A Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and \boldit{b}-quark Jets in $p\bar p$ Collisions at $\sqrt{s}=1.96$ TeV

TL;DR

This paper reports a search for the standard model Higgs boson in proton-antiproton collisions using neural networks, focusing on events with missing energy and b-quark jets, setting upper limits on production cross sections.

Contribution

It introduces a neural network-based analysis method for Higgs boson searches in complex event topologies at the Tevatron.

Findings

No significant excess observed over background predictions.

Set 95% CL upper limits on Higgs production cross section.

Limits range from 5.6 to 6.9 times the standard model prediction.

Abstract

We report on a search for the standard model Higgs boson produced in association with a $W$ or $Z$ boson in $p\bar{p}$ collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb$^{-1}$. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a $b$ hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110$\gevm$ to 150$\gevm$. For a mass of 115$\gevm$ the observed (expected) limit is 6.9 (5.6) times the standard model prediction.