A search for the Standard Model Higgs boson in proton–proton collisions with the ATLAS detector at the LHC is presented. The datasets used correspond to integrated luminosities of approximately 4.8 fb−1 collected at √s=7 TeV in 2011 and 5.8 fb−1 at √s=8 TeV in 2012. Individual searches in the channels H→ZZ(⁎)→4ℓ, H→γγ and H→WW(⁎)→eνμν in the 8 TeV data are combined with previously published results of searches for H→ZZ(⁎), WW(⁎), bb and τ+τ− in the 7 TeV data and results from improved analyses of the H→ZZ(⁎)→4ℓ and H→γγ channels in the 7 TeV data. Clear evidence for the production of a neutral boson with a measured mass of 126.0±0.4(stat)±0.4(sys) GeV is presented. This observation, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9, is compatible with the production and decay of the Standard Model Higgs boson

A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H → γγ and H → ZZ → 4l decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is m H ¼ 125.09 AE 0.21 ðstatÞ AE 0.11 ðsystÞ GeV. DOI: 10.1103/PhysRevLett.114.191803 PACS numbers: 14.80.Bn, 13.85.Qk The study of the mechanism of electroweak symmetry breaking is one of the principal goals of the CERN LHC program. In the standard model (SM), this symmetry breaking is achieved through the introduction of a complex doublet scalar field, leading to the prediction of the Higgs boson H [1-6], whose mass m H is, however, not predicted by the theory. In 2012, the ATLAS and CMS Collaborations at the LHC announced the discovery of a particle with Higgs-boson-like properties and a mass of about 125 GeV [7][8][9]. The discovery was based primarily on mass peaks observed in the γγ and ZZ → l þ l − l 0þ l 0−(denoted H → ZZ → 4l for simplicity) decay channels, where one or both of the Z bosons can be off shell and where l and l 0 denote an electron or muon. With m H known, all properties of the SM Higgs boson, such as its production cross section and partial decay widths, can be predicted. Increasingly precise measurements [10][11][12][13] have established that all observed properties of the new particle, including its spin, parity, and coupling strengths to SM particles are consistent within the uncertainties with those expected for the SM Higgs boson.The ATLAS and CMS Collaborations have independently measured m H using the samples of proton-proton collision data collected in 2011 and 2012, commonly referred to as LHC Run 1. The analyzed samples correspond to approximately 5 fb −1 of integrated luminosity at ffiffi ffi s p ¼ 7 TeV, and 20 fb −1 at ffiffi ffi s p ¼ 8 TeV, for each experiment. Combined results in the context of the separate experiments, as well as those in the individual channels, are presented in Refs. [12,[14][15][16].This Letter describes a combination of the Run 1 data from the two experiments, leading to improved precision for m H . Besides its intrinsic importance as a fundamental parameter, improved knowledge of m H yields more precise predictions for the other Higgs boson properties. Furthermore, the combined mass measurement provides a first step towards combinations of other quantities, such as the couplings. In the SM, m H is related to the values of the masses of the W boson and top quark through loopinduced effects. Taking into account other measured SM quantities, the comparison of the measurements of the Higgs boson, W boson, and top quark masses can be used to directly test the consistency of the SM [17] and thus to search for evidence of physics beyond the SM.The combination is performed usin...

H. von der Schmitt 99 , J. von Loeben 99 , H. von Radziewski 48 , E. von Toerne 20 , V. Vorobel 126 , V. Vorwerk 11 , M. Vos 166 , R. Voss 29 , T.T. Voss 173 , J.H. Vossebeld 73 , N. Vranjes 12a , M. Vranjes Milosavljevic 12a , V. Vrba 125 , M. Vreeswijk 105 , T. Abstract The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description , interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.

The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for largescale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the AT-LAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.

Distributions measured in high energy physics experiments are usually distorted and/or transformed by various detector effects. A regularization method for unfolding these distributions is re-formulated in terms of the Singular Value Decomposition (SVD) of the response matrix. A relatively simple, yet quite efficient unfolding procedure is explained in detail. The concise linear algorithm results in a straightforward implementation with full error propagation, including the complete covariance matrix and its inverse. Several improvements upon widely used procedures are proposed, and recommendations are given how to simplify the task by the proper choice of the matrix. Ways of determining the optimal value of the regularization parameter are suggested and discussed, and several examples illustrating the use of the method are presented.