Measurement of jet mass in Pb-Pb and p-Pb collisions

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HEP Data
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2.76 TeV
5.02 TeV
Abstract Plain Text: 
The fragmentation process of a high energetic parton propagating through a dense medium, created in a heavy-ion collisions, is potentially modified compared to the parton shower in vacuum. Collimated jets have a small jet mass while jets with a broad profile have a larger jet mass. Interactions with the medium increase the virtuality of the propagating partons, which increases the radiation at large angles from the leading parton \cite{Vitev:2005yg,Renk:2009nz,Renk:2010zx,Armesto:2011ht}. This would result in a broadening of the jet profile and an increase of the jet mass if all radiated gluons are captured within the definition of the jet. The leading parton experiences substantial virtuality (or mass) depletion along with energy loss\cite{Majumder:2014gda}.
In heavy-ion collisions the jet energy scale is distorted by the large heavy-ion background \cite{Abelev:2012ej}. The contribution of particles unrelated to the hard jet pointing in the same direction as the jet needs to be subtracted. For jet structure measurements, including the jet mass, it is crucial to understand the influence of the background to all components of the 4-vector of the jet.
We will study the performance of jet mass reconstruction in heavy-ion collisions by generating background events resembling the particle densities observed at the LHC: thermal model. Soft particle production in the model follows a Boltzmann distribution with pT=670 \MeVc. The hard component is added by embedding PYTHIA events into this soft background providing a data sample referred to as 'hybrid events'. The hard jets in the PYTHIA events without background are the probe jets while the jets reconstructed from the hybrid events are distorted by the background. The same study is also performed using the ALICE \PbPb{} data as background.
We use sophisticated data-driven background subtraction schemes to correct the jet mass for the contribution of the underlying event. The data is compared at detector level to a PYTHIA reference. We also explore unfolding techniques for two-dimensional observables. The two-dimensional unfolding allows to correct back to particle level after which we compare the data to models.