Achieving fairness with a simple ridge penalty

In this paper, we present a general framework for estimating regression models subject to a user-defined level of fairness. We enforce fairness as a model selection step in which we choose the value of a ridge penalty to control the effect of sensitive attributes. We then estimate the parameters of the model conditional on the chosen penalty value. Our proposal is mathematically simple, with a solution that is partly in closed form and produces estimates of the regression coefficients that are intuitive to interpret as a function of the level of fairness. Furthermore, it is easily extended to generalised linear models, kernelised regression models and other penalties, and it can accommodate multiple definitions of fairness. We compare our approach with the regression model from Komiyama et al. (in: Proceedings of machine learning research. 35th international conference on machine learning (ICML), vol 80, pp 2737–2746, 2018), which implements a provably optimal linear regression model and with the fair models from Zafar et al. (J Mach Learn Res 20:1–42, 2019). We evaluate these approaches empirically on six different data sets, and we find that our proposal provides better goodness of fit and better predictive accuracy for the same level of fairness. In addition, we highlight a source of bias in the original experimental evaluation in Komiyama et al. (in: Proceedings of machine learning research. 35th international conference on machine learning (ICML), vol 80, pp 2737–2746, 2018)

HBD HV Control and Monitoring System for the PHENIX Experiment at the Relativistic Heavy Ion Collider

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Dijet Invariant Mass Studies in the Higgs boson H→bb- resonance search in association with a W/Z boson using the ATLAS detector

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.)

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton-proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 fb$^{-1}$ of collisions at a centre-of-mass energy of $\sqrt{s}$ = 8 TeV, although in some case an additional 4.7 fb$^{-1}$ of collision data at $\sqrt{s}$ = 7 TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models