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We study various fluctuation and correlation signals of the deconfined state using a dynamical recombination approach (quark Molecular Dynamics, qMD). We analyse charge ratio fluctuations, charge transfer fluctuations and baryon-strangeness correlations as a function of the center of mass energy with a set of central Pb+Pb/Au+Au events from AGS energies on (Elab = 4 AGeV) up to the highest RHIC energy available (V sNN = 200 GeV) and as a function of time with a set of central Au+Au qMD events at V sNN = 200 GeV with and without applying our hadronization procedure. For all studied quantities, the results start from values compatible with a weakly coupled QGP in the early stage and end with values compatible with the hadronic result in the final state. We show that the loss of the signal occurs at the same time as hadronization and trace it back to the dynamical recombination process implemented in our model.
Starting from a classical picture of shear viscosity we construct a steady velocity gradient in the partonic cascade BAMPS. Using the Navier-Stokes-equation we calculate the shear viscosity coefficient. For elastic isotropic scatterings we find a very good agreement with the analytic values. For both elastic and inelastic scatterings with pQCD cross sections we find good agreement with previously published calculations.
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models. Here we introduce SORN, a self-organizing recurrent network. It combines three distinct forms of local plasticity to learn spatio-temporal patterns in its input while maintaining its dynamics in a healthy regime suitable for learning. The SORN learns to encode information in the form of trajectories through its high-dimensional state space reminiscent of recent biological findings on cortical coding. All three forms of plasticity are shown to be essential for the network's success. Keywords: synaptic plasticity, intrinsic plasticity, recurrent neural networks, reservoir computing, time series prediction
In this paper we discuss experimental evidence related to the structure and origin of the bosonic spectral function alpha 2F (omega) in high-temperature superconducting (HTSC) cuprates at and near optimal doping. Global properties of alpha 2F (omega), such as number and positions of peaks, are extracted by combining optics, neutron scattering, ARPES and tunnelling measurements. These methods give evidence for strong electron-phonon interaction (EPI) with 1<lambda ep <~ 3.5 in cuprates near optimal doping. We clarify how these results are in favor of the modified Migdal-Eliashberg (ME) theory for HTSC cuprates near optimal doping. In Section 2 we discuss theoretical ingredients—such as strong EPI, strong correlations—which are necessary to explain the mechanism of d-wave pairing in optimally doped cuprates. These comprise the ME theory for EPI in strongly correlated systems which give rise to the forward scattering peak. The latter is supported by the long-range part of EPI due to the weakly screened Madelung interaction in the ionic-metallic structure of layered HTSC cuprates. In this approach EPI is responsible for the strength of pairing while the residual Coulomb interaction and spin fluctuations trigger the d-wave pairing.
In this proceeding the emergence of a composite, adjoint-scalar field as an average over (trivial holonomy) calorons and anti-calorons is reviewed. This composite field acts as a background field to the dynamics of perturbative gluons, to which it is coupled via an effective, gauge invariant Lagrangian valid for temperatures above the deconfinement phase transition. Moreover a Higgs mechanism is induced by the composite field: two gluons acquire a quasi-particle thermal mass. On the phenomenological side the composite field acts as a bag pressure which shows a linear dependence on the temperature. As a result the linear rise with temperature of the trace anomaly is obtained and is compared to recent lattice studies.
Short-term memory requires the coordination of sub-processes like encoding, retention, retrieval and comparison of stored material to subsequent input. Neuronal oscillations have an inherent time structure, can effectively coordinate synaptic integration of large neuron populations and could therefore organize and integrate distributed sub-processes in time and space. We observed field potential oscillations (14–95 Hz) in ventral prefrontal cortex of monkeys performing a visual memory task. Stimulus-selective and performance-dependent oscillations occurred simultaneously at 65–95 Hz and 14–50 Hz, the latter being phase-locked throughout memory maintenance. We propose that prefrontal oscillatory activity may be instrumental for the dynamical integration of local and global neuronal processes underlying short-term memory.
Clathrates are candidate materials for thermoelectric applications because of a number of unique properties. The clathrate I phases in the Ba-Ni-Ge ternary system allow controlled variation of the charge carrier concentration by adjusting the Ni content. Depending on the Ni content, the physical properties vary from metal-like to insulator-like and show a transition from p-type to n-type conduction. Here we present first results on the characterization of millimeter-sized single crystals grown by the Bridgman technique. Single crystals with a composition of Ba8Ni3.5Ge42.1h0.4 show metallic behavior (dp/dT > 0) albeit with high resistivity at room temperature [p (300 K) = 1 mOhm cm]. The charge carrier concentration at 300 K, as determined from Hall-effect measurements, is 2.3 e-/unit cell. The dimensionless thermoelectric figure of merit estimated at 680 K is ZT ~ 0.2. Keywords Clathrates - thermoelectric material - intermetallic compound - nickel
Den Geheimnissen der Materie auf der Spur : neue Denkfabrik für physikalische Grundlagenforschung
(2009)
Bei Darmstadt entsteht FAIR, eines der größten internationalen Forschungszentren für Physik. Durch das von der Landesregierung geförderte Exzellenzzentrum »HIC for FAIR« erhält die Forschung in Hessen die einmalige Chance, sich direkt an globaler Spitzenforschung zu beteiligen: auf der Suche nach den letzten Geheimnissen der Materie.
The surface tension sigma and the surface density thickness t of nuclear matter have been calculated in the Fermi-gas model, the nucleons moving in a self-made shell model potential with a realistic slope and velocity dependence ( parameters alpha and beta ). One gets the experimental values for sigma and t with alpha and beta agreeing with earlier data.
Theoretical studies in the shell model have led to the conclusion that the shape dependence of the liquid-drop part of the semi-empirical mass formula of the Weizsaecker-Bethe type should contain terms proportional to the volume, the surface, and the mean-total curvature of the surface of the drop, respectively. Now the surface tension beta_e and the curvature tension gamma_e are fitted to the experimentally known fission barriers of 35 nuclei. Furthermore, the parameters of the liquid-drop part of the mass formula are roughly fitted to the ground-state masses of about 600 beta-stable nuclei. For the elementary radius r_e, the value 1.123 fm ( determined by Elton ) is used. As a result, gamma_e should be in the range 6-8 MeV, with the value 6.8 MeV being the most probable, thus beta_e=17.85 MeV. For sufficiently large values of the curvature tension ( e.g. gamma_e=13.4 MeV ), a small double-hump fission barrier occurs in the region of Ra.
Die Reform der Lehrerausbildung spielt in der aktuellen bildungspolitischen Diskussion eine wichtige Rolle. In der Auseinandersetzung um fachdidaktische Ausbildungsstandards und Kerncurricula werden von den Studierenden, neben fachlichen Fähigkeiten, Reflexions-, Kommunikations- und unterrichtsbezogene Handlungskompetenzen gefordert. In der Physik-lehrerausbildung der universitären Phase müssen Lernumgebungen zur Schulung dieser Kom-petenzen häufig erst noch geschaffen werden. Aus diesem Grund wird seit dem Wintersemester 2002/03 der Universität Frankfurt/M. eine Seminarreihe mit dem Charakter einer Lernwerkstatt angeboten, in der die Studierenden selbstorganisiert Unterrichtsmaterialien entwickeln. Von den Zielen, der Durchführung und den Ergebnissen dieses Projekts wird berichtet und ein Seminarkonzept in Kombination mit den schulpraktischen Studien vorgestellt.
Background: In this interdisciplinary project, the biological effects of heavy ions are compared to those of X-rays using tissue slice culture preparations from rodents and humans. Advantages of this biological model are the conservation of an organotypic environment and the independency from genetic immortalization strategies used to generate cell lines. Its open access allows easy treatment and observation via live-imaging microscopy. Materials and methods: Rat brains and human brain tumor tissue are cut into 300 micro m thick tissue slices. These slices are cultivated using a membrane-based culture system and kept in an incubator at 37°C until treatment. The slices are treated with X-rays at the radiation facility of the University Hospital in Frankfurt at doses of up to 40 Gy. The heavy ion irradiations were performed at the UNILAC facility at GSI with different ions of 11.4 A MeV and fluences ranging from 0.5–10 x 106 particles/cm². Using 3D-confocal microscopy, cell-death and immune cell activation of the irradiated slices are analyzed. Planning of the irradiation experiments is done with simulation programs developed at GSI and FIAS. Results: After receiving a single application of either X-rays or heavy ions, slices were kept in culture for up to 9d post irradiation. DNA damage was visualized using gamma H2AXstaining. Here, a dose-dependent increase and time-dependent decrease could clearly be observed for the X-ray irradiation. Slices irradiated with heavy ions showed less gamma H2AX-positive cells distributed evenly throughout the slice, even though particles were calculated to penetrate only 90–100 micro m into the slice. Conclusions: Single irradiations of brain tissue, even at high doses of 40 Gy, will result neither in tissue damage visible on a macroscopic level nor necrosis. This is in line with the view that the brain is highly radio-resistant. However, DNA damage can be detected very well in tissue slices using gamma H2AX-immuno staining. Thus, slice cultures are an excellent tool to study radiation-induced damage and repair mechanisms in living tissues.
Recent results of the NA49 collaboration are presented. Transverse mass spectra as well as total multiplicities of identified particles are discussed. The study of their evolution from AGS over SPS to the highest RHIC energy reveals a couple of interesting features. These include a sudden change in the energy dependence of the mt-spectra and of the yields of strange hadrons around 30A GeV. Additionally, new results on particle production at high-pt for Pb+Pb collsions at 158A GeV, as well as on the v2 of L, are discussed.
We study the line shapes of radiative φ-decays with a direct coupling of the φ meson to the f0(980) and a0(980) scalar mesons. The latter couple via derivative interactions to π0π0 and π0η, respectively. Although the kaon-loop mechanism is usually regarded as the dominant mechanism in radiative φ decays, here we test a different possibility: we set the kaon-loop to zero and we fit the theoretical curves to the data by retaining only the direct coupling. Remarkably, satisfactory fits can be achieved, mainly due to the effects of derivative interactions of scalar with pseudoscalar mesons.
Poster presentation: The brain is autonomously active and this self-sustained neural activity is in general modulated, but not driven, by the sensory input data stream [1,2]. Traditionally one has regarded this eigendynamics as resulting from inter-modular recurrent neural activity [3]. Understanding the basic modules for cognitive computation is, in this view, the primary focus of research and the overall neural dynamics would be determined by the the topology of the intermodular pathways. Here we examine an alternative point of view, asking whether certain aspects of the neural eigendynamics have a central functional role for overall cognitive computation [4,5]. Transiently stable neural activity is regularly observed on the cognitive time-scale of 80–100 ms, with indications that neural competition [6] plays an important role in the selection of the transiently stable neural ensembles [7], also denoted winning coalitions [8]. We report on a theory approach which implements these two principles, transient-state dynamics and neural competition, in terms of an associative neural network with clique encoding [9]. A cognitive system [10] with a non-trivial internal eigendynamics has two seemingly contrasting tasks to fulfill. The internal processes need to be regular and not chaotic on one side, but sensitive to the afferent sensory stimuli on the other side. We show, that these two contrasting demands can be reconciled within our approach based on competitive transient-state dynamics, when allowing the sensory stimuli to modulate the competition for the next winning coalition. By testing the system with the bars problem, we find an emerging cognitive capability. Only based on the two basic architectural principles, neural competition and transient-state dynamics, with no explicit algorithmic encoding, the system performs on its own a non-linear independent component analysis of input data stream. The system has rudimentary biological features. All learning is local Hebbian-style, unsupervised and online. It exhibits an ever-ongoing eigendynamics and at no time is the state or the value of synaptic strengths reset or the system restarted; there is no separation between training and performance. We believe that this kind of approach – cognitive computation with autonomously active neural networks – to be an emerging field, relevant both for system neuroscience and synthetic cognitive systems.
We explain how fluctuations of ratios can constrain and falsify the statistical model of particle production in heavy ion collisions, using K/p fluctuations as an example. We define an observable capable of determining which statistical model, if any, governs freeze-out in ultrarelativistic heavy ion collisions. We calculate this observable for K/p fluctuations, and show that it should be the same for RHIC and LHC energies, as well as independent of centrality, if the Grand-Canonical statistical model is an appropriate description and chemical equilibrium applies. We describe variations of this scaling for deviations from this scenario, such as light quark chemical non-equilibrium, strange quark over-saturation and local conservation (canonical ensemble) for strange quarks. We also introduce a similar observable capable, together with the published K*/K measurement, of ascertaining if an interacting hadron gas phase governs the system between thermal and chemical freeze-out, and of ascertaining its duration and impact on hadronic chemistry.
Zellulare Nichtlineare Netzwerke (CNN) wurden 1988 von Chua und Yang (Chua und Yang, 1988) eingeführt. Diese Netzwerke sind dadurch gekennzeichnet, dass eine Zelle, die die kleinste Einheit eines CNN darstellt, nur mit Zellen innerhalb einer bestimmten Umgebung verbunden ist. üblicherweise sind Art und Stärke der Wechselwirkung zwischen zwei Zellen eines CNN translationsinvariant, d.h. sie hängen nur von der relativen Lage beider Zellen zueinander ab. Im Vordergrund aktueller Arbeiten stehen auf derartigen Netzwerken basierende schaltungstechnische Realisierungen mit bis zu 176x144 Zellen, die eine direkte Verbindung zu zweidimensionalen optischen Sensor-Anordnungen aufweisen. Über einen separaten Speicherbereich können die Zellkopplungen eines Netzwerks verändert werden, wodurch eine adaptive Verarbeitung von mehrdimensionalen Sensorsignalen ermöglicht wird. Das kürzlich vorgestellte so genannte EyeRis System (Anafocus Ltd.) enthält zusätzlich noch einen Standardprozessor und stellt (bei einer Größe vergleichbar mit der einer Kreditkarte) daher ein vollständiges superschnelles System zur Informationsverarbeitung dar. In diesem Beitrag sollen, nach einem kurzen Überblick über die Eigenschaften von CNN, aktuelle Realisierungen und exemplarisch eine neuere eigene Anwendung vorgestellt und besprochen werden.
We calculate low-energymeson decay processes and pion-pion scattering lengths in a two-flavour linear sigma model with global chiral symmetry, exploring the scenario in which the scalar mesons f0(600) and a0(980) are assumed to be ¯qq states.