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Recent STAR data for the directed flow of protons, antiprotons and charged pions obtained within the beam energy scan program are analyzed within the Parton-Hadron-String-Dynamics (PHSD/HSD) transport models. Both versions of the kinetic approach are used to clarify the role of partonic degrees of freedom. The PHSD results, simulating a partonic phase and its coexistence with a hadronic one, are roughly consistent with the STAR data. Generally, the semi-qualitative agreement between the measured data and model results supports the idea of a crossover type of quark-hadron transition which softens the nuclear EoS but shows no indication of a first-order phase transition. Furthermore, the directed flow of kaons and antikaons is evaluated in the PHSD/HSD approachesfrom √sNN ≈ 3 - 200 GeV which shows a high sensitivity to hadronic potentials in the FAIR/NICA energy regime √sNN ≤ 8 GeV.
In the initial stage of relativistic heavy-ion collisions, strong magnetic fields appear due to the large velocity of the colliding charges. The evolution of these fields appears as a novel and intriguing feature in the fluid-dynamical description of heavy-ion collisions. In this work, we study analytically the one-dimensional, longitudinally boost-invariant motion of an ideal fluid in the presence of a transverse magnetic field. Interestingly, we find that, in the limit of ideal magnetohydrodynamics, i.e., for infinite conductivity, and irrespective of the strength of the initial magnetization, the decay of the fluid energy density e with proper time τ is the same as for the time-honoured “Bjorken flow” without magnetic field. Furthermore, when the magnetic field is assumed to decay , where a is an arbitrary number, two classes of analytic solutions can be found depending on whether a is larger or smaller than one. In summary, the analytic solutions presented here highlight that the Bjorken flow is far more general than formerly thought. These solutions can serve both to gain insight on the dynamics of heavy-ion collisions in the presence of strong magnetic fields and as testbeds for numerical codes.
The high collision energies reached at the LHC lead to significant production yields of light (anti-)nuclei and (hyper-)nuclei in proton–proton, proton–lead and, in particular, lead–lead collisions. The excellent particle identification capabilities of the ALICE apparatus, based on the specific energy loss in the Time Projection Chamber and the velocity information in the Time-Of-Flight detector, allow for the detection of these rarely produced particles. Further, the Inner Tracking System gives the possibility to separate primary nuclei from those coming from weak decay of heavier systems. One example of such a weak decay is the measurement of the (anti-)hypertriton decay to 3He + π− (3H̅e̅ + π+). The aforementioned capabilities of the ALICE apparatus offer the unique opportunity to search for exotica, like the bound state of a Λ and a neutron which would decay into a deuteron and a pion, or the bound state of two Λ’s. Results on the production of stable nuclei in Pb–Pb collisions at √sNN = 2.76 TeV are presented, and compared with thermal model predictions. We further present the current status of the searches, by their upper limits on the production yields, and compare the results to thermal and coalescence model expectations.
Ein Laserblitz von unvorstellbarer Intensität pulverisiert im Labor ein Molekül. Wachsam zeichnen die Instrumente die Flugbahn und Geschwindigkeit jedes Bruchstücks auf. Physiker gewinnen daraus hochpräzise Informationen über die Molekülstruktur. Auch links- und rechtshändige Formen lassen sich unterscheiden.
The pA system is typically regarded in heavy ion collisions as a “cold” nuclear matter environment and thought to isolate and identify initial state effects due to the presence of multiple nucleons in the incoming nucleus. Moreover, pA collisions bridge the gap between peripheral AA collisions and the pp baseline to create a more complete understanding of underlying production mechanisms and how they evolve with multiplicity. Recent measurements at both RHIC and the LHC provide an indication, however, that the “cold” nuclear matter picture may be somewhat naïve.
Recent LHC results from the 2013 p–Pb run at √sNN = 5.02 TeV will be discussed.
We present an effective model for timing-dependent synaptic plasticity (STDP) in terms of two interacting traces, corresponding to the fraction of activated NMDA receptors and the concentration in the dendritic spine of the postsynaptic neuron. This model intends to bridge the worlds of existing simplistic phenomenological rules and highly detailed models, thus constituting a practical tool for the study of the interplay of neural activity and synaptic plasticity in extended spiking neural networks. For isolated pairs of pre- and postsynaptic spikes, the standard pairwise STDP rule is reproduced, with appropriate parameters determining the respective weights and timescales for the causal and the anticausal contributions. The model contains otherwise only three free parameters, which can be adjusted to reproduce triplet nonlinearities in hippocampal culture and cortical slices. We also investigate the transition from time-dependent to rate-dependent plasticity occurring for both correlated and uncorrelated spike patterns.
The Fisher information constitutes a natural measure for the sensitivity of a probability distribution with respect to a set of parameters. An implementation of the stationarity principle for synaptic learning in terms of the Fisher information results in a Hebbian self-limiting learning rule for synaptic plasticity. In the present work, we study the dependence of the solutions to this rule in terms of the moments of the input probability distribution and find a preference for non-Gaussian directions, making it a suitable candidate for independent component analysis (ICA). We confirm in a numerical experiment that a neuron trained under these rules is able to find the independent components in the non-linear bars problem. The specific form of the plasticity rule depends on the transfer function used, becoming a simple cubic polynomial of the membrane potential for the case of the rescaled error function. The cubic learning rule is also an excellent approximation for other transfer functions, as the standard sigmoidal, and can be used to show analytically that the proposed plasticity rules are selective for directions in the space of presynaptic neural activities characterized by a negative excess kurtosis.
Thermal dilepton radiation from the hot fireballs created in high-energy heavy-ion collisions provides unique insights into the properties of the produced medium. We first show how the predictions of hadronic many-body theory for a melting ρ meson, coupled with quark–gluon plasma emission utilizing a modern lattice-QCD based equation of state, yield a quantitative description of dilepton spectra in heavy-ion collisions at the SPS and the RHIC beam energy scan program. We utilize these results to systematically extract the excess yields and their invariant-mass spectral slopes to predict the excitation function of fireball lifetimes and (early) temperatures, respectively. We thereby demonstrate that future measurements of these quantities can yield unprecedented information on basic fireball properties. Specifically, our predictions quantify the relation between the measured and maximal fireball temperature, and the proportionality of excess yield and total lifetime. This information can serve as a “caloric” curve to search for a first-order QCD phase transition, and to detect non-monotonous lifetime variations possibly related to critical phenomena.