Refine
Year of publication
Document Type
- Article (1902) (remove)
Has Fulltext
- yes (1902) (remove)
Is part of the Bibliography
- no (1902) (remove)
Keywords
- Heavy Ion Experiments (20)
- heavy ion collisions (16)
- BESIII (15)
- LHC (15)
- Kollisionen schwerer Ionen (14)
- Hadron-Hadron Scattering (11)
- Hadron-Hadron scattering (experiments) (11)
- e +-e − Experiments (11)
- Relativistic heavy-ion collisions (10)
- Branching fraction (9)
Institute
- Physik (1902) (remove)
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.