Abstract
We propose a new method for pileup mitigation by implementing “pileup per particle identification” (PUPPI). For each particle we first define a local shape α which probes the collinear versus soft diffuse structure in the neighborhood of the particle. The former is indicative of particles originating from the hard scatter and the latter of particles originating from pileup interactions. The distribution of α for charged pileup, assumed as a proxy for all pileup, is used on an event-by-event basis to calculate a weight for each particle. The weights describe the degree to which particles are pileup-like and are used to rescale their four-momenta, superseding the need for jet-based corrections. Furthermore, the algorithm flexibly allows combination with other, possibly experimental, probabilistic information associated with particles such as vertexing and timing performance. We demonstrate the algorithm improves over existing methods by looking at jet p T and jet mass. We also find an improvement on non-jet quantities like missing transverse energy.
Highlights
Pileup jet identification [2, 4]: removes entire jets that are identified as being composed primarily of pileup using both charged particle information and jet shapes
We propose a new method for pileup mitigation by implementing “pileup per particle identification” (PUPPI)
We study the performance of the PUPPI algorithm on several jet and event observables
Summary
We describe qualitatively how the algorithm works. First we select a shape α, which attempts to locally distinguish parton shower-like radiation from pileuplike radiation, compute it for each particle in an event. We assign a weight to each particle by comparing its α value to the median of the charged pileup distribution. In that region, tracking information provides the ability to distinguish charged tracks originating from the leading vertex and charged tracks originating from pileup Associating these tracks to particles can be done with the particle flow algorithm [21] which combines measurements from various detector subsystems to define individual candidates.. This assumes the distribution of αF and αC is the same for charged and neutral particles, and for central and forward particles Neither of these assumptions is exact, but they both can be corrected if necessary. Because the computation of αPFU and σPFU is only done for charged pileup, it must be computed in the central region, even though these quantities are used to calculate the weights of particles in the forward region. The weights would be calculated using the correction {αPFU, σPFU} → f (yi){αPFU, σPFU} where f (y) is extracted from minimum-bias data
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