A. Figure, 1: Normalized distribution of the discriminating variables used as input of the boosted decision tree for signal (blue) and background (red) for 2-jets events

A. Figure, 2: Normalized distribution of the discriminating variables used as input of the boosted decision tree for signal (blue) and background (red) for 2-jets events

A. Figure, 3: Normalized distribution of the discriminating variables used as input of the boosted decision tree for signal (blue) and background (red) for 3-jets events

A. Figure, 4: Normalized distribution of the discriminating variables used as input of the boosted decision tree for signal (blue) and background (red) for 3-jets events

A. Figure, 5: Stacked distributions of the variables used as input of the BDT for the 2-jets pretag sample

A. Figure, 6: Stacked distributions of the variables used as input of the BDT for the 2-jets pretag sample

A. Figure, 7: Stacked distributions of the variables used as input of the BDT for the 2-jets pretag sample

A. Figure, 8: Stacked distributions of the variables used as input of the BDT for the 2-jets pretag sample

A. Figure, 9: Stacked distributions of the variables used as input of the BDT for the 3-jets pretag sample

A. Figure, 10: Stacked distributions of the variables used as input of the BDT for the 3-jets pretag sample

A. Figure, 11: Stacked distributions of the variables used as input of the BDT for the 3-jets pretag sample

A. Figure, 12: Stacked distributions of the variables used as input of the BDT for the 3-jets pretag sample

A. Figure, 13: Stacked distributions of the variables used as input of the BDT for the 2-jets tag sample

A. Figure, 14: Stacked distributions of the variables used as input of the BDT for the 2-jets tag sample

A. Figure, 15: Stacked distributions of the variables used as input of the BDT for the 2-jets tag sample

A. Figure, 16: Stacked distributions of the variables used as input of the BDT for the 2-jets tag sample

A. Figure, 17: Stacked distributions of the variables used as input of the BDT for the 3-jets tag sample

A. Figure, 18: Stacked distributions of the variables used as input of the BDT for the 3-jets tag sample

A. Figure, 19: Stacked distributions of the variables used as input of the BDT for the 3-jets tag sample

A. Figure, 20: Stacked distributions of the variables used as input of the BDT for the 3-jets tag sample

M. Aliev, HATHOR ??? HAdronic Top and Heavy quarks crOss section calculatoR, Computer Physics Communications, vol.182, issue.4, pp.1034-1046, 2011.
DOI : 10.1016/j.cpc.2010.12.040
URL : http://arxiv.org/abs/1007.1327

S. M. Langenfeld and P. Uwer, Measuring the running top-quark mass, Physical Review D, vol.80, issue.5, p.54009, 2009.
DOI : 10.1103/PhysRevD.80.054009

N. Kidonakis, Next-to-next-to-leading soft-gluon corrections for the top quark cross section and transverse momentum distribution, Physical Review D, vol.82, issue.11, p.114030, 2010.
DOI : 10.1103/PhysRevD.82.114030

M. N. Ahrens and A. Ferroglia, Renormalization-group improved predictions for top-quark pair production at hadron colliders, Journal of High Energy Physics, vol.102, issue.9, pp.1009-097, 2010.
DOI : 10.1007/JHEP09(2010)097
URL : http://arxiv.org/abs/1003.5827

L. Rudolf, S. Ps-division, D. Div, . Manglunki, and . Div, CERN, 02.09.96 Revised and adapted by Antonella Del Rosso, ETT Div

D. Fournier, Performance of the LHC, ATLAS and CMS in 2011, EPJ Web of Conferences, vol.28
DOI : 10.1051/epjconf/20122801003

B. Marcello, Mass measurements of the top quark in electroweak production channels at ATLAS, 2006.

B. Atlas-collaboration, K. Alvarez, M. Becker, D. Castanheira, S. Chakraborty et al., Measurement of the t-channel single top-quark production cross section

N. Kidonakis, -channel single top quark production, Physical Review D, vol.83, issue.9, 2011.
DOI : 10.1103/PhysRevD.83.091503
URL : https://hal.archives-ouvertes.fr/in2p3-00024705

F. M. Campbell and R. Frederix, NLO predictions for t-channel production of single top and fourth generation quarks at hadron colliders, Journal of High Energy Physics, vol.1998, issue.10, p.42, 2009.
DOI : 10.1016/j.physrep.2005.12.006

M. Kobayashi and T. Maskawa, -Violation in the Renormalizable Theory of Weak Interaction, Progress of Theoretical Physics, vol.49, issue.2, pp.49-652, 1973.
DOI : 10.1143/PTP.49.652
URL : https://hal.archives-ouvertes.fr/hal-00409826

S. L. Glashow, Partial-symmetries of weak interactions, Partial Symmetries of Weak Interactions, pp.579-588, 1961.
DOI : 10.1016/0029-5582(61)90469-2

S. Weinberg, A Model of Leptons, Physical Review Letters, vol.19, issue.21, pp.1264-1266, 1967.
DOI : 10.1103/PhysRevLett.19.1264

A. Salam, Gauge unification of fundamental forces, Reviews of Modern Physics, vol.52, issue.3, pp.525-538, 1980.
DOI : 10.1103/RevModPhys.52.525

P. W. Higgs, Spontaneous Symmetry Breakdown without Massless Bosons, Spontaneous Symmetry Breakdown without Massless Bosons, pp.1156-1163, 1966.
DOI : 10.1103/PhysRev.145.1156

H. Yukawa, On the interaction of elementary particles, Proc. Phys, pp.48-57, 1935.

D. Gross and F. Wilczek, Ultraviolet Behavior of Non-Abelian Gauge Theories, Physical Review Letters, vol.30, issue.26, p.1343, 1973.
DOI : 10.1103/PhysRevLett.30.1343

F. Abe, Observation of top quark production in p¯ p collisions with the Collider Detector at Fermilab, Phys. Rev. Lett, p.74, 1995.

D. Collaboration and S. Abachi, Observation of the top quark, Il Nuovo Cimento A, vol.69, issue.6-7, pp.2632-26379503003, 1995.
DOI : 10.1007/BF02731710

C. , D. Collaboration, and M. Lancaster, Combination of CDF and D0 results on the mass of the top quark using up to 5.8 fb-1 of data
DOI : 10.2172/1021497

B. L. Combridge, Associated production of heavy flavour states in pp and p??p interactions: Some QCD estimates, Nuclear Physics B, vol.151, pp.429-456, 1979.
DOI : 10.1016/0550-3213(79)90449-8

Z. G. Bernreuther, A. Brandenburg, and P. Uwer, Top quark pair production and decay at hadron colliders, Nuclear Physics B, vol.690, issue.1-2, pp.81-1370403035, 2004.
DOI : 10.1016/j.nuclphysb.2004.04.019

A. V. Ahrens and . Ferroglia, Renormalization-group improved predictions for top-quark pair production at hadron colliders, Journal of High Energy Physics, vol.102, issue.9, 2010.
DOI : 10.1007/JHEP09(2010)097

R. Frederix, Top quark phenomenology at hadron colliders, 2009.

W. Bernreuther, Top-quark physics at the LHC, Journal of Physics G: Nuclear and Particle Physics, vol.35, issue.8
DOI : 10.1088/0954-3899/35/8/083001

S. Willenbrock and D. Dicus, Production of Heavy Quarks from W Gluon Fusion, Phys. Rev, vol.155, p.34, 1986.

N. Kidonakis, NNLL resummation for s-channel single top quark production, Phys. Rev. D, vol.81, issue.054028, 2010.

M. Jezabek and J. H. Kuhn, QCD corrections to semileptonic decays of heavy quarks, Nuclear Physics B, vol.314, issue.1, 1989.
DOI : 10.1016/0550-3213(89)90108-9

J. H. Kuhn, Theory of top quark production and decay, arXiv:9707321 [hep-ph], Probing anomalous Wtb couplings in top pair decays, Eur.Phys.J. C50 519

. T. Cdf-collaboration and . Aaltonen, Observation of the top quark, Il Nuovo Cimento A, vol.69, issue.6-7, p.81, 2010.
DOI : 10.1007/BF02731710

P. U. Cdf-collaboration and . Moch, Observation of the top quark, Il Nuovo Cimento A, vol.69, issue.6-7, pp.183-75, 2008.
DOI : 10.1007/BF02731710

N. Kidonakis, Single top quark production at the Fermilab Tevatron: Threshold resummation and finite-order soft gluon corrections, Physical Review D, vol.74, issue.11, p.114012, 2006.
DOI : 10.1103/PhysRevD.74.114012

C. , D. Collaboration, and T. E. Group, Combination of CDF and D0 Measurements of the Single Top Production Cross Section, pp.hep-ex
DOI : 10.2172/963445

. Muidmuoncollection, ch/twiki/bin/viewauth/atlasprotected/muidmuoncollection. [90] ATLAS Collaboration, Track Reconstruction in the ATLAS Muon Spectrometer with MOORE, 2003.

G. P. Salam and G. Soyez, A practical seedless infrared-safe cone jet algorithm, Journal of High Energy Physics, vol.2006, issue.05, p.5, 2007.
DOI : 10.1016/j.physletb.2005.08.125
URL : https://hal.archives-ouvertes.fr/hal-00170223

G. Piacquadio and C. Weiser, A new inclusive secondary vertex algorithm for b-jet tagging in ATLAS, Journal of Physics: Conference Series, vol.119, issue.3, p.32032, 2008.
DOI : 10.1088/1742-6596/119/3/032032

J. Pumplin, New Generation of Parton Distributions with Uncertainties from Global QCD Analysis, Journal of High Energy Physics, vol.28, issue.07, p.12, 2002.
DOI : 10.1016/S0370-2693(01)01090-5

B. P. Kersevan and R. W. Elzbieta, The Monte Carlo Event Generator AcerMC version 3.5 with interfaces to PYTHIA 6.4, HERWIG 6.5 and ARIADNE 4, p.405247, 2008.

M. L. Mangano, M. Moretti, F. Piccinini, R. Pittau, and A. D. Polosa, ALPGEN, a generator for hard multiparton processes in hadronic collisions, Journal of High Energy Physics, vol.46, issue.07, p.7, 2003.
DOI : 10.1016/0370-2693(91)91396-D

S. Frixione, B. R. Webber, and P. Nason, MC@NLO Generator version 3, p.305252, 2002.

P. Nason, A new method for combining NLO QCD computations with parton shower simulations, JHEP, vol.11, p.409146, 2004.

S. Frixione and P. Nason, Positive weight next-to-leading-order Monte Carlo, JHEP, vol.11111, p.7073088, 2007.

G. Corcella, HERWIG 6.5: an event generator for Hadron Emission Reactions With Interfering Gluons (including supersymmetric processes), JHEP, vol.01, issue.010, pp.hep-ph, 2001.

T. Sjostrand, S. Mrenna, and P. Skands, PYTHIA Generator version 6, pp.5-026, 2006.

J. M. Butterworth, J. R. Forshaw, and M. H. Seymour, Multiparton interactions in photoproduction at HERA, Zeitschrift f??r Physik C: Particles and Fields, vol.66, issue.4, pp.637-646, 1996.
DOI : 10.1007/s002880050286

N. L. Hoeche and F. Krauss, Matching Parton Showers and Matrix Elements, . [113] Single Top Object Definition

. Atlas-top and . Group, Mis-identified lepton backgrounds in top quark pair production studies for EPS 2011 analyses, 2011.

J. Quinlan, Induction of decision trees, Machine Learning, vol.1, issue.1, pp.81-106, 1986.
DOI : 10.1007/BF00116251

B. R. Yang and J. Zhu, Studies of boosted decision trees for MiniBooNE particle identification, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol.555, issue.1-2, 2005.
DOI : 10.1016/j.nima.2005.09.022

B. Atlas-collaboration, K. Alvarez, M. Becker, D. Castanheira, S. Chakraborty et al., Measurement on t-channel single-top quark production using boosted decision trees, 2011.

M. Feindt, A Neural Bayesian Estimator for Conditional Probability Densities, arXiv:0402093v1 [physics.data-an]

M. Feindt and U. Kerzel, The NeuroBayes neural network package, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol.559, issue.1, pp.559-190, 2006.
DOI : 10.1016/j.nima.2005.11.166

A. Hocker, TMVA: Toolkit for multivariate data analysis, PoS ACAT, vol.040, 2007.
URL : https://hal.archives-ouvertes.fr/in2p3-00158246

L. Breiman, J. Friedman, R. Olshen, and C. Stone, Classification and Regression Trees, 1984.

Y. Freund and R. E. Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Journal of Computer and System Sciences, vol.55, issue.1, pp.119-139, 1997.
DOI : 10.1006/jcss.1997.1504

J. Campbell and R. Ellis, Mcfm?monte carlo for femtobarn processes

R. D. Cousins, J. T. Linnemann, and J. Tucker, Evaluation of three methods for calculating statistical significance when incorporating a systematic uncertainty into a test of the background-only hypothesis for a Poisson process, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol.595, issue.2, p.480, 2008.
DOI : 10.1016/j.nima.2008.07.086

M. Feindt, A Neural Bayesian Estimator for Conditional Probability Densities, arXiv:0402093v1 [physics.data-an]

T. T. Malkawi and C. P. Yuan, A model of strong flavor dynamics for the top quark, Physics Letters B, vol.385, issue.1-4, 1996.
DOI : 10.1016/0370-2693(96)00859-3

B. A. Burdman and E. Ponton, Resonances from two universal extra dimensions, Physical Review D, vol.74, issue.7, p.75008, 2006.
DOI : 10.1103/PhysRevD.74.075008
URL : http://arxiv.org/abs/hep-ph/0601186

M. Perelstein, Little Higgs models and their phenomenology, Progress in Particle and Nuclear Physics, vol.58, issue.1, 2007.
DOI : 10.1016/j.ppnp.2006.04.001
URL : http://arxiv.org/abs/hep-ph/0512128

F. M. Andrea and B. Fuks, Monotops at the LHC, Physical Review D, vol.84, issue.7, p.6199, 2011.
DOI : 10.1103/PhysRevD.84.074025

F. S. Lacker and A. Menzel, Model-independent extraction of |V tq | matrix elements from top-quark measurements at hadron colliders

P. S. Saurabh and D. Rindani, Probing anomalous tbW couplings in single-top production using top polarization at the Large Hadron Collider

J. D. Jung and A. Pierce, Top-quark asymmetry and the search for a light hadronic resonance in association with a single top quark, Physical Review D, vol.84, issue.9
DOI : 10.1103/PhysRevD.84.091502

J. S. Yao-bei and . Liu, Associated production of the charged Higgs boson and single top quark at the LHC , Mod, Phys.Lett.A, vol.24, pp.143-150, 2009.

D. Collaboration and V. M. Abazov, Model-independent measurement of t-channel single top quark production in p¯ p collisions at ? s = 1

. Atlas-top and . Group, Scale Factors For Use in Rel 16 analyses

K. Becker, D. Hirschbuehl, P. Sturm, and W. Wagner, Measurement of t-Channel Single Top-Quark Production in pp Collisions at sqrts = 7TeV using Neural Networks, Tech. Rep. ATL-COM, 2011.