The Standard Model of Particle Physics describes the fundamental building blocks of matter and phenomena up to the highest particle interaction energies. The theory demands the existence of a scalar particle: the Higgs boson. The Higgs boson was discovered by the ATLAS and CMS collaborations at CERN using bosonic final states and is measured to have a mass of around 125 GeV. This particle is predicted to decay predominantly into pairs of b-quarks at this mass, but suffers from overwhelming backgrounds from the multijet production expected from QCD interactions. Therefore, H→bb- production in association with a leptonically decaying W or Z boson is considered, with Z → vv-, W → lv and Z → ll, where ` denotes electrons and muons. This thesis presents a search for the Higgs boson decaying into bb- pairs in association with a W or Z boson using the ATLAS detector at the Large Hadron Collider (LHC) at CERN. The analysis uses the full dataset recorded during pp collisions at the LHC in Run-1, corresponding to 4.7 fb-1 at √s = 7 TeV and 20.3 fb-1 at √s = 8 TeV. A multivariate technique and a kinematic cut-based approach have been used to maximize the signal over background ratio, where a particular emphasis on the latter approach is made in this thesis. Final state radiation and reconstruction effects may decrease the bb- resonance resolution significantly, while comparably decreasing the probability of observing the decay over the background. The b quark pairs from the Higgs boson are reconstructed as topological clusters formed to jets in the ATLAS calorimeter. Thus, the reconstruction and calibration of these jets are crucial for the final Higgs mass resolution and paramount for the search and for future precision measurements of V H, H→bb- production. This thesis presents the development and evaluation of advanced techniques to improve the invariant dijet mass reconstruction of the H→bb- candidate. Sequential jet calibrations, semileptonic corrections and pT corrections to account for the interplay between jet resolution/scale and the underlying signal pT spectrum obtained from Monte Carlo simulations have been studied. A major focus has been made on the development and evaluation of an event-level kinematic likelihood fitting framework to exploit the full kinematic potential of V H topologies within the detector uncertainties of the reconstructed final state signatures in order to improve the measurement of the b-tagged jet kinematics. The jet energy calibrations of the H→bb- signal candidates yield an overall improvement of the dijet invariant mass resolution of up to ~30%, and of the expected statistical significance of ~12%. The analysis procedure is validated using the resonant V Z(bb-) production in the same final states as for the Higgs boson search, and is observed, compatible with the Standard Model expectation, with a significance of 4.9 standard deviations and a signal strength of μ^V Z = 0:74+0:17 -0:16. For a Higgs boson mass of 125.36 GeV, the observed (expected) deviation from the background-only hypothesis is found with a significance of 1.4 (2.6) standard deviations and a signal strength is determined to be μ^V H = 0:52±0:32(stat.)±0:24(syst.).

As one of the major mid-rapidity tracking devices of the STAR detector at the Relativistic Heavy-Ion Collider (RHIC), the Time Projection Chamber (TPC) plays an important role in measuring trajectory and energy of high energy charged particles in polarized proton-proton collision experiments. TPC's in-jet tracking efficiency represents the largest systematic uncertainty on jet energy scale at high transverse momentum, whose measurement contributes to the understanding of the spin structure of protons. The objective of this analysis is to get a better estimation of this systematic uncertainty, through methods of pure Monte-Carlo simulation and real- data embedding, in which simulated tracks are embedded into real-data events. Be- sides, simulated tracks are also embedded into Monte-Carlo events, to make a strict comparison for the uncertainty estimation. The result indicates that the unexplained part of the systematic uncertainty is reduced to 3.3%, from a previous quoted value of 5%. This analysis also suggests that future analysis, such as embedding jets into zero-bias real data and analysis with much higher event statistics, will benefit the understanding of the systematic uncertainty of the in-jet TPC tracking efficiency.