Multivariate discrimination and the Higgs+W/Z search

Abstract

A systematic method for optimizing multivariate discriminants is developed and applied to the important example of a light Higgs boson search at the Tevatron and the LHC. The Significance Improvement Characteristic (SIC), defined as the signal efficiency of a cut or multivariate discriminant divided by the square root of the background efficiency, is shown to be an extremely powerful visualization tool. SIC curves demonstrate numerical instabilities in the multivariate discriminants, show convergence as the number of variables is increased, and display the sensitivity to the optimal cut values. For our application, we concentrate on Higgs boson production in association with a W or Z boson with H → bb and compare to the irreducible standard model background, Z/W + bb. We explore thousands of experimentally motivated, physically motivated, and unmotivated single variable discriminants. Along with the standard kinematic variables, a number of new ones, such as twist, are described which should have applicability to many processes. We find that some single variables, such as the pull angle, are weak discriminants, but when combined with others they provide important marginal improvement. We also find that multiple Higgs boson-candidate mass measures, such as from mild and aggressively trimmed jets, when combined may provide additional discriminating power. Comparing the significance improvement from our variables to those used in recent CDF and DØ searches, we find that a 10-20% improvement in significance against Z/W + bb is possible. Our analysis also suggests that the H + W/Z channel with H → bb is also viable at the LHC, without requiring a hard cut on the W/Z transverse momentum.

Quark and gluon jet substructure

“…Cutting on the likelihood is optimal in the sense that it maximizes gluon rejection for every given quark acceptance [25]. Some ways of visualizing the effects of cuts and multivariate improvements were discussed in [43,44].…”

Associated jet and subjet rates in light-quark and gluon jet discrimination

“…2 We drop the α 2 S term in Γ f as it is beyond NDLA and does not affect the boundary condition. Figure 2.…”

“…This includes both discrete variables like the number of charged tracks inside the jet cone, as well as continuous ones like the width of a jet and energy-energy-correlation (EEC) angularity [1][2][3][4][5]. ATLAS and CMS collaborations have also studied the discrimination of light quarks from gluons along these lines with the 7 and 8 TeV LHC data respectively [6,7].…”

“…A large number of variables have been surveyed in the context of quark-gluon discrimination, constructed out of either track based observables or calorimeter based ones [1][2][3][4][5]. While the former category has the practical advantage of being more accurate due to better track momentum resolution as well as being less prone to pile-up contamination, the latter category can be used for jets with larger rapidities outside the tracker coverage.…”

Jet dipolarity: top tagging with color flow

“…More recently, the authors of [22] introduced a jet observable dubbed pull, which is a p T -weighted vector in rapidity-phi space that is constructed so as to point from a given jet to its color-connected partner(s). Although pull has been shown to offer some discrimination in particle searches [29], it does not seem well-suited to tagging boosted hadronic tops. The most straightforward way to incorporate pull into a top tagging algorithm is to measure the pull of two subjets that reconstruct the W ± and check whether each subjet's pull vector points towards the other subjet.…”