to define the building's state of preservation. The working group comprises specialists from different institutions, amongst which the Italian Military Geographic Institute, the University of Florence, the National Research Council Institute for the Preservation and Enhancement of the Cultural Heritage, and the Florence City Council.

The recent outbreak of geospatial information to a wider audience, represents an inexorable flow made possible by the technological and scientific advances that cannot be opposed. The democratization of Geomatics technologies requires training opportunities with different level of complexity specifically tailored on the target audience and on the final purpose of the digitization process. In this frame, education plays a role of paramount importance, to create in the final users the awareness of the potentials of Geomatics-based technologies and of the quality control over the entire process. This paper outlines the current educational offer concerning the Geomatics Academic discipline in the Italian higher education system, highlighting the lack of dedicated path entirely devoted to the creation of specifically trained figure in this field. The comparison with the International panorama further stresses out this necessity. The purpose of this work is to present different educational approaches by distinguishing between the starting knowledge level of the students/participants and the final aim of the training activities. Three main audiences have been identified: i) experts, who already know some basics of Geomatics to understand the theoretical concepts behind its technologies; ii) intermediate audience, who are interested in learning about Geomatics technologies and methodologies, without any previous or poor education concerning these topics; iii) non-experts, a mix of a wide group of people, with different educations and interests, or without any interest at all. For each group, the multi-year experience concerning educational and training activities for the geomatics-based knowledge transfer in all the multi-level approaches of the GECO Lab (University of Florence) is presented.

The recent outbreak of geospatial information to a wider audience, represents an inexorable flow made possible by the technological and scientific advances that cannot be opposed. The democratization of Geomatics technologies requires training opportunities with different level of complexity specifically tailored on the target audience and on the final purpose of the digitization process. In this frame, education plays a role of paramount importance, to create in the final users the awareness of the potentials of Geomatics-based technologies and of the quality control over the entire process. This paper outlines the current educational offer concerning the Geomatics Academic discipline in the Italian higher education system, highlighting the lack of dedicated path entirely devoted to the creation of specifically trained figure in this field. The comparison with the International panorama further stresses out this necessity. The purpose of this work is to present different educational approaches by distinguishing between the starting knowledge level of the students/participants and the final aim of the training activities. Three main audiences have been identified: i) experts, who already know some basics of Geomatics to understand the theoretical concepts behind its technologies; ii) intermediate audience, who are interested in learning about Geomatics technologies and methodologies, without any previous or poor education concerning these topics; iii) non-experts, a mix of a wide group of people, with different educations and interests, or without any interest at all. For each group, the multi-year experience concerning educational and training activities for the geomatics-based knowledge transfer in all the multi-level approaches of the GECO Lab (University of Florence) is presented.

The democratization and accessibility of low-cost devices for image acquisition and the development of highly automated procedures for orientation and dense image matching allow almost every person to be a potential producer of photogrammetric models. The diffusion of image-based technologies to produce 3D models amongst wider audiences entails however some risks, as the lack of critical awareness of the final quality of the outputs. Information and education about potentialities and limitations of reality-based digitization by photogrammetry may help spreading procedures and methods for the correct use of this technology. This paper presents the results of one of the funded projects within the 2018 ISPRS Capacity Building Initiatives "Education and training resources on digital photogrammetry". The production of multimedia material for supporting smart educational teaching and learning approaches will be reported, as well as experiences on their application on case studies. Blended innovative teaching and learning pedagogical approaches have been tested, as Flipped Classroom (FC), Learning-by-doing (LBD), Collaborative Learning (CL), and Challenge-Based Learning (CBL), supported by multimedia tools for capacity-building and knowledge transfer. The implementation of multimedia materials for supporting teaching strategies resulted in the production of updated and engaging resources, as videos, tutorials, and datasets to be used during courses, workshops, and seminars targeted to different user groups. The combination of teaching strategies and multimedia supporting materials were tested within national and international projects, from academic courses to complete non-experts, from activities on the field to online and distance learning.

The democratization and accessibility of low-cost devices for image acquisition and the development of highly automated procedures for orientation and dense image matching allow almost every person to be a potential producer of photogrammetric models. The diffusion of image-based technologies to produce 3D models amongst wider audiences entails however some risks, as the lack of critical awareness of the final quality of the outputs. Information and education about potentialities and limitations of reality-based digitization by photogrammetry may help spreading procedures and methods for the correct use of this technology. This paper presents the results of one of the funded projects within the 2018 ISPRS Capacity Building Initiatives "Education and training resources on digital photogrammetry". The production of multimedia material for supporting smart educational teaching and learning approaches will be reported, as well as experiences on their application on case studies. Blended innovative teaching and learning pedagogical approaches have been tested, as Flipped Classroom (FC), Learning-by-doing (LBD), Collaborative Learning (CL), and Challenge-Based Learning (CBL), supported by multimedia tools for capacity-building and knowledge transfer. The implementation of multimedia materials for supporting teaching strategies resulted in the production of updated and engaging resources, as videos, tutorials, and datasets to be used during courses, workshops, and seminars targeted to different user groups. The combination of teaching strategies and multimedia supporting materials were tested within national and international projects, from academic courses to complete non-experts, from activities on the field to online and distance learning.

Aad, G. et al. ; This Letter describes a model-independent search for the production of new resonances in photon + jet (γ+jet) events using 20 fb−1 of proton–proton LHC data recorded with the ATLAS detector at a centre-of-mass energy of View the MathML source. The γ+jet mass distribution is compared to a background model fit from data; no significant deviation from the background-only hypothesis is found. Limits are set at 95% credibility level on generic Gaussian-shaped signals and two benchmark phenomena beyond the Standard Model: non-thermal quantum black holes and excited quarks. Non-thermal quantum black holes are excluded below masses of 4.6 TeV and excited quarks are excluded below masses of 3.5 TeV. ; We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWF and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET, ERC and NSRF, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; GSRT and NSRF, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; BRF and RCN, Norway; MNiSW, Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United Kingdom; DOE and NSF, United States of America. ; Peer reviewed

Measurements of fiducial integrated and differential cross sections for inclusive W+, W− and Z boson production are reported. They are based on 25.0±0.5pb−1 of pp collision data at s√=5.02 TeV collected with the ATLAS detector at the CERN Large Hadron Collider. Electron and muon decay channels are analysed, and the combined W+, W− and Z integrated cross sections are found to be σW+=2266±9 (stat)±29 (syst)±43 (lumi) pb, σW−=1401±7 (stat)±18 (syst)±27 (lumi) pb, and σZ=374.5±3.4 (stat)±3.6 (syst)±7.0 (lumi) pb, in good agreement with next-to-next-to-leading-order QCD cross-section calculations. These measurements serve as references for Pb+Pb interactions at the LHC at sNN−−−√=5.02 TeV. An erratum to this article is available online at https://doi.org/10.1140/epjc/s10052-019-6870-9. ; We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d' Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [52]. ; Peer Reviewed

The efficiency of the photon identification criteria in the ATLAS detector is measured using 36.1 fb1 to 36.7 fb1 of pp collision data at s√=13 TeV collected in 2015 and 2016. The efficiencies are measured separately for converted and unconverted isolated photons, in four different pseudorapidity regions, for transverse momenta between 10 GeV and 1.5 TeV. The results from the combination of three data-driven techniques are compared with the predictions from simulation after correcting the variables describing the shape of electromagnetic showers in simulation for the average differences observed relative to data. Data-to-simulation efficiency ratios are determined to account for the small residual efficiency differences. These factors are measured with uncertainties between 0.5% and 5% depending on the photon transverse momentum and pseudorapidity. The impact of the isolation criteria on the photon identification efficiency, and that of additional soft pp interactions, are also discussed. The probability of reconstructing an electron as a photon candidate is measured in data, and compared with the predictions from simulation. The efficiency of the reconstruction of photon conversions is measured using a sample of photon candidates from Z→μμγ events, exploiting the properties of the ratio of the energies deposited in the first and second longitudinal layers of the ATLAS electromagnetic calorimeter. ; We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, The Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d' Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, UK. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (The Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [43]. ; Peer reviewed

This paper presents measurements of WZ production cross sections in pp collisions at a centre-of-mass energy of 13 TeV. The data were collected in 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider, and correspond to an integrated luminosity of 36.1fb-1. The WZ candidate events are reconstructed using leptonic decay modes of the gauge bosons into electrons and muons. The measured inclusive cross section in the detector fiducial region for a single leptonic decay mode is σW±Z→ℓ′νℓℓfid.=63.7±1.0(stat.)±2.3(syst.)±1.4(lumi.) fb, reproduced by the next-to-next-to-leading-order Standard Model prediction of 61.5-1.3+1.4 fb. Cross sections for WZ and WZ production and their ratio are presented as well as differential cross sections for several kinematic observables. An analysis of angular distributions of leptons from decays of W and Z bosons is performed for the first time in pair-produced events in hadronic collisions, and integrated helicity fractions in the detector fiducial region are measured for the W and Z bosons separately. Of particular interest, the longitudinal helicity fraction of pair-produced vector bosons is also measured. ; We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d' Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, UK. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [106]. ; Peer Reviewed

Aad, G. et al. ; A measurement of the mass difference between top and anti-top quarks is presented. In a 4.7 fb−1 data sample of proton–proton collisions at View the MathML source recorded with the ATLAS detector at the LHC, events consistent with View the MathML source production and decay into a single charged lepton final state are reconstructed. For each event, the mass difference between the top and anti-top quark candidate is calculated. A two b -tag requirement is used in order to reduce the background contribution. A maximum likelihood fit to these per-event mass differences yields View the MathML source, consistent with CPT invariance. ; We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWF and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; EPLANET, ERC and NSRF, European Union; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, DFG, HGF, MPG and AvH Foundation, Germany; GSRT and NSRF, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; FOM and NWO, Netherlands; BRF and RCN, Norway; MNiSW, Poland; GRICES and FCT, Portugal; MNE/IFA, Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SER, SNSF and Cantons of Bern and Geneva, Switzerland; NSC, Taiwan; TAEK, Turkey; STFC, the Royal Society and Leverhulme Trust, United Kingdom; DOE and NSF, United States of America. ; Peer reviewed

Inclusive and differential cross-sections for the production of a top-quark pair in association with a photon are measured with proton-proton collision data corresponding to an integrated luminosity of 36.1 fb-1, collected by the ATLAS detector at the LHC in 2015 and 2016 at a centre-of-mass energy of 13 TeV. The measurements are performed in single-lepton and dilepton final states in a fiducial volume. Events with exactly one photon, one or two leptons, a channel-dependent minimum number of jets, and at least one b-jet are selected. Neural network algorithms are used to separate the signal from the backgrounds. The fiducial cross-sections are measured to be 521±9(stat.)±41(sys.)fb and 69±3(stat.)±4(sys.)fb for the single-lepton and dilepton channels, respectively. The differential cross-sections are measured as a function of photon transverse momentum, photon absolute pseudorapidity, and angular distance between the photon and its closest lepton in both channels, as well as azimuthal opening angle and absolute pseudorapidity difference between the two leptons in the dilepton channel. All measurements are in agreement with the theoretical predictions. ; We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d' Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [64]. ; Peer Reviewed

Searches for scalar leptoquarks pair-produced in proton–proton collisions at s=13 TeV at the Large Hadron Collider are performed by the ATLAS experiment. A data set corresponding to an integrated luminosity of 36.1 fb is used. Final states containing two electrons or two muons and two or more jets are studied, as are states with one electron or muon, missing transverse momentum and two or more jets. No statistically significant excess above the Standard Model expectation is observed. The observed and expected lower limits on the leptoquark mass at 95% confidence level extend up to 1.29 TeV and 1.23 TeV for first- and second-generation leptoquarks, respectively, as postulated in the minimal Buchmüller–Rückl–Wyler model, assuming a branching ratio into a charged lepton and a quark of 50%. In addition, measurements of particle-level fiducial and differential cross sections are presented for the Z→ ee, Z→ μμ and tt¯ processes in several regions related to the search control regions. Predictions from a range of generators are compared with the measurements, and good agreement is seen for many of the observables. However, the predictions for the Z→ ℓℓ measurements in observables sensitive to jet energies disagree with the data. ; We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d' Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [95]. ; Peer Reviewed

The top quark mass is measured using a template method in the tt¯→lepton+jets channel (lepton is e or μ) using ATLAS data recorded in 2012 at the LHC. The data were taken at a proton–proton centre-of-mass energy of s√=8 TeV and correspond to an integrated luminosity of 20.2 fb−1. The tt¯→lepton+jets channel is characterized by the presence of a charged lepton, a neutrino and four jets, two of which originate from bottom quarks (b). Exploiting a three-dimensional template technique, the top quark mass is determined together with a global jet energy scale factor and a relative b-to-light-jet energy scale factor. The mass of the top quark is measured to be mtop=172.08±0.39(stat)±0.82(syst) GeV. A combination with previous ATLAS mtop measurements gives mtop=172.69±0.25(stat)±0.41(syst) GeV. ; Acknowledgements We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, CRC and Compute Canada, Canada; COST, ERC, ERDF, Horizon 2020, and Marie Skłodowska-Curie Actions, European Union; Investissements d' Avenir Labex and Idex, ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya, Spain; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [103] ; Peer reviewed