Exploring jet substructure with jet shapes in ALICE

The characterization of the jet substructure can give insight into the microscopic nature of the modification induced on high-momentum partons by the Quark-Gluon Plasma that is formed in ultra-relativistic heavy-ion collisions. Jet shapes allow us to study the modification of parton to jet fragmentation and virtuality, probing jet energy redistribution, intra-jet broadening or collimation and possible flavour hierarchy. Results of a selected set of jet shapes will be presented for p–Pb collisions at √ sNN = 5.02 TeV and for Pb–Pb collisions at √ sNN = 2.76 TeV. Results are also compared with PYTHIA calculations and models that include in-medium energy loss.

energy lost out of the jet cone High-p T and virtuality partons lose energy traveling through the medium at large angle → jet not modified "pp-like" inside the jet cone → jet broadening Jet structures allow to study: detailed mechanisms of the energy loss modification of the fragmentation fundamental properties of the medium (density, degree of freedom, …) flavour differences Jet yields are suppressed (R AA < 1) energy lost out of the jet cone High-p T and virtuality partons lose energy traveling through the medium at large angle → jet not modified "pp-like" inside the jet cone → jet broadening

Radial moment (g):
Measures the momentum re-distribution of jet constituents weighted by their distance from the jet axis. Jet shapes are observables constructed combining information: on how the constituents are distributed in the jet considering the clustering history.

Jet Mass (M)
Difference of the momentum of the jets and the energy of its constituents weighted by their pseudo-rapidity. Related to the virtuality of the parton traversing the medium. pared to their p T . To clarify our statement, i massless four-momenta are reconstructed, th reconstructed jet, while, the z-component and magnitude of the be obtained as, In terms of the equations above, the reconstru of the jet may be obtained as, One should note that the calculation of the m reconstructed jet involves, not just a knowledg We propose an extension to classify jet modification in heavy-ion collisions by including the jet mass along with its energy. The mass of a jet, as measured by jet reconstruction algorithms, is constrained by the jet's virtuality, which in turn has a considerable e↵ect on such observables as the fragmentation function and jet shape observables. The leading parton, propagating through a dense medium, experiences substantial virtuality (or mass) depletion along with energy loss. Meaningful comparisons between surviving jets and jets produced in p-p collisions require mass depletion to be taken into account. Using a vacuum event generator, we show the close relationship between the actual jet mass and that after applying a jet reconstruction algorithm. Using an in-medium event generator, we demonstrate the clear di↵erence between the mass of a surviving parton exiting a dense medium and a parton with a similar energy formed in a hard scattering event. E↵ects of this di↵erence on jet observables are discussed. 25.75.Dw, With the advent of the LHC, the study of the modation of hard jets in a Quark-Gluon-Plasma (QGP) s entered a detailed phase: Unlike the case at the Relivistic Heavy-Ion Collider (RHIC), where one has so been limited to few particle observables [1, 2], isolan and reconstruction of particles within a jet, from the ckground of particles at the LHC, has led to an entirely w methodology of studying jets [3-10]: currently, new servables such as the dijet asymmetry, intra-jet fragntation functions and jet shapes are being measured multiple experiments.
By all accounts, detailed comparisons between theory d the new observables should lead to deeper insight o the mechanisms by which jet showers are modified by e presence of a medium [11][12][13][14][15], and how energy flows a reconstructed mass M , which is non-negligible compared to their p T . To clarify our statement, if n almost massless four-momenta are reconstructed, then, for the reconstructed jet, while, the z-component and magnitude of the vector may be obtained as, In terms of the equations above, the reconstructed mass Jet shapes are observables constructed combining information: on how the constituents are distributed in the jet considering the clustering history.
p T distribution of hard subjet (z g ) Momentum balance of the two hard sub-jets. Observable connected to the hardest splitting.
ple LHC13b4 plus (PYTHIA6 Perugia 2011 tune, 10 hard parton p T bins) ed for the analysis. e considered in the analysis. Jets are reconstructed with the anti-k T algo-stJet package [REF] clustering charged tracks with the momentum above e. The jet cone radius of R = 0.4 is used. Acceptance cut |h jet | < 0.5 is 6pR 2 is applied, and the jet area is calculated used ghosts with the cell area bstructure algorithm, implemented in the FastJet Contributions package jets. Parameters b = 0 and z cut = 0.1 were used. z g defined as

Good agreement between data and NLO calculations
Recent calculations based on NNLO+LL R including UE and hadronization effects seem to be in better agreement than just NNLO calculations.  Jet shapes, fully corrected to charged particle level. Jet shapes, fully corrected to charged particle level. Reasonable agreement between data and PYTHIA calculations for all the jet shapes. Use PYTHIA as reference for Pb-Pb Important for low R where hadronisation effects start to play an important role. Reasonable agreement between data and PYTHIA calculations for jet mass.
Slightly worst agreement with HERWIG, in particular in the low mass tail.
p-Pb measurement can be used as reference for the comparison with the Pb-Pb one.   Jet shapes are observables constructed combining information: on how the constituents are distributed in the jet considering the clustering history. embedding technique presented in Sec. 4. The systematic uncertainty due to the background subtraction method varies between 5% at the center of the distribution and 30% in the tails.
As mentioned in Sec. 3.2, in p-Pb events the background subtraction introduces additional fluctuations due to the region-to-region fluctuations of the background, which leads to a broadening of the jet mass distribution after subtraction. It was therefore decided not to perform the subtraction event-by-event and jet-by-jet, and instead include the background in the response matrix and correct for in it the unfolding.
As an extreme variation for the systematic uncertainty, the background was subtracted event-by-event in the data with the constituent method, which is less sensitive to fluctuations than the area method, and corrected only for detector effects using the PYTHIA response. The jet mass distributions corrected with the two assumptions differ by 5% in the peak region and the difference increases gradually up to 40% in the low-mass tail. These variations were taken as systematic uncertainties.
The uncertainty in the detector response was dominated by the uncertainty in the tracking efficiency, which was estimated by varying track quality cuts and found to be 3-4%. The tracking efficiency in the detector simulation was varied accordingly, providing an alternative response matrix with which to repeat the unfolding. Observed differences with respect to the nominal result vary from 10% to 40% and 5% to 30% in Pb-Pb and p-Pb, respectively, with the largest uncertainty in the tails of the distributions.
All systematic uncertainties were added in quadrature for each M ch jet bin. The uncertainties affect the shape of the jet mass distribution and the normalization applied causes long-range anti-correlations.   Not negligible difference in the jet shapes due to due to q/g difference fraction at two collider energies.