Person:

Schwartz, Matthew

Knowing the charge of the parton initiating a light-quark jet could be extremely useful both for testing aspects of the standard model and for characterizing potential beyond-the-standard-model signals. We show that despite the complications of hadronization and out-of-jet radiation such as pileup, a weighted sum of the charges of a jet’s constituents can be used at the LHC to distinguish among jets with different charges. Potential applications include measuring electroweak quantum numbers of hadronically decaying resonances or supersymmetric particles, as well as standard model tests, such as jet charge in dijet events or in hadronically decaying W bosons in (t\bar{t}) events. We develop a systematically improvable method to calculate moments of these charge distributions by combining multihadron fragmentation functions with perturbative jet functions and pertubative evolution equations. We show that the dependence on energy and jet size for the average and width of the jet charge can be calculated despite the large experimental uncertainty on fragmentation functions. These calculations can provide a validation tool for data independent of Monte Carlo fragmentation models.

Jet substructure is typically studied using clustering algorithms, such as kT , which arrange the jets’ constituents into trees. Instead of considering a single tree per jet, we propose that multiple trees should be considered, weighted by an appropriate metric. Then each jet in each event produces a distribution for an observable, rather than a single value. Advantages of this approach include: 1) observables have significantly increased statistical stability; and, 2) new observables, such as the variance of the distribution, provide new handles for signal and background discrimination. For example, we find that employing a set of trees substantially reduces the observed fluctuations in the pruned mass distribution, enhancing the likelihood of new particle discovery for a given integrated luminosity. Furthermore, the resulting pruned mass distributions for (background) QCD jets are found to be substantially wider than that for (signal) jets with intrinsic mass scales, e.g. boosted W jets. A cut on this width yields a substantial enhancement in significance relative to a cut on the standard pruned jet mass alone. In particular the luminosity needed for a given significance requirement decreases by a factor of two relative to standard pruning.

One of the greatest impediments to extracting useful information from high luminosity hadroncollider data is radiation from secondary collisions (i.e. pileup) which can overlap with that of the primary interaction. In this paper we introduce a simple jet-substructure technique termed cleansing which can consistently correct for large amounts of pileup in an observable independent way. Cleansing works at the subjet level, combining tracker and calorimeter-based data to reconstruct the pileup-free primary interaction. The technique can be used on its own, with various degrees of sophistication, or in concert with jet grooming. We apply cleansing to both kinematic and jet shape reconstruction, finding in all cases a marked improvement over previous methods both in the correlation of the cleansed data with uncontaminated results and in measures like S/√ B. Cleansing should improve the sensitivity of new-physics searches at high luminosity and could also aid in the comparison of precision QCD calculations to collider data.

The classification of events involving jets as signal-like or background-like can depend strongly on the jet algorithm used and its parameters. This is partly due to the fact that standard jet algorithms yield a single partition of the particles in an event into jets, even if no particular choice stands out from the others. As an alternative, we propose that one should consider multiple interpretations of each event, generalizing the Qjets procedure to event-level analysis. With multiple interpretations, an event is no longer restricted to either satisfy cuts or not satisfy them – it can be assigned a weight between 0 and 1 based on how well it satisfies the cuts. These cut-weights can then be used to improve the discrimination power of an analysis or reduce the uncertainty on mass or cross-section measurements. For example, using this approach on a Higgs plus Z boson sample, with H → b ¯b we find an 28% improvement in significance can be realized at the 8 TeV LHC. Through a number of other examples, we show various ways in which having multiple interpretations can be useful on the event level.