Search for the Higgs Boson decaying to tau leptons at ATLAS using multi-variate analysis techniques

This thesis presents three differing approaches to the search for the Standard Model Higgs boson decaying to tau leptons using ps = 7 TeV protonproton collision data from the ATLAS experiment at the LHC. Multi-variate analysis techniques involving boosted decision trees are used to extend an existing cut-based analysis procedure. The expected 95% confidence level upper limit on the observed cross-section is compared between the analyses. The upper limit at a Higgs mass of mH = 125 GeV is improved from 2:9+4:3 2:1 to 2:3+3:3 1:7 times the Standard Model prediction, after implementing multivariate techniques. No significant excess is seen in data for any analysis strategy. The most sensitive measurement of the signal strength normalised to the Standard Model prediction was observed to be ˆ m = 1:6 1:1, corresponding to 1:4s upward fluctuation of the background-only model to match the data

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012

This report of the BOOST2012 workshop presents the results of four working groups that studied key aspects of jet substructure. We discuss the potential of first-principle QCD calculations to yield a precise description of the substructure of jets and study the accuracy of state-of-the-art Monte Carlo tools. Limitations of the experiments’ ability to resolve substructure are evaluated, with a focus on the impact of additional (pile-up) proton proton collisions on jet substructure performance in future LHC operating scenarios. A final section summarizes the lessons learnt from jet substructure analyses in searches for new physics in the production of boosted top quarks

Ensemble deep learning: A review

Ensemble learning combines several individual models to obtain better generalization performance. Currently, deep learning models with multilayer processing architecture is showing better performance as compared to the shallow or traditional classification models. Deep ensemble learning models combine the advantages of both the deep learning models as well as the ensemble learning such that the final model has better generalization performance. This paper reviews the state-of-art deep ensemble models and hence serves as an extensive summary for the researchers. The ensemble models are broadly categorised into ensemble models like bagging, boosting and stacking, negative correlation based deep ensemble models, explicit/implicit ensembles, homogeneous /heterogeneous ensemble, decision fusion strategies, unsupervised, semi-supervised, reinforcement learning and online/incremental, multilabel based deep ensemble models. Application of deep ensemble models in different domains is also briefly discussed. Finally, we conclude this paper with some future recommendations and research directions

A 1200-micron MAMBO survey of ELAISN2 and the Lockman Hole - I. Maps, sources and number counts

The definitive version is available at www.blackwell-synergy.com '.--Copyright Blackwell Publishing. DOI : 10.1111/j.1365-2966.2004.08235.xWe present a deep, new 1200μm survey of the ELAISN2 and Lockman Hole fields using the Max Planck Millimeter Bolometer array (MAMBO). The areas surveyed are 160 arcmin2 in ELAISN2 and 197 arcmin2 in the Lockman Hole, covering the entire SCUBA ‘8mJy Survey’. In total, 27 (44) sources have been detected at a significance 4.0 ( 3.5 ). The primary goals of the survey were to investigate the reliability of (sub)millimetre galaxy (SMG) samples, to analyse SMGs using flux ratios sensitive to redshift at z > 3, and to search for ‘SCUBA drop-outs’, i.e. galaxies at z >> 3. We present the 1200μm number counts and find evidence of a fall at bright flux levels. Employing parametric models for the evolution of the local 60μm IRAS luminosity function (LF), we are able to account simultaneously for the 1200 and 850μm counts, suggesting that the MAMBO and SCUBA sources trace the same underlying population of high-redshift, dust-enshrouded galaxies. From a nearest-neighbour clustering analysis we find tentative evidence that themost significantMAMBO sources come in pairs, typically separated by 23′′. Our MAMBO observations unambiguously confirm around half of the SCUBA sources. In a robust sub-sample of 13 SMGs detected by both MAMBO and SCUBA at a significance 3.5 , only one has no radio counterpart. Furthermore, the distribution of 850/1200μmflux density ratios for this sub-sample is consistent with the spectroscopic redshift distribution of radio-detected SMGs (Chapman et al. 2003). Finally, we have searched for evidence of a high-redshift tail of SMGs amongst the 18 MAMBO sources which are not detected by SCUBA. While we cannot rule out that some of them are SCUBA drop-outs at z >> 3, their overall 850-to-1200μm flux distribution is statistically indistinguishable from that of the 13 SMGS which were robustly identified by both MAMBO and SCUBA.Peer reviewe