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We present an in-depth study of masses and decays of excited scalar and pseudoscalar q¯q states in the Extended Linear Sigma Model (eLSM). The model also contains ground-state scalar, pseudoscalar, vector and axial-vector mesons. The main objective is to study the consequences of the hypothesis that the f0(1790) resonance, observed a decade ago by the BES Collaboration and recently by LHCb, represents an excited scalar quarkonium. In addition we also analyse the possibility that the new a0(1950) resonance, observed recently by BABAR, may also be an excited scalar state. Both hypotheses receive justification in our approach although there appears to be some tension between the simultaneous interpretation of f0(1790)/a0(1950) and pseudoscalar mesons η(1295), π(1300), η(1440) and K(1460) as excited q¯q states.
The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network’s changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network’s sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.
The crossbar H-mode (CH) cavity is an accelerating structure operated in the H21(0) mode. The robustness of the crossbar geometry allows one to realize room temperature as well as superconducting linac cavities. The shunt impedance characteristics of this structure are attractive to develop proton and heavy ion linacs in the low and medium beta range. A first room temperature eight-cell prototype has proven the feasibility of the crossbar design in terms of mechanical construction, copper plating, and cooling. An innovative rf coupling concept has been developed where two CH cavities are connected by a two gap E010-mode resonator which, at the same time, provides transverse focusing by a quadrupole triplet. The concept has been applied in the design of the new FAIR proton linac and a scaled model of the second cavity of this injector has been built and tested too. The full scale prototype is now under construction at the University of Frankfurt. In this paper, the room temperature CH cavity development as well as the general layout of the FAIR proton injector (70 MeV, 325 MHz, 70 mA) is presented and discussed.
The crossbar-H-mode (CH) structure is the first superconducting multicell drift tube cavity for the low and medium energy range operated in the H21 mode. Because of the large energy gain per cavity, which leads to high real estate gradients, it is an excellent candidate for the efficient acceleration in high power proton and ion accelerators with fixed velocity profile. A prototype cavity has been developed and tested successfully with a gradient of 7MV/m. A few new superconducting CH cavities with improved geometries for different high power applications are under development at present. One cavity (f=325 MHz, β=0.16, seven cells) is currently under construction and studied with respect to a possible upgrade option for the GSI UNILAC. Another cavity (f=217 MHz, β=0.059, 15 cells) is designed for a cw operated energy variable heavy ion linac application. Furthermore, the EUROTRANS project (European research program for the transmutation of high level nuclear waste in an accelerator driven system, 600 MeV protons, 352 MHz) is one of many possible applications for this kind of superconducting rf cavity. In this context a layout of the 17 MeV EUROTRANS injector containing four superconducting CH cavities was proposed by the Institute for Applied Physics (IAP) Frankfurt. The status of the cavity development related to the EUROTRANS injector is presented.
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.
We study the sensitivities of the directed flow in Au+Au collisions on the equation of state (EoS), employing the transport theoretical model JAM. The EoS is modified by introducing a new collision term in order to control the pressure of a system by appropriately selecting an azimuthal angle in two-body collisions according to a given EoS. It is shown that this approach is an efficient method to modify the EoS in a transport model. The beam energy dependence of the directed flow of protons is examined with two different EoS, a first-order phase transition and crossover. It is found that our approach yields quite similar results as hydrodynamical predictions on the beam energy dependence of the directed flow; Transport theory predicts a minimum in the excitation function of the slope of proton directed flow and does indeed yield negative directed flow, if the EoS with a first-order phase transition is employed. Our result strongly suggests that the highest sensitivity for the critical point can be seen in the beam energy range of 4.7 ≤√sNN≤11.5GeV.
We investigate the properties of the QCD matter across the deconfinement phase transition in the scope of the parton-hadron string dynamics (PHSD) transport approach. We present here in particular the results on the electromagnetic radiation, i.e. photon and dilepton production, in relativistic heavy-ion collisions. By comparing our calculations for the heavy-ion collisions to the available data, we determine the relative importance of the various production sources and address the possible origin of the observed strong elliptic flow v2 of direct photons. We argue that the different centrality dependence of the hadronic and partonic sources for direct photon production in nucleusnucleus collisions can be employed to shed some more light on the origin of the photon v2 “puzzle”. While the dilepton spectra at low invariant mass show in-medium effects like an enhancement from multiple baryonic resonance formation or a collisional broadening of the vector meson spectral functions, the dilepton yield at high invariant masses (above 1.1 GeV) is dominated by QGP contributions for central heavy-ion collisions at ultra-relativistic energies. This allows to have an independent view on the parton dynamics via their electromagnetic massive radiation.
I summarize recent developments in the hard-thermal-loop approach to QCD. I first discuss a finite-temperature and -density calculation of QCD thermodynamics at NNLO from the hard-thermal-loop perturbation theory. I then discuss a generalization of the hard-thermal-loop framework to the magnetic scale g2T, from which a novel non-Abelian massless mode is uncovered.
We study a random matrix model for QCD at finite density via complex Langevin dynamics. This model has a phase transition to a phase with nonzero baryon density. We study the convergence of the algorithm as a function of the quark mass and the chemical potential and focus on two main observables: the baryon density and the chiral condensate. For simulations close to the chiral limit, the algorithm has wrong convergence properties when the quark mass is in the spectral domain of the Dirac operator. A possible solution of this problem is discussed.
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.
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.
Time resolved measurements of the biased disk effect at an Electron Cyclotron Resonance Ion Source
(1999)
First results are reported from time resolved measurements of ion currents extracted from the Frankfurt 14 GHz Electron Cyclotron Resonance Ion Source with pulsed biased-disk voltage. It was found that the ion currents react promptly to changes of the bias. From the experimental results it is concluded that the biased disk effect is mainly due to improvements of the extraction conditions for the source and/or an enhanced transport of ions into the extraction area. By pulsing the disk voltage, short current pulses of highly charged ions can be generated with amplitudes significantly higher than the currents obtained in continuous mode.
A small electrostatic storage ring is the central machine of the Frankfurt Ion Storage Experiments (FIRE) which will be built at the new Stern-Gerlach Center of Frankfurt University. As a true multiuser, multipurpose facility with ion energies up to 50 keV, it will allow new methods to analyze complex many-particle systems from atoms to very large biomolecules. With envisaged storage times of some seconds and beam emittances in the order of a few mm mrad, measurements with up to 6 orders of magnitude better resolutions as compared to single-pass experiments become possible. In comparison to earlier designs, the ring lattice was modified in many details: Problems in earlier designs were related to, e.g., the detection of light particles and highly charged ions with different charge states. Therefore, the deflectors were redesigned completely, allowing a more flexible positioning of the diagnostics. Here, after an introduction to the concept of electrostatic machines, an overview of the planned FIRE is given and the ring lattice and elements are described in detail.
We report on the results on the dynamical modelling of cluster formation with the new combined PHSD+FRIGA model at Nuclotron and NICA energies. The FRIGA clusterization algorithm, which can be applied to the transport models, is based on the simulated annealing technique to obtain the most bound configuration of fragments and nucleons. The PHSD+FRIGA model is able to predict isotope yields as well as hypernucleus production. Based on present predictions of the combined model we study the possibility to detect such clusters and hypernuclei in the BM@N and MPD/NICA detectors.
The properties of matter at finite baryon densities play an important role for the astrophysics of compact stars as well as for heavy ion collisions or the description of nuclear matter. Because of the sign problem of the quark determinant, lattice QCD cannot be simulated by standard Monte Carlo at finite baryon densities. I review alternative attempts to treat dense QCD with an effective lattice theory derived by analytic strong coupling and hopping expansions, which close to the continuum is valid for heavy quarks only, but shows all qualitative features of nuclear physics emerging from QCD. In particular, the nuclear liquid gas transition and an equation of state for baryons can be calculated directly from QCD. A second effective theory based on strong coupling methods permits studies of the phase diagram in the chiral limit on coarse lattices.
The production of 77,79,85,85mKr and 77Br via the reaction Se(a, x) was investigated between Ea = 11 and 15 MeV using the activation technique. The irradiation of natural selenium targets on aluminum backings was conducted at the Physikalisch-Technische Bundesanstalt (PTB) in Braunschweig, Germany. The spectroscopic analysis of the reaction products was performed using a high-purity germanium detector located at PTB and a low energy photon spectrometer detector at the Goethe University Frankfurt, Germany. Thicktarget yields were determined. The corresponding energy-dependent production cross sections of 77,79,85,85mKr and 77Br were calculated from the thicktarget yields. Good agreement between experimental data and theoretical predictions using the TALYS-1.6 code was found.
Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij = Pji, the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric.
Criticality meets learning : criticality signatures in a self-organizing recurrent neural network
(2017)
Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions – matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model’s performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN’s spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences.
For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation can split into an initial exponential decrease and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. Both processes can be either of the same or of very different time scales. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall extent of the attractor) for exceedingly long times and remain partially predictable. Standard tests for chaos widely use inter-orbital correlations as an indicator. However, testing partially predictable chaos yields mostly ambiguous results, as this type of chaos is characterized by attractors of fractally broadened braids. For a resolution we introduce a novel 0-1 indicator for chaos based on the cross-distance scaling of pairs of initially close trajectories. This test robustly discriminates chaos, including partially predictable chaos, from laminar flow. Additionally using the finite time cross-correlation of pairs of initially close trajectories, we are able to identify laminar flow as well as strong and partially predictable chaos in a 0-1 manner solely from the properties of pairs of trajectories.
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings.
Electronic states with non-trivial topology host a number of novel phenomena with potential for revolutionizing information technology. The quantum anomalous Hall effect provides spin-polarized dissipation-free transport of electrons, while the quantum spin Hall effect in combination with superconductivity has been proposed as the basis for realizing decoherence-free quantum computing. We introduce a new strategy for realizing these effects, namely by hole and electron doping kagome lattice Mott insulators through, for instance, chemical substitution. As an example, we apply this new approach to the natural mineral herbertsmithite. We prove the feasibility of the proposed modifications by performing ab-initio density functional theory calculations and demonstrate the occurrence of the predicted effects using realistic models. Our results herald a new family of quantum anomalous Hall and quantum spin Hall insulators at affordable energy/temperature scales based on kagome lattices of transition metal ions.
Study of hard core repulsive interactions in an hadronic gas from a comparison with lattice QCD
(2016)
We study the influence of hard-core repulsive interactions within the Hadron-Resonace Gas model in comparison to first principle calculation performed on a lattice. We check the effect of a bag-like parametrization for particle eigenvolume on flavor correlators, looking for an extension of the agreement with lattice simulations up to higher temperatures, as was yet pointed out in an analysis of hadron yields measured by the ALICE experiment. Hints for a flavor depending eigenvolume are present.
It is proposed to install an experimental setup in the fixed-target hall of the Nuclotron with the final goal to perform a research program focused on the production of strange matter in heavyion collisions at beam energies between 2 and 6 A GeV. The basic setup will comprise a large acceptance dipole magnet with inner tracking detector modules based on double-sided Silicon micro-strip sensors and GEMs. The outer tracking will be based on the drift chambers and straw tube detector. Particle identification will be based on the time-of-flight measurements. This setup will be sufficient perform a comprehensive study of strangeness production in heavy-ion collisions, including multi-strange hyperons, multi-strange hypernuclei, and exotic multi-strange heavy objects. These pioneering measurements would provide the first data on the production of these particles in heavy-ion collisions at Nuclotron beam energies, and would open an avenue to explore the third (strangeness) axis of the nuclear chart. The extension of the experimental program is related with the study of in-medium effects for vector mesons decaying in hadronic modes. The studies of the NN and NA reactions for the reference is assumed.
Abstract We consider the phase structure of hadronic and hadron-quark models at finite temperature and density. The basis for the hadronic part is an extension of a flavor-SU(3) ? ? ? model. We study the effect on the phase diagram by adding additional hadronic resonances to the model. With the resulting equation of state we investigate heavy-ion c... collisions using hydrodynamical simulations. In a combined approach we include quarks and the Polyakov loop field in the calculation and study chiral symmetry restoration and the deconfinement transition.
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.
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.
Generating functionals may guide the evolution of a dynamical system and constitute a possible route for handling the complexity of neural networks as relevant for computational intelligence.We propose and explore a new objective function, which allows to obtain plasticity rules for the afferent synaptic weights. The adaption rules are Hebbian, self-limiting, and result from the minimization of the Fisher information with respect to the synaptic flux. We perform a series of simulations examining the behavior of the new learning rules in various circumstances.The vector of synaptic weights aligns with the principal direction of input activities, whenever one is present. A linear discrimination is performed when there are two or more principal directions; directions having bimodal firing-rate distributions, being characterized by a negative excess kurtosis, are preferred. We find robust performance and full homeostatic adaption of the synaptic weights results as a by-product of the synaptic flux minimization. This self-limiting behavior allows for stable online learning for arbitrary durations.The neuron acquires new information when the statistics of input activities is changed at a certain point of the simulation, showing however, a distinct resilience to unlearn previously acquired knowledge. Learning is fast when starting with randomly drawn synaptic weights and substantially slower when the synaptic weights are already fully adapted.
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.
Oscillations play a critical role in cognitive phenomena and have been observed in many brain regions. Experimental evidence indicates that classes of neurons exhibit properties that could promote oscillations, such as subthreshold resonance and electrical gap junctions. Typically, these two properties are studied separately but it is not clear which is the dominant determinant of global network rhythms. Our aim is to provide an analytical understanding of how these two effects destabilize the fluctuation-driven state, in which neurons fire irregularly, and lead to an emergence of global synchronous oscillations. Here we show how the oscillation frequency is shaped by single neuron resonance, electrical and chemical synapses.The presence of both gap junctions and subthreshold resonance are necessary for the emergence of oscillations. Our results are in agreement with several experimental observations such as network responses to oscillatory inputs and offer a much-needed conceptual link connecting a collection of disparate effects observed in networks.
A measurement of the transverse momentum spectra of jets in Pb-Pb collisions at sNN−−−√=2.76 TeV is reported. Jets are reconstructed from charged particles using the anti-kT jet algorithm with jet resolution parameters R of 0.2 and 0.3 in pseudo-rapidity |η|<0.5. The transverse momentum pT of charged particles is measured down to 0.15 GeV/c which gives access to the low pT fragments of the jet. Jets found in heavy-ion collisions are corrected event-by-event for average background density and on an inclusive basis (via unfolding) for residual background fluctuations and detector effects. A strong suppression of jet production in central events with respect to peripheral events is observed. The suppression is found to be similar to the suppression of charged hadrons, which suggests that substantial energy is radiated at angles larger than the jet resolution parameter R=0.3 considered in the analysis. The fragmentation bias introduced by selecting jets with a high pT leading particle, which rejects jets with a soft fragmentation pattern, has a similar effect on the jet yield for central and peripheral events. The ratio of jet spectra with R=0.2 and R=0.3 is found to be similar in Pb-Pb and simulated PYTHIA pp events, indicating no strong broadening of the radial jet structure in the reconstructed jets with R<0.3.
Conventional radar-based image reconstruction techniques fail when they are applied to heterogeneous breast tissue, since the underlying in-breast relative permittivity is unknown or assumed to be constant. This results in a systematic error during the process of image formation. A recent trend in microwave biomedical imaging is to extract the relative permittivity from the object under test to improve the image reconstruction quality and thereby to enhance the diagnostic assessment. In this paper, we present a novel radar-based methodology for microwave breast cancer detection in heterogeneous breast tissue integrating a 3D map of relative permittivity as a priori information. This leads to a novel image reconstruction formulation where the delay-and-sum focusing takes place in time rather than range domain. Results are shown for a heterogeneous dense (class-4) and a scattered fibroglandular (class-2) numerical breast phantom using Bristol's 31-element array configuration.
We enlarge the so-called extended linear Sigma model (eLSM) by including the charm quark according to the global U(4)r × U(4)l chiral symmetry. In the eLSM, besides scalar and pseudoscalar mesons, also vector and axial-vector mesons are present. Almost all the parameters of the model were fixed in a previous study of mesons below 2 GeV. In the extension to the four-flavor case, only three additional parameters (all of them related to the bare mass of the charm quark) appear.We compute the (OZI dominant) strong decays of open charmed mesons. The results are compatible with the experimental data, although the theoretical uncertainties are still large.
In the presence of a minimal length, physical objects cannot collapse to an infinite density, singular, matter point. In this paper, we consider the possible final stage of the gravitational collapse of "thick" matter layers. The energy momentum tensor we choose to model these shell-like objects is a proper modification of the source for "noncommutative geometry inspired," regular black holes. By using higher momenta of Gaussian distribution to localize matter at finite distance from the origin, we obtain new solutions of the Einstein equation which smoothly interpolates between Minkowski's geometry near the center of the shell and Schwarzschild’s spacetime far away from the matter layer. The metric is curvature singularity free. Black hole type solutions exist only for "heavy" shells; that is, M >= Me, where Me is the mass of the extremal configuration. We determine the Hawking temperature and a modified area law taking into account the extended nature of the source.
In the framework of an interference setup in which only two outcomes are possible (such as in the case of a Mach–Zehnder interferometer), we discuss in a simple and pedagogical way the difference between a standard, unitary quantum mechanical evolution and the existence of a real collapse of the wavefunction. This is a central and not-yet resolved question of quantum mechanics and indeed of quantum field theory as well. Moreover, we also present the Elitzur–Vaidman bomb, the delayed choice experiment, and the effect of decoherence. In the end, we propose two simple experiments to visualize decoherence and to test the role of an entangled particle.
EUROTRANS is a European research program for the transmutation of high level nuclear waste in an accelerator-driven system (ADS). As proposed, the driver linac needs to deliver a 2.5–4 mA, 600 MeV continuous-wave (CW) proton beam and later a 20 mA, 800 MeV one to the spallation target in the prototype-scale and industrial-scale demonstration phases, respectively. This paper is focusing on the conceptual studies performed with respect to the 17 MeV injector. First, the special beam dynamics strategies and methods, which have been developed and applied to design a current-variable injector up to 30 mA for allowing an easy upgrade without additional R&D costs, will be introduced. Then the error study made for evaluating the tolerance limits of the designed injector will be presented as well.
Focus on quantum efficiency
(2014)
Technologies which convert light into energy, and vice versa, rely on complex, microscopic transport processes in the condensed phase, which obey the laws of quantum mechanics, but hitherto lack systematic analysis and modeling. Given our much improved understanding of multicomponent, disordered, highly structured, open quantum systems, this ‘focus on’ collection collects cuttingedge research on theoretical and experimental aspects of quantum transport in truly complex systems as defined, e.g., by the macromolecular functional complexes at the heart of photosynthesis, by organic quantum wires, or even photovoltaic devices. To what extent microscopic quantum coherence effects can (be made to) impact on macroscopic transport behavior is an equally challenging and controversial question, and this "focus on" collection provides a setting for the present state of affairs, as well as for the "quantum opportunities" on the horizon.
We study the equilibrium properties of strongly-interacting infinite parton-hadron matter, characterized by the transport coefficients such as shear and bulk viscosity and electric conductivity, and the non-equilibrium dynamics of heavy-ion collisions within the Parton-Hadron-String Dynamics (PHSD) transport approach, which incorporates explicit partonic degrees of freedom in terms of strongly interacting quasiparticles (quarks and gluons) in line with an equation of state from lattice QCD as well as the dynamical hadronization and hadronic collision dynamics in the final reaction phase. We discuss in particular the possible origin for the strong elliptic flow v2 of direct photons observed at RHIC energies.
Tumour cells show a varying susceptibility to radiation damage as a function of the current cell cycle phase. While this sensitivity is averaged out in an unperturbed tumour due to unsynchronised cell cycle progression, external stimuli such as radiation or drug doses can induce a resynchronisation of the cell cycle and consequently induce a collective development of radiosensitivity in tumours. Although this effect has been regularly described in experiments it is currently not exploited in clinical practice and thus a large potential for optimisation is missed. We present an agent-based model for three-dimensional tumour spheroid growth which has been combined with an irradiation damage and kinetics model. We predict the dynamic response of the overall tumour radiosensitivity to delivered radiation doses and describe corresponding time windows of increased or decreased radiation sensitivity. The degree of cell cycle resynchronisation in response to radiation delivery was identified as a main determinant of the transient periods of low and high radiosensitivity enhancement. A range of selected clinical fractionation schemes is examined and new triggered schedules are tested which aim to maximise the effect of the radiation-induced sensitivity enhancement. We find that the cell cycle resynchronisation can yield a strong increase in therapy effectiveness, if employed correctly. While the individual timing of sensitive periods will depend on the exact cell and radiation types, enhancement is a universal effect which is present in every tumour and accordingly should be the target of experimental investigation. Experimental observables which can be assessed non-invasively and with high spatio-temporal resolution have to be connected to the radiosensitivity enhancement in order to allow for a possible tumour-specific design of highly efficient treatment schedules based on induced cell cycle synchronisation.
Author Summary: The sensitivity of a cell to a dose of radiation is largely affected by its current position within the cell cycle. While under normal circumstances progression through the cell cycle will be asynchronous in a tumour mass, external influences such as chemo- or radiotherapy can induce a synchronisation. Such a common progression of the inner clock of the cancer cells results in the critical dependence on the effectiveness of any drug or radiation dose on a suitable timing for its administration. We analyse the exact evolution of the radiosensitivity of a sample tumour spheroid in a computer model, which enables us to predict time windows of decreased or increased radiosensitivity. Fractionated radiotherapy schedules can be tailored in order to avoid periods of high resistance and exploit the induced radiosensitivity for an increase in therapy efficiency. We show that the cell cycle effects can drastically alter the outcome of fractionated irradiation schedules in a spheroid cell system. By using the correct observables and continuous monitoring, the cell cycle sensitivity effects have the potential to be integrated into treatment planing of the future and thus to be employed for a better outcome in clinical cancer therapies.
System size dependence of hadron production properties is discussed within the Wounded Nucleon Model and the Statistical Model in the grand canonical, canonical and micro-canonical formulations. Similarities and differences between predictions of the models related to the treatment of conservation laws are exposed. A need for models which would combine a hydrodynamicallike expansion with conservation laws obeyed in individual collisions is stressed.
Coupling local, slowly adapting variables to an attractor network allows to destabilize all attractors, turning them into attractor ruins. The resulting attractor relict network may show ongoing autonomous latching dynamics. We propose to use two generating functionals for the construction of attractor relict networks, a Hopfield energy functional generating a neural attractor network and a functional based on information-theoretical principles, encoding the information content of the neural firing statistics, which induces latching transition from one transiently stable attractor ruin to the next. We investigate the influence of stress, in terms of conflicting optimization targets, on the resulting dynamics. Objective function stress is absent when the target level for the mean of neural activities is identical for the two generating functionals and the resulting latching dynamics is then found to be regular. Objective function stress is present when the respective target activity levels differ, inducing intermittent bursting latching dynamics.
Which are the factors underlying human information production on a global level? In order to gain an insight into this question we study a corpus of 252–633 mil. publicly available data files on the Internet corresponding to an overall storage volume of 284–675 Terabytes. Analyzing the file size distribution for several distinct data types we find indications that the neuropsychological capacity of the human brain to process and record information may constitute the dominant limiting factor for the overall growth of globally stored information, with real-world economic constraints having only a negligible influence. This supposition draws support from the observation that the files size distributions follow a power law for data without a time component, like images, and a log-normal distribution for multimedia files, for which time is a defining qualia.
Author summary: The generation of new information is limited by two key factors, by the incurring economic costs and by the capacity of the human brain to process and store data and information; the controlling agent needs to retain an overall understanding even when data is generated by semiautomatic processes. These processes are reflected in the statistical properties of the data files publicly available on the Internet. Collecting a corpus of 252–633 mil. files we find that the statistics of the file size distribution are consistent with the supposition that data production on a global level is shaped and limited by the neuropsychological information processing capacity of the brain, with economic and hardware constraints having a negligible influence.
Abstract: Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.
Author Summary: The statistics of our visual world is dominated by occlusions. Almost every image processed by our brain consists of mutually occluding objects, animals and plants. Our visual cortex is optimized through evolution and throughout our lifespan for such stimuli. Yet, the standard computational models of primary visual processing do not consider occlusions. In this study, we ask what effects visual occlusions may have on predicted response properties of simple cells which are the first cortical processing units for images. Our results suggest that recently observed differences between experiments and predictions of the standard simple cell models can be attributed to occlusions. The most significant consequence of occlusions is the prediction of many cells sensitive to center-surround stimuli. Experimentally, large quantities of such cells are observed since new techniques (reverse correlation) are used. Without occlusions, they are only obtained for specific settings and none of the seminal studies (sparse coding, ICA) predicted such fields. In contrast, the new type of response naturally emerges as soon as occlusions are considered. In comparison with recent in vivo experiments we find that occlusive models are consistent with the high percentages of center-surround simple cells observed in macaque monkeys, ferrets and mice.
Part of Focus on High Energy Density Physics. In this paper, we present a novel theoretical approach, which allows the study of nonequilibrium dynamics of both electrons and atoms/ions within free-electron laser excited semiconductors at femtosecond time scales. The approach consists of the Monte-Carlo method treating photoabsorption, high-energy-electron and core-hole kinetics and relaxation processes. Low-energy electrons localized within the valence and conduction bands of the target are treated with a temperature equation, including source terms, defined by the exchange of energy and particles with high-energy electrons and atoms. We follow the atomic motion with the molecular dynamics method on the changing potential energy surface. The changes of the potential energy surface and of the electron band structure are calculated at each time step with the help of the tight-binding method. Such a combination of methods enables investigation of nonequilibrium structural changes within materials under extreme ultraviolet (XUV) femtosecond irradiation. Our analysis performed for diamond irradiated with an XUV femtosecond laser pulse predicts for the first time in this wavelength regime the nonthermal phase transition from diamond to graphite. Similar to the case of visible light irradiation, this transition takes place within a few tens of femtoseconds and is caused by changes of the interatomic potential induced by ultrafast electronic excitations. It thus occurs well before the heating stimulated by electron–phonon coupling starts to play a role. This allows us to conclude that this transition is nonthermal and represents a general mechanism of the response of solids to ultrafast electron excitations.
In non-hadronic axion models, which have a tree-level axion-electron interaction, the Sun produces a strong axion flux by bremsstrahlung, Compton scattering, and axiorecombination, the "BCA processes." Based on a new calculation of this flux, including for the first time axio-recombination, we derive limits on the axion-electron Yukawa coupling gae and axion-photon interaction strength ga using the CAST phase-I data (vacuum phase). For ma <~ 10 meV/c2 we find ga gae < 8.1 × 10−23 GeV−1 at 95% CL. We stress that a next-generation axion helioscope such as the proposed IAXO could push this sensitivity into a range beyond stellar energy-loss limits and test the hypothesis that white-dwarf cooling is dominated by axion emission.
Supersurface electron scattering, i.e., electron energy losses and associated deflections in vacuum above the surface of a medium, is shown to contribute significantly to electron spectra. We have obtained experimental verification (in absolute units) of theoretical predictions that the angular distribution of the supersurface backscattering probability exhibits strong oscillations which are anticorrelated with the generalized Ramsauer-Townsend minima in the backscattering probability. We have investigated 500-eV electron backscattering from an Au surface for an incidence angle of 70° and scattering angles between 37° and 165°. After removing the contribution of supersurface scattering from the experimental data, the resulting angular and energy distribution agrees with the Landau-Goudsmit-Saunderson (LGS) theory, which was proposed about 60 years ago, while the raw data are anticorrelated with LGS theory. This result implies that supersurface scattering is an essential phenomenon for quantitative understanding of electron spectra.
In the study of trapped two-component Bose gases, a widely used dynamical protocol is to start from the ground state of a one-component condensate and then switch half the atoms into another hyperfine state. The slightly different intra-component and inter-component interactions can then lead to highly non-trivial dynamics, especially in the density mismatch between the two components, commonly referred to as 'spin' density. We study and classify the possible subsequent dynamics, over a wide variety of parameters spanned by the trap strength and by the inter- to intra-component interaction ratio. A stability analysis suited to the trapped situation provides us with a framework to explain the various types of dynamics in different regimes.
The way we perceive the visual world depends crucially on the state of the observer. In the present study we show that what we are holding in working memory (WM) can bias the way we perceive ambiguous structure from motion stimuli. Holding in memory the percept of an unambiguously rotating sphere influenced the perceived direction of motion of an ambiguously rotating sphere presented shortly thereafter. In particular, we found a systematic difference between congruent dominance periods where the perceived direction of the ambiguous stimulus corresponded to the direction of the unambiguous one and incongruent dominance periods. Congruent dominance periods were more frequent when participants memorized the speed of the unambiguous sphere for delayed discrimination than when they performed an immediate judgment on a change in its speed. The analysis of dominance time-course showed that a sustained tendency to perceive the same direction of motion as the prior stimulus emerged only in the WM condition, whereas in the attention condition perceptual dominance dropped to chance levels at the end of the trial. The results are explained in terms of a direct involvement of early visual areas in the active representation of visual motion in WM.