Jet Tomography in Heavy-Ion Collisions with Deep Learning.

Deep learning techniques have the power to identify the degree of modification of high energy jets traversing deconfined QCD matter on a jet-by-jet basis. Such knowledge allows us to study jets based on their initial, rather than final, energy. We show how this new technique provides unique access to the genuine configuration profile of jets over the transverse plane of the nuclear collision, both with respect to their production point and their orientation. By effectively removing the selection biases induced by final-state interactions, one can analyze the potential azimuthal anisotropies of jet production associated to initial-state effects. Additionally, we demonstrate the capability of our new method to locate with precision the production point of a dijet pair in the nuclear overlap region, in what constitutes an important step forward toward the long term quest of using jets as tomographic probes of the quark-gluon plasma.

Cone-Size Dependence of Jet Suppression in Heavy-Ion Collisions.

The strong suppression of high-p_{T} jets in heavy-ion collisions is a result of elastic and inelastic energy loss suffered by the jet multiprong collection of color charges that are resolved by medium interactions. Hence, quenching effects depend on the fluctuations of the jet substructure that are probed by the cone-size dependence of the spectrum. In this Letter, we present the first complete, analytic calculation of the inclusive R-dependent jet spectrum in PbPb collisions at LHC energies, including resummation of energy loss effects from hard, vacuumlike emissions occurring in the medium and modeling of soft energy flow and recovery at the jet cone. Both the geometry of the collision and the local medium properties, such as the temperature and fluid velocity, are given by a hydrodynamic evolution of the medium, leaving only the coupling constant in the medium as a free parameter. The calculation yields a good description of the centrality and p_{T} dependence of jet suppression for R=0.4 together with a mild cone-size dependence, which is in agreement with recent experimental results. Gauging the theoretical uncertainties, we find that the largest sensitivity resides in the leading logarithmic approximation of the phase space of resolved splittings, which can be improved systematically, while nonperturbative modeling of the soft-gluon sector is of relatively minor importance up to large cone sizes.

Jet Suppression From a Small to Intermediate to Large Radius.

We present predictions for jet suppression from small to intermediate to very large radius, for high energy jets created in heavy ion collisions at the LHC. We find that jet suppression is surprisingly independent of the anti-kT radius R, first slightly increasing as one increases R, then at larger values of R very slowly decreasing. This behavior arises from two competing effects, namely the larger energy loss of the hard jet components, which tends to increase suppression, versus the partial recovery of the lost energy due to medium response, reducing suppression.