Photon tagged correlations in heavy ion collisions

A detailed study of various two-particle correlation functions involving photons and neutral pions is presented in proton-proton and lead-lead collisions at the LHC energy. The aim is to use these correlation functions to quantify the effect of the medium (in lead-lead collisions) on the jet decay properties. The calculations are carried out at the leading order in QCD but the next-to-leading order corrections are also discussed. The competition between different production mechanisms makes the connection between the jet energy loss spectrum and the gamma-pi correlations somewhat indirect while the gamma-gamma correlations have a clearer relation to the jet fragmentation properties.Comment: 32 pages, 19 figures. Minor changes, published versio

Deciphering the properties of the medium produced in heavy ion collisions at RHIC by a pQCD analysis of quenched large p⊥p_{\perp} π0\pi^0 spectra

We discuss the question of the relevance of perturbative QCD calculations for analyzing the properties of the dense medium produced in heavy ion collisions. Up to now leading order perturbative estimates have been worked out and confronted with data for quenched large $p_{\perp}$ hadron spectra. Some of them are giving paradoxical results, contradicting the perturbative framework and leading to speculations such as the formation of a strongly interacting quark-gluon plasma. Trying to bypass some drawbacks of these leading order analysis and without performing detailed numerical investigations, we collect evidence in favour of a consistent description of quenching and of the characteristics of the produced medium within the pQCD framework.Comment: 10 pages, 3 figure

System size dependence of nuclear modification and azimuthal anisotropy of jet quenching

We investigate the system size dependence of jet-quenching by analyzing transverse momentum spectra of neutral pions in Au+Au and Cu+Cu collisions at $\sqrt{s_{\textrm{NN}}}$ =200 GeV for different centralities. The fast partons are assumed to lose energy by radiating gluons as they traverse the plasma and undergo multiple collisions. The energy loss per collision, $\epsilon$, is taken as proportional to $E$(where $E$ is the energy of the parton), proportional to $\sqrt{E}$, or a constant depending on whether the formation time of the gluon is less than the mean path, greater than the mean free path but less than the path length, or greater than the path length of the partons, respectively. NLO pQCD is used to evaluate pion production by modifying the fragmentation function to account for the energy loss. We reproduce the nuclear modification factor $R_\textrm{AA}$ by treating $\epsilon$ as the only free parameter, depending on the centrality and the mechanism of energy loss. These values are seen to explain the nuclear modification of prompt photons, caused by the energy lost by final state quarks before they fragment into photons. These also reproduce the azimuthal asymmetry of transverse momentum distribution for pions within a factor of two and for prompt photons in a fair agreement with experimental data.Comment: 26 pages, 17 figures. One more figure added. Discussion expanded. Typographical corrections done, several references added. To appear in Journal of Physics

Atomic Mass Dependence of Hadron Production in Deep Inelastic Scattering on Nuclei

Hadron production in lepton-nucleus deep inelastic scattering is studied in an absorption model. In the proposed model, the early stage of hadronization in the nuclear medium is dominated by prehadron formation and absorption, controlled by flavor-dependent formation lengths and absorption cross sections. Computations for hadron multiplicity ratios are presented and compared with the HERMES experimental data for pions, kaons, protons and antiprotons. The mass-number dependence of hadron attenuation is shown to be sensitive to the underlying hadronization dynamics. Contrary to common expectations for absorption models, a leading term proportional to A^{2/3} is found. Deviations from the leading behavior arise at large mass-numbers and large hadron fractional momenta.Comment: 30 pages, 10 figures, v2: minor changes (legend in figs 5 & 6 is added), v3: additional explanations are added, v4: Version combines v3 and the erratum hep-ph/050803

Spatial orientation in navigating agents: Modeling head-direction cells

A model that is consistent with several neurophysiological properties of biological head-direction cells is presented. The dynamics of the system is primarily controlled by idiothetic signals which determine the direction selectivity property. By means of LTP correlation learning, allothetic cues are incorporated to stabilize the direction representation over time. The interaction between allothetic and idiothetic signals to control head-direction cells is studied. Experimental results obtained by validating the model on a mobile Khepera robot are given. The neural system enables the robot to track its allocentric heading effectively

Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity

A computational model of hippocampal activity during spatial cognition and navigation tasks is presented. The spatial representation in our model of the rat hippocampus is built on-line during exploration via two processing streams. An allothetic vision-based representation is built by unsupervised Hebbian learning extracting spatio-temporal properties of the environment from visual input. An idiothetic representation is learned based on internal movement-related information provided by path integration. On the level of the hippocampus, allothetic and idiothetic representations are integrated to yield a stable representation of the environment by a population of localized overlapping CA3-CA1 place fields. The hippocampal spatial representation is used as a basis for goal-oriented spatial behavior. We focus on the neural pathway connecting the hippocampus to the nucleus accumbens. Place cells drive a population of locomotor action neurons in the nucleus accumbens. Reward-based learning is applied to map place cell activity into action cell activity. The ensemble action cell activity provides navigational maps to support spatial behavior. We present experimental results obtained with a mobile Khepera robot

Charmonium suppression in p-A collisions at RHIC

We discuss charmonium production in proton-nucleus collisions at RHIC energies under the assumption of xF and x2 scaling. We find that all the ambiguities due to energy loss are gone at this energy and therefore data will reveal the scaling law, if any. These p-A data will also be crucial to interpret nucleus-nucleus data with respect to a possible formation of a quark gluon plasma because the extrapolations for charmonium production from the present p-A data to RHIC energies, based on the two scaling laws, differ by a factor of four.Comment: 6 pages, 3 figures. New section on shadowing and energy loss, References adde

Cold nuclear matter effects on J/psi production: intrinsic and extrinsic transverse momentum effects

Cold nuclear matter effects on J/psi production in proton-nucleus and nucleus-nucleus collisions are evaluated taking into account the specific J/psi production kinematics at the partonic level, the shadowing of the initial parton distributions and the absorption in the nuclear matter. We consider two different parton processes for the c-cbar pair production: one with collinear gluons and a recoiling gluon in the final state and the other with initial gluons carrying intrinsic transverse momentum. Our results are compared to RHIC observables. The smaller values of the nuclear modification factor R_AA in the forward rapidity region (with respect to the mid rapidity region) are partially explained, therefore potentially reducing the need for recombination effects.Comment: 7 pages, 11 figures, LaTeX, uses elsarticle.cls (included).v2: version (with minor text revisions and Fig 2 and 4a modified) to appear in Phys.Lett.

Space-time evolution of hadronization

Beside its intrinsic interest for the insights it can give into color confinement, knowledge of the space-time evolution of hadronization is very important for correctly interpreting jet-quenching data in heavy ion collisions and extracting the properties of the produced medium. On the experimental side, the cleanest environment to study the space-time evolution of hadronization is semi-inclusive Deeply Inelastic Scattering on nuclear targets. On the theoretical side, 2 frameworks are presently competing to explain the observed attenuation of hadron production: quark energy loss (with hadron formation outside the nucleus) and nuclear absorption (with hadronization starting inside the nucleus). I discuss recent observables and ideas which will help to distinguish these 2 mechanisms and to measure the time scales of the hadronization process.Comment: 6 pages, 4 figures. Based on talks given at "Hot Quarks 2006", Villasimius, Italy, May 15-20, 2006, and at the "XLIV internataional winter meeting on nuclear physics", Bormio, Italy, Jan 29 - Feb 5, 2006. To appear in Eur.Phys.J.

Cognitive navigation based on non-uniform Gabor space sampling, unsupervised growing networks, and reinforcement learning

We study spatial learning and navigation for autonomous agents. A state space representation is constructed by unsupervised Hebbian learning during exploration. As a result of learning, a representation of the continuous two-dimensional (2-D) manifold in the high-dimensional input space is found. The representation consists of a population of localized overlapping place fields covering the 2-D space densely and uniformly. This space coding is comparable to the representation provided by hippocampal place cells in rats. Place fields are learned by extracting spatio-temporal properties of the environment from sensory inputs. The visual scene is modeled using the responses of modified Gabor filters placed at the nodes of a sparse Log-polar graph. Visual sensory aliasing is eliminated by taking into account self-motion signals via path integration. This solves the hidden state problem and provides a suitable representation for applying reinforcement learning in continuous space for action selection. A temporal-difference prediction scheme is used to learn sensorimotor mappings to perform goal-oriented navigation. Population vector coding is employed to interpret ensemble neural activity. The model is validated on a mobile Khepera miniature robot