Latest ALICE results of photon and jet measurements

Highly energetic jets and photons are complementary probes for the kinematics and the topology of nuclear collisions. Jets are collimated sprays of charged and neutral particles, which are produced in the fragmentation of hard scattered partons in an early stage of the collision. While traversing the medium formed in nuclear collisions, they lose energy and therefore carry information about the interaction of partons with the medium. The jet substructure is particularly interesting to learn about in-medium modification of the jets and several observables exists to probe it. In contrast to jets, photons are created in all collision stages. There are prompt photons from the initial collision, thermal photons produced in the medium, and decay- and fragmentation photons from later collision stages. Photons escape the medium essentially unaffected after their creation. This article presents recent ALICE results on jet substructure and direct photon measurements in pp, p-Pb and Pb-Pb collisions.Comment: 4 pages, 7 figures, Rencontres de Moriond proceeding

Measurement of inclusive jet spectra in pp, p-Pb, and Pb-Pb collisions with the ALICE detector

Highly energetic jets are sensitive probes for the kinematic properties and the topology of high energy hadron collisions. Jets are collimated sprays of charged and neutral particles, which are produced in fragmentation of hard scattered partons from an early stage of the collision. In ALICE, jets have been measured in pp, p-Pb, and Pb-Pb collisions at several collision energies. While analyses of Pb-Pb events unveil properties of the hot and dense medium formed in heavy-ion collisions, pp and p-Pb collisions can shed light on hadronization and cold nuclear matter effects in jet production. Additionally, pp and p-Pb serve as a baseline for disentangling hot and cold nuclear matter effects. A possible modification of the initial state is tested in p-Pb analyses. For the extraction of a jet signal, the exact evaluation of the background from the underlying event is an especially important ingredient. Due to the different nature of underlying events, each collision system requires a different analysis technique for removing the effect of the background on the jet sample. The focus of this publication is on the ALICE measurements of nuclear modification factors connecting p-Pb and Pb-Pb events to pp collisions. Furthermore, the radial jet structure is explored by comparing jet spectra reconstructed with different resolution parameters.Comment: 6 pages, 9 figures, HPT2014 proceeding

Machine and deep learning techniques in heavy-ion collisions with ALICE

Over the last years, machine learning tools have been successfully applied to a wealth of problems in high-energy physics. A typical example is the classification of physics objects. Supervised machine learning methods allow for significant improvements in classification problems by taking into account observable correlations and by learning the optimal selection from examples, e.g. from Monte Carlo simulations. Even more promising is the usage of deep learning techniques. Methods like deep convolutional networks might be able to catch features from low-level parameters that are not exploited by default cut-based methods. These ideas could be particularly beneficial for measurements in heavy-ion collisions, because of the very large multiplicities. Indeed, machine learning methods potentially perform much better in systems with a large number of degrees of freedom compared to cut-based methods. Moreover, many key heavy-ion observables are most interesting at low transverse momentum where the underlying event is dominant and the signal-to-noise ratio is quite low. In this work, recent developments of machine- and deep learning applications in heavy-ion collisions with ALICE will be presented, with focus on a deep learning-based b-jet tagging approach and the measurement of low-mass dielectrons. While the b-jet tagger is based on a mixture of shallow fully-connected and deep convolutional networks, the low-mass dielectron measurement uses gradient boosting and shallow neural networks. Both methods are very promising compared to default cut-based methods.Comment: 7 pages, 5 figures, EPS HEP 2017 proceeding

Centrality dependence of charged jets in p-Pb collisions at sNN=5.02\sqrt{s_\mathrm{NN}} = 5.02 TeV measured with the ALICE detector

Highly energetic jets are sensitive probes for the kinematics and the topology of nuclear collisions. Jets are collimated sprays of charged and neutral particles, which are produced in the fragmentation of hard scattered partons in an early stage of the collision. The measurement of jet spectra in p-Pb collisions provides an important way of quantifying the effects of cold nuclear matter in the initial state on jet production, fragmentation, and hadronization. Unlike in Pb-Pb collisions, strong hot nuclear matter effects - e.g. from quark-gluon plasma formation - are not expected to occur in p-Pb collisions. Hence, cold nuclear matter effects can be investigated in isolation. The impact of cold nuclear matter effects on charged jet spectra is expected to depend on the event centrality. Higher event centralities are principally connected to a higher probability for an interaction of proton and lead-nucleus and therefore also for a possible nuclear modification. This article is the conference proceeding of a talk, in which centrality-dependent properties of charged jets in p-Pb measured by ALICE were shown for the first time. The focus is here on the fully corrected jet production cross sections and the nuclear modification factors. Additionally, the jet radial structure is explored by comparing jet spectra reconstructed with different resolution parameters.Comment: 8 pages, 4 figures, Bormio2015 proceeding

Machine Learning based jet momentum reconstruction in Pb-Pb collisions measured with the ALICE detector

The precise reconstruction of jet transverse momenta in heavy-ion collisions is a challenging task. A major obstacle is the large number of uncorrelated (mainly) low-$p_\mathrm{T}$ particles overlaying the jets. Strong region-to-region fluctuations of this background complicate the jet measurement and lead to significant uncertainties. We developed a novel approach to correct jet momenta (or energies) for the underlying background in heavy-ion collisions. The approach allows the measurement of jets down to extremely low transverse momenta and for large resolution $R$ by making use of common Machine Learning techniques to estimate the jet transverse momentum based on several parameters. In this conference proceeding, we will present transverse momentum spectra and nuclear modification factors of track-based jets that have been corrected by this Machine Learning approach and comparisons to published results where possible. The analysis was performed on Pb-Pb collisions at $\sqrt{s_\mathrm{NN}} = 5.02$ TeV recorded with the ALICE detector and measures jets with large resolution parameters for low momenta, unprecedented thus far in data on heavy-ion collisions.Comment: Proceedings of EPS-HEP2019 conference, 10-17 July, 201

Hypersensitivity and chaos signatures in the quantum baker's maps

Classical chaotic systems are distinguished by their sensitive dependence on initial conditions. The absence of this property in quantum systems has lead to a number of proposals for perturbation-based characterizations of quantum chaos, including linear growth of entropy, exponential decay of fidelity, and hypersensitivity to perturbation. All of these accurately predict chaos in the classical limit, but it is not clear that they behave the same far from the classical realm. We investigate the dynamics of a family of quantizations of the baker's map, which range from a highly entangling unitary transformation to an essentially trivial shift map. Linear entropy growth and fidelity decay are exhibited by this entire family of maps, but hypersensitivity distinguishes between the simple dynamics of the trivial shift map and the more complicated dynamics of the other quantizations. This conclusion is supported by an analytical argument for short times and numerical evidence at later times.Comment: 32 pages, 6 figure

Centrality evolution of the charged-particle pseudorapidity density over a broad pseudorapidity range in Pb-Pb collisions at root s(NN)=2.76TeV

Peer reviewe

Charged jets in p–Pb collisions at sNN\sqrt{s_{NN}} = 5.02 TeV measured with the ALICE detector

Highly energetic jets are sensitive probes for the kinematics and the topology of nuclear collisions. Jets are collimated sprays of charged and neutral particles, which are produced in the fragmentation of hard scattered partons in the early stage of the collision. The measurement of nuclear modification of charged jet spectra in p–Pb collisions provides an important way of quantifying the effects of cold nuclear matter in the initial state on jet production, fragmentation, and hadronization. Unlike in Pb–Pb collisions, modifications of jet production due to hot nuclear matter effects are not expected to occur in p–Pb collisions. Therefore, measurements of nuclear modifications in charged jet spectra in p–Pb collisions (commonly known as $R_{pPb}$) can be used to isolate and quantify cold nuclear matter effects. Potential nuclear effects are expected to be more pronounced in more central p–Pb collisions due to a higher probability of an interaction between the proton and the lead-nucleus. To measure the centrality dependence of charged jet spectra, it is crucial to use a reliable definition of event centrality, which ALICE developed utilizing the Zero-Degree Calorimeter (ZDC)

SCOPE: An Environment for Continuous Improvement Teams in Virtual Corporations

: A continuous improvement team is a group of people who work together on the same project and are committed to continuous improvement of their work processes. In order to support continuous improvement teams in a virtual corporation, a comprehensive system is needed to support integrated collaborative work and collaborative learning processes. In this paper, the SCOPE system is presented, which provides support for the definition, modification and execution of session-based collaborative processes for continuous improvement teams. 1 Introduction A virtual corporation is a temporary network of independent operating units such as creative designers, manufacturers, suppliers, customers, and other experts in marketing and finance linked by interactive multimedia networks to share skills, production facilities, resources, to decrease costs and to increase access to each other's markets. In virtual corporations, the definition of a task is continually changing, and its product is a ..