Pileup Per Particle Identification

TL;DR

Pileup mitigation at high-luminosity colliders is addressed with PUPPI, a per-particle weighting scheme that uses a local shape α to distinguish pileup from hard-scatter radiation. By computing event-wide α distributions from charged pileup and converting particle-level α into weights, PUPPI rescale particle momenta to form a pileup-corrected event prior to jet clustering. The approach integrates additional detector information via generalized χ^2 weighting and supports forward regions where tracking is limited. Across simulated dijet and Z+jets scenarios, PUPPI improves jet p_T and mass resolutions and enhances MET performance, demonstrating benefits over existing methods and offering a flexible framework for further detector-specific refinements.

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.

Figures (10)

• Figure 1: The distribution of $\alpha_i$, over many events, for particles $i$ from the leading vertex (gray filled) and particles from pileup (blue) in a dijet sample. For $\alpha_i^F$ (left) we sum over all particles as defined in Eqs. (\ref{['eq:alpha']}) or (\ref{['eq:alphaFWD']}), for $\alpha_i^C$ (right) we sum over charged particles from the leading vertex as defined in Eq. (\ref{['eq:alphaLV']}). Both distributions consider only particles with a $p_T > 1~\mathrm{GeV}$. Dotted and solid lines refer to neutral and charged particles respectively.
• Figure 2: The distribution of weights from Eq. (\ref{['eq:weight']}), over many events, for neutral particles $i$ with $p_T > 1~\mathrm{GeV}$ from the leading vertex (gray) and particles from pileup (blue) in a dijet sample. The weights are calculated using $\alpha_i^F$ (left) and $\alpha_i^C$ (right). In this sample, for weights from $\alpha_i^F$, $30 \%$ ($5 \%$) of neutral PU (LV) particles have $w_i<0.02$ while $10 \%$ ($60 \%$) have $w_i>0.98$. For weights from $\alpha_i^C$, $50 \%$ ($5 \%$) of neutral PU (LV) particles have $w_i<0.02$ while $5 \%$ ($55 \%$) have $w_i>0.98$.
• Figure 3: The mean weight, over many events, of neutral particles from the leading vertex (red) and pileup (blue) as a function of the particle's $p_T$ in a dijet sample.
• Figure 4: Event display for sample dijet event with $80$ pileup interactions added. The particle collections shown are LV (top left), PFlow (top right), PFlowCHS (bottom left), and PUPPI (bottom right). Particles from the leading vertex are colored according to their $p_T$, while particles from pileup are uncolored and their size is logarithmically proportional to their $p_T$. The unfilled colored circles show anti-$k_T$$R=0.7$ jets where the colors denote the $p_T$ bin. The bins $25-50~\mathrm{GeV}$, $50-200~\mathrm{GeV}$, and $>200~\mathrm{GeV}$ correspond to colors of magenta, cyan, and blue respectively. In the PFlow and PFlowCHS events, the average value of $p_T$ among the pileup cells is $\sim 0.7~\mathrm{GeV}$ and $\sim 0.4~\mathrm{GeV}$, respectively.
• Figure 5: Jet multiplicity as a function of pseudorapidity for $n_{\text{PU}} = 80$.