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The recent discovery of binary neutron star mergers has opened a new and exciting venue of research into hot and dense strongly interacting matter. For the first time, this elusive state of matter, described by the theory of quantum chromo dynamics, can be studied in two very different environments. On the macroscopic scale, in the collisions of neutron stars; and on the microscopic scale, in collisions of heavy ions at particle collider facilities. We will discuss the conditions that are created in these mergers and the corresponding high energy nuclear collisions. This includes the properties of quantum chromo dynamics matter, that is, the expected equation of state as well as expected chemical and thermodynamic properties of this exotic matter. To explore this matter in the laboratory, a new research prospect is available at the Facility for Antiproton and Ion Research, FAIR. The new facility is being constructed adjacent to the existing accelerator complex of the GSI Helmholtz Centre for Heavy Ion Research at Darmstadt/Germany, expanding the research goals and technical possibilities substantially. The worldwide unique accelerator and experimental facilities of FAIR will open the way for a broad spectrum of unprecedented research supplying a variety of experiments in hadron, nuclear, atomic, and plasma physics as well as biomedical and material science, which will be briefly described.
The brain is a large complex system which is remarkably good at maintaining stability under a wide range of input patterns and intensities. In addition, such a stable dynamical state is able to sustain essential functions, including the encoding of information about the external environment and storing memories. In order to succeed in these challenging tasks, neural circuits rely on a variety of plasticity mechanisms that act as self-organizational rules and regulate their dynamics. Based on toy models of self-organized criticality, this stable state has been proposed to be a phase transition point, poised between distinct types of unhealthy dynamics, in what has become known as the critical brain hypothesis. It is not yet known, however, if and how self-organization could drive biological neural networks towards a critical state while maintaining or improving their learning and memory functions.
Here, we investigate the emergence of criticality signatures in the form of neuronal avalanches due to self-organizational plasticity rules in a recurrent neural network. We show that power-law distributions of events, widely observed in experiments, arise from a combination of biologically inspired synaptic and homeostatic plasticity but are highly dependent on the external drive. Additionally, we describe how learning abilities and fading memory emerge and are improved by the same self-organizational processes. We finally propose an application of these enhanced functions, focusing on sequence and simple language learning tasks.
Taken together, our results suggest that the same self-organizational processes can be responsible for improving the brain’s spatio-temporal learning abilities and memory capacity while also giving rise to criticality signatures under particular input conditions, thus proposing a novel link between such abilities and neuronal avalanches. Although criticality was not verified, the detailed study of self-organization towards critical dynamics further elucidates its potential emergence and functions in the brain.
As the successor of the EUROTRANS project, the MAX project is aiming to continue the R&D effects for a European Accelerator-Driven System and to bring the conceptual design to reality. The layout of the driver linac for MAX will follow the reference design made for the XT-ADS phase of the EUROTRANS project. For the injector part, new design strategies and approaches, e.g. half resonant frequency, half transition-energy between the RFQ and the CH-DTL, and using the 4-rod RFQ structure instead of the originally proposed 4-vane RFQ, have been conceived and studied to reach a more reliable CW operation at reduced costs. In this paper, the design and simulation results of the MAX injector are presented.
Bottomonium states are key probes for experimental studies of the quark-gluon plasma (QGP) created in high-energy nuclear collisions. Theoretical models of bottomonium productions in high-energy nuclear collisions rely on the in-medium interactions between the bottom and antibottom quarks, which can be characterized by real (VR(T, r)) and imaginary (VI(T, r)) potentials, as functions of temperature and spatial separation. Recently, the masses and thermal widths of up to 3S and 2P bottomonium states in QGP were calculated using lattice quantum chromodynamics (LQCD). Starting from these LQCD results and through a novel application of deep neural network (DNN), here, we obtain model-independent results for VR(T, r) and VI(T, r). The temperature dependence of VR(T, r) was found to be very mild between T ≈ 0 − 330 MeV. Meanwhile, VI(T, r) shows rapid increase with T and r, which is much larger than the perturbation theory based expectations.
We discuss recent applications of the partonic perturbative QCD based cascade model BAMPS with focus on heavy-ion phenomenology in the hard and soft momentum range. First, the elliptic flow and suppression of charm and bottom quarks are studied at LHC energies. Thereafter, we compare in a detailed study the standard Gunion-Bertsch approximation of the matrix elements for inelastic processes to the exact results in leading order perturbative QCD. Since a disagreement is found, we propose an improved Gunion-Bertsch matrix element, which agrees with the exact result in all phase space regions.
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.
From the colour glass condensate to filamentation: systematics of classical Yang–Mills theory
(2019)
The non-equilibrium early time evolution of an ultra-relativistic heavy ion collision is often described by classical lattice Yang–Mills theory, starting from the colour glass condensate (CGC) effective theory with an anisotropic energy momentum tensor as initial condition. In this work we investigate the systematics associated with such studies and their dependence on various model parameters (IR, UV cutoffs and the amplitude of quantum fluctuations) which are not yet fixed by experiment. We perform calculations for SU() and SU(), both in a static box and in an expanding geometry. Generally, the dependence on model parameters is found to be much larger than that on technical parameters like the number of colours, boundary conditions or the lattice spacing. In a static box, all setups lead to isotropisation through chromo-Weibel instabilities, which is illustrated by the accompanying filamentation of the energy density. However, the associated time scale depends strongly on the model parameters and in all cases is longer than the phenomenologically expected one. In the expanding system, no isotropisation is observed for any parameter choice. We show how investigations at fixed initial energy density can be used to better constrain some of the model parameters.
The non-equilibrium quantum field dynamics is usually described in the closed-time-path formalism. The initial state correlations are introduced into the generating functional by non-local source terms. We propose a functional approach to the Dyson-Schwinger equation, which treats the non-local and local source terms in the same way. In this approach, the generating functional is formulated for the connected Green functions and one-particle-irreducible vertices. The great advantages of our approach over the widely used two-particle-irreducible method are that it is much simpler and that it is easy to implement the procedure in a computer program to automatically generate the Feynman diagrams for a given process. The method is then applied to a pure gluon plasma to derive the gauge-covariant transport equation from the Dyson-Schwinger equation in the background covariant gauge. We discuss the structure of the kinetic equation and show its relationship with the classical one. We derive the gauge-covariant collision part and present an approximation in the vicinity of equilibrium. The role of the non-local source kernel in the non-equilibrium system is discussed in the context of a free scalar field. PACS numbers: 12.38.Mh, 25.75.-q, 24.85.+p, 11.15.Kc
Cryo-electron tomography (CET) is a unique technique to visualize biological objects under near-to-native conditions at near-atomic resolution. CET provides three-dimensional (3D) snapshots of the cellular proteome, in which the spatial relations between macromolecular complexes in their near native cellular context can be explored. Due to the limitation of the electron dose applicable on biological samples, the achievable resolution of a tomogram is restricted to a few nanometers, higher resolution can be achieved by averaging of structures occurring in multiples. For this purpose, computational techniques such as template matching, sub-tomogram averaging and classification are essential for a meaningful processing of CET data.
This thesis introduces the techniques of template matching and sub-tomogram averaging and their applications on real biological data sets. Subsequently, the problem of reference bias, which restricts the applicability of those techniques, is addressed. Two methods that estimate the reference bias in Fourier and real space are demonstrated. The real space method, which we have named the “M-free” score, provides a reliable estimation of the reference bias, which gives access to the reliability of the template matching or sub-tomogram averaging process. Thus, the “M-free” score makes those approaches more applicable to structural biology. Furthermore, a classification algorithm based on Neural Networks (NN) called “KerDenSOM3D” is introduced, which is implemented in 3D and compensates for the missing-wedge. This approach helps extracting different structural states of macromolecular complexes or increasing the class purity of data sets by eliminating outliers. A comprehensive comparison with other classification methods shows superior performance of KerDenSOM3D.
The present thesis is primarily concerned with the application of the functional renormalization group (FRG) to spin systems. In the first part, we study the critical regime close to the Berezinskii-Kosterlitz-Thouless (BKT) transition in several systems. Our starting point is the dual-vortex representation of the two-dimensional XY model, which is obtained by applying a dual transformation to the Villain model. In order to deal with the integer-valued field corresponding to the dual vortices, we apply the lattice FRG formalism developed by Machado and Dupuis [Phys. Rev. E 82, 041128 (2010)]. Using a Litim regulator in momentum space with the initial condition of isolated lattice sites, we then recover the Kosterlitz-Thouless renormalization group equations for the rescaled vortex fugacity and the dimensionless temperature. In addition to our previously published approach based on the vertex expansion [Phys. Rev. E 96, 042107 (2017)], we also present an alternative derivation within the derivative expansion. We then generalize our approach to the O(2) model and to the strongly anisotropic XXZ model, which enables us to show that weak amplitude fluctuations as well as weak out-of-plane fluctuations do not change the universal properties of the BKT transition.
In the second part of this thesis, we develop a new FRG approach to quantum spin systems. In contrast to previous works, our spin functional renormalization group (SFRG) does not rely on a mapping to bosonic or fermionic fields, but instead deals directly with the spin operators. Most importantly, we show that the generating functional of the irreducible vertices obeys an exact renormalization group equation, which resembles the Wetterich equation of a bosonic system. As a consequence, the non-trivial structure of the su(2) algebra is fully taken into account by the initial condition of the renormalization group flow. Our method is motivated by the spin-diagrammatic approach to quantum spin system that was developed more than half a century ago in a seminal work by Vaks, Larkin, and Pikin (VLP) [Sov. Phys. JETP 26, 188 (1968)]. By embedding their ideas in the language of the modern renormalization group, we avoid the complicated diagrammatic rules while at the same time allowing for novel approximation schemes. As a demonstration, we explicitly show how VLP's results for the leading corrections to the free energy and to the longitudinal polarization function of a ferromagnetic Heisenberg model can be recovered within the SFRG. Furthermore, we apply our method to the spin-S Ising model as well as to the spin-S quantum Heisenberg model, which allows us to calculate the critical temperature for both a ferromagnetic and an antiferromagnetic exchange interaction. Finally, we present a new hybrid formulation of the SFRG, which combines features of both the pure and the Hubbard-Stratonovich SFRG that were published recently [Phys. Rev. B 99, 060403(R) (2019)].