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We introduce a novel technique that utilizes a physics-driven deep learning method to reconstruct the dense matter equation of state from neutron star observables, particularly the masses and radii. The proposed framework involves two neural networks: one to optimize the EoS using Automatic Differentiation in the unsupervised learning scheme; and a pre-trained network to solve the Tolman–Oppenheimer–Volkoff (TOV) equations. The gradient-based optimization process incorporates a Bayesian picture into the proposed framework. The reconstructed EoS is proven to be consistent with the results from conventional methods. Furthermore, the resulting tidal deformation is in agreement with the limits obtained from the gravitational wave event, GW170817.
Using an advanced version of the hadron resonance gas model we have found several remarkable irregularities at chemical freeze-out. The most prominent of them are two sets of highly correlated quasi-plateaus in the collision energy dependence of the entropy per baryon, total pion number per baryon, and thermal pion number per baryon which we found at center of mass energies 3.6-4.9 GeV and 7.6-10 GeV. The low energy set of quasi-plateaus was predicted a long time ago. On the basis of the generalized shockadiabat model we demonstrate that the low energy correlated quasi-plateaus give evidence for the anomalous thermodynamic properties of the mixed phase at its boundary to the quark-gluon plasma. The question is whether the high energy correlated quasi-plateaus are also related to some kind of mixed phase. In order to answer this question we employ the results of a systematic meta-analysis of the quality of data description of 10 existing event generators of nucleus-nucleus collisions in the range of center of mass collision energies from 3.1 GeV to 17.3 GeV. These generators are divided into two groups: the first group includes the generators which account for the quark-gluon plasma formation during nuclear collisions, while the second group includes the generators which do not assume the quark-gluon plasma formation in such collisions. Comparing the quality of data description of more than a hundred of different data sets of strange hadrons by these two groups of generators, we find two regions of the equal quality of data description which are located at the center of mass collision energies 4.3-4.9 GeV and 10.-13.5 GeV. These two regions of equal quality of data description we interpret as regions of the hadron-quark-gluon mixed phase formation. Such a conclusion is strongly supported by the irregularities in the collision energy dependence of the experimental ratios of the Lambda hyperon number per proton and positive kaon number per Lambda hyperon. Although at the moment it is unclear, whether these regions belong to the same mixed phase or not, there are arguments that the most probable collision energy range to probe the QCD phase diagram (tri)critical endpoint is 12-14 GeV.
In the framework of the so-called extended linear sigma model (eLSM), we include a pseudoscalar glueball with a mass of 2.6 GeV (as predicted by Lattice-QCD simulations) and we compute the two- and three-body decays into scalar and pseudoscalar mesons. This study is relevant for the future PANDA experiment at the FAIR facility. As a second step, we extend the eLSM by including the charm quark according to the global U(4)R × U(4)L chiral symmetry. We compute the masses, weak decay constants and strong decay widths of open charmed mesons. The precise description of the decays of open charmed states is important for the CBM experiment at FAIR.
The relativistic method of moments is one of the most successful approaches to extract second order viscous hydrodynamics from a kinetic underlying background. The equations can be systematically improved to higher order, and they have already shown a fast convergence to the kinetic results. In order to generalize the method we introduced long range effects in the form of effective (medium dependent) masses and gauge (coherent) fields. The most straightforward generalization of the hydrodynamic expansion is problematic at higher order. Instead of introducing an additional set of approximations, we propose to rewrite the series in terms of moments resumming the contributions of infinite non-hydrodynamics modes. The resulting equations are are consistent with hydrodynamics and well defined at all order. We tested the new approximation against the exact solutions of the Maxwell-Boltzmann-Vlasov equations in (0 + 1)-dimensions, finding a fast and stable convergence to the exact results.
We explore the parameter space of the two-flavor thermal quark–meson model and its Polyakov loop-extended version under the influence of a constant external magnetic field B. We investigate the behavior of the pseudo critical temperature for chiral symmetry breaking taking into account the likely dependence of two parameters on the magnetic field: the Yukawa quark–meson coupling and the parameter T0 of the Polyakov loop potential. Under the constraints that magnetic catalysis is realized at zero temperature and the chiral transition at B=0 is a crossover, we find that the quark–meson model leads to thermal magnetic catalysis for the whole allowed parameter space, in contrast to the present picture stemming from lattice QCD.
We study simulated animats in terms of wheeled robots with the most simple neural controller possible – a single neuron per actuator. The system is fully self-organized in the sense that the controlling neuron receives uniquely the actual angle of the wheel as an input. Non-trivial locomotion results in structured environments, with the robot determining autonomously the direction of movement (time-reversal symmetry is spontaneously broken). Our controller, which mimics the mechanism used to transmit power in steam locomotives, abstracts from the body plan of the animat, working without problems also in the presence of noise and for chains of individual two-wheeled cars. Being fully compliant our controller may be also used, in the spirit of morphological computation, as a basic unit for higher-level evolutionary algorithms.
We predict the formation of highly dense baryon-rich resonance matter in Au+Au collisions at AGS energies. The final pion yields show observable signs for resonance matter. The Delta1232 resonance is predicted to be the dominant source for pions of small transverse momenta. Rescattering e ects consecutive excitation and deexcitation of Delta's lead to a long apparent life- time (> 10 fm/c) and rather large volumina (several 100 fm3) of the Delta-matter state. Heavier baryon resonances prove to be crucial for reaction dynamics and particle production at AGS.
This paper explores the many interesting implications for oscillator design, with optimized phase-noise performance, deriving from a newly proposed model based on the concept of oscillator conjugacy. For the case of 2-D (planar) oscillators, the model prominently predicts that only circuits producing a perfectly symmetric steady-state can have zero amplitude-to-phase (AM-PM) noise conversion, a so-called zero-state. Simulations on standard industry oscillator circuits verify all model predictions and, however, also show that these circuit classes cannot attain zero-states except in special limit-cases which are not practically relevant. Guided by the newly acquired design rules, we describe the synthesis of a novel 2-D reduced-order LC oscillator circuit which achieves several zero-states while operating at realistic output power levels. The potential future application of this developed theoretical framework for implementation of numerical algorithms aimed at optimizing oscillator phase-noise performance is briefly discussed.
We investigate the well-known vector state ψ(4040) in the frame-work of a quantum field theoretical model. In particular, we study its spectral function and search for the pole(s) in the complex plane. Quite interestingly, the spectral function has a non-standard shape and two poles are present. The role of the meson-meson quantum loops (in particular DD* ones) is crucial and could also explain the not yet conformed “state” Y(4008).
Recently the Universal Linear Accelerator (UNILAC) serves as a powerful high duty factor (25%) heavy ion beam accelerator for the ambitious experiment program at GSI. Beam time availability for SHE (Super Heavy Element)-research will be decreased due to the limitation of the UNILAC providing Uranium beams with an extremely high peak current for FAIR simultaneously. To keep the GSI-SHE program competitive on a high level and even beyond, a standalone superconducting continuous wave (100% duty factor) LINAC in combination with the upgraded GSI High Charge State injector is envisaged. In preparation for this, the first LINAC section (financed by HIM and GSI) will be tested with beam in 2017, demonstrating the future experimental capabilities. Further on the construction of an extended cryo module comprising two shorter Crossbar-H cavities is foreseen to test until end of 2017. As a final R&D step towards an entire LINAC three advanced cryo modules, each comprising two CH cavities, should be built until 2019, serving for first user experiments at the Coulomb barrier.
It is widely believed that chiral symmetry is spontaneously broken at zero temperature in the strong coupling limit of staggered fermions, for any number of colors and flavors. Using Monte Carlo simulations, we show that this conventional wisdom, based on a mean-field analysis, is wrong. For sufficiently many fundamental flavors, chiral symmetry is restored via a bulk, first-order transition. This chirally symmetric phase appears to be analytically connected with the expected conformal window of manyflavor continuum QCD. We perform simulations in the chirally symmetric phase at zero quark mass for various system sizes L, and measure the torelon mass and the Dirac spectrum. We find that all observables scale with L, which is hence the only infrared length scale. Thus, the strong-coupling chirally restored phase appears as a convenient laboratory to study IR-conformality. Finally, we present a conjecture for the phase diagram of lattice QCD as a function of the bare coupling and the number of quark flavors.
The temporal development of macroobservables is described within a correlation-functionformalism. The results are exact for a certain class of initial ensembles. The same problem is discussed with the help of the linear-response-formalism. The results agree under certain conditions which should be fulfilled for macroobservables.
This paper introduces a new methodology for the fabrication of strain-sensor elements for MEMS and NEMS applications based on the tunneling effect in nano-granular metals. The strain-sensor elements are prepared by the maskless lithography technique of focused electron-beam-induced deposition (FEBID) employing the precursor trimethylmethylcyclopentadienyl platinum [MeCpPt(Me)3]. We use a cantilever-based deflection technique to determine the sensitivity (gauge factor) of the sensor element. We find that its sensitivity depends on the electrical conductivity and can be continuously tuned, either by the thickness of the deposit or by electron-beam irradiation leading to a distinct maximum in the sensitivity. This maximum finds a theoretical rationale in recent advances in the understanding of electronic charge transport in nano-granular metals.
Das Gehirn ist die wohl komplexeste Struktur auf Erden, die der Mensch erforscht. Es besteht aus einem riesigen Netzwerk von Nervenzellen, welches in der Lage ist eingehende sensorische Informationen zu verarbeiten um daraus eine sinnvolle Repräsentation der Umgebung zu erstellen. Außerdem koordiniert es die Aktionen des Organismus um mit der Umgebung zu interagieren. Das Gehirn hat die bemerkenswerte Fähigkeit sowohl Informationen zu speichern als auch sich ständig an ändernde Bedingungen anzupassen, und zwar über die gesamte Lebensdauer. Dies ist essentiell für Mensch oder Tier um sich zu entwickeln und zu lernen. Die Grundlage für diesen lebenslangen Lernprozess ist die Plastizität des Gehirns, welche das riesige Netzwerk von Neuronen ständig anpasst und neu verbindet. Die Veränderungen an den synaptischen Verbindungen und der intrinsischen Erregbarkeit jedes Neurons finden durch selbstorganisierte Mechanismen statt und optimieren das Verhalten des Organismus als Ganzes. Das Phänomen der neuronalen Plastizität beschäftigt die Neurowissenschaften und anderen Disziplinen bereits über mehrere Jahrzehnte. Dabei beschreibt die intrinsische Plastizität die ständige Anpassung der Erregbarkeit eines Neurons um einen ausbalancierten, homöostatischen Arbeitsbereich zu gewährleisten. Aber besonders die synaptische Plastizität, welche die Änderungen in der Stärke bestehender Verbindungen bezeichnet, wurde unter vielen verschiedenen Bedingungen erforscht und erwies sich mit jeder neuen Studie als immer komplexer. Sie wird durch ein komplexes Zusammenspiel von biophysikalischen Mechanismen induziert und hängt von verschiedenen Faktoren wie der Frequenz der Aktionspotentiale, deren Timing und dem Membranpotential ab und zeigt außerdem eine metaplastische Abhängigkeit von vergangenen Ereignissen. Letztlich beeinflusst die synaptische Plastizität die Signalverarbeitung und Berechnung einzelner Neuronen und der neuronalen Netzwerke.
Der Schwerpunkt dieser Arbeit ist es das Verständnis der biologischen Mechanismen und deren Folgen, die zu den beobachteten Plastizitätsphänomene führen, durch eine stärker vereinheitlichte Theorie voranzutreiben.Dazu stelle ich zwei funktionale Ziele für neuronale Plastizität auf, leite Lernregeln aus diesen ab und analysiere deren Konsequenzen und Vorhersagen.
Kapitel 3 untersucht die Unterscheidbarkeit der Populationsaktivität in Netzwerken als funktionales Ziel für neuronale Plastizität. Die Hypothese ist dabei, dass gerade in rekurrenten aber auch in vorwärtsgekoppelten Netzwerken die Populationsaktivität als Repräsentation der Eingangssignale optimiert werden kann, wenn ähnliche Eingangssignale eine möglichst unterschiedliche Repräsentation haben und dadurch für die nachfolgende Verarbeitung besser unterscheidbar sind. Das funktionale Ziel ist daher diese Unterscheidbarkeit durch Veränderungen an den Verbindungsstärke und der Erregbarkeit der Neuronen mithilfe von lokalen selbst-organisierten Lernregeln zu maximieren. Aus diesem funktionale Ziel lassen sich eine Reihe von Standard-Lernenregeln für künstliche neuronale Netze gemeinsam abzuleiten.
Kapitel 4 wendet einen ähnlichen funktionalen Ansatz auf ein komplexeres, biophysikalisches Neuronenmodell an. Das Ziel ist eine spärliche, stark asymmetrische Verteilung der synaptischen Stärke, wie sie auch bereits mehrfach experimentell gefunden wurde, durch lokale, synaptische Lernregeln zu maximieren. Aus diesem funktionalen Ansatz können alle wichtigen Phänomene der synaptischen Plastizität erklärt werden. Simulationen der Lernregel in einem realistischen Neuronmodell mit voller Morphologie erklären die Daten von timing-, raten- und spannungsabhängigen Plastizitätsprotokollen. Die Lernregel hat auch eine intrinsische Abhängigkeit von der Position der Synapse, welche mit den experimentellen Ergebnissen übereinstimmt. Darüber hinaus kann die Lernregel ohne zusätzliche Annahmen metaplastische Phänomene erklären. Dabei sagt der Ansatz eine neue Form der Metaplastizität voraus, welche die timing-abhängige Plastizität beeinflusst. Die formulierte Lernregel führt zu zwei neuartigen Vereinheitlichungen für synaptische Plastizität: Erstens zeigt sie, dass die verschiedenen Phänomene der synaptischen Plastizität als Folge eines einzigen funktionalen Ziels verstanden werden können. Und zweitens überbrückt der Ansatz die Lücke zwischen der funktionalen und mechanistische Beschreibungsweise. Das vorgeschlagene funktionale Ziel führt zu einer Lernregel mit biophysikalischer Formulierung, welche mit etablierten Theorien der biologischen Mechanismen in Verbindung gebracht werden kann. Außerdem kann das Ziel einer spärlichen Verteilung der synaptischen Stärke als Beitrag zu einer energieeffizienten synaptischen Signalübertragung und optimierten Codierung interpretiert werden.
We have developed a versatile software package for the simulation of di-electron production in pp and dp collisions at moderate beam kinetic energies (1-2GeV). Particular attention has been paid to incorporate different descriptions of the Dalitz decay Δ rightarrow Ne + e - via a common interface. In addition, suitable parameterizations for the virtual bremsstrahlung process NN rightarrow NNe + e - based on one-boson exchange models have been implemented. Such simulation tools with high flexibility of the framework are important for the interpretation of the di-electron data taken with the HADES spectrometer and demonstrates the wide applicability within the field of nuclear and hadronic physics.