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Institute
- Physik (352) (remove)
Mixing and magnetic fields in asymptotic giant branch stars in the framework of FRUITY models
(2021)
In the last few years, the modeling of asymptotic giant branch (AGB) stars has been much investigated, both focusing on nucleosynthesis and stellar evolution aspects. Recent advances in the input physics required for stellar computations made it possible to construct more accurate evolutionary models, which are an essential tool to interpret the wealth of available observational and nucleosynthetic data. Motivated by such improvements, the FUNS stellar evolutionary code has been updated. Nonetheless, mixing processes occurring in AGB stars’ interiors are currently not well-understood. This is especially true for the physical mechanism leading to the formation of the 13C pocket, the major neutron source in low-mass AGB stars. In this regard, post-processing s-process models assuming that partial mixing of protons is induced by magneto-hydrodynamics processes were shown to reproduce many observations. Such mixing prescriptions have now been implemented in the FUNS code to compute stellar models with fully coupled nucleosynthesis. Here, we review the new generation of FRUITY models that include the effects of mixing triggered by magnetic fields by comparing theoretical findings with observational constraints available either from the isotopic analysis of trace-heavy elements in presolar grains or from carbon AGB stars and Galactic open clusters.
In quantum scattering processes between two particles, aspects characterizing the strong and Coulomb forces can be observed in kinematic distributions of the particle pairs. The sensitivity to the interaction potential reaches a maximum at low relative momentum and vanishing distance between the two particles. Ultrarelativistic heavy-ion collisions at the LHC provide an abundant source of many hadron species and can be employed as a measurement method of scattering parameters that is complementary to scattering experiments. This study confirms that momentum correlations of particles produced in Pb–Pb collisions at the LHC provide an accurate measurement of kaon–proton scattering parameters at low relative momentum, allowing precise access to the K−p→K−p process. This work also validates the femtoscopic measurement in ultrarelativistic heavy-ion collisions as an alternative to scattering experiments and a complementary tool to the study of exotic atoms with comparable precision. In this work, the first femtoscopic measurement of momentum correlations of K−p(K+p‾) and K+p(K−p‾) pairs in Pb–Pb collisions at centre-of-mass energy per nucleon pair of sNN=5.02 TeV registered by the ALICE experiment is reported. The components of the K−p complex scattering length are extracted and found to be ℜf0=−0.91±0.03(stat)−0.03+0.17(syst) and ℑf0=0.92±0.05(stat)−0.33+0.12(syst). The results are compared with chiral effective field theory predictions as well as with existing data from dedicated scattering and exotic kaonic atom experiments.
Vibrational energy transfer (VET) is essential for protein function. It is responsible for efficient energy dissipation in reaction sites, and has been linked to pathways of allosteric communication. While it is understood that VET occurs via backbone as well as via non-covalent contacts, little is known about the competition of these two transport channels, which determines the VET pathways. To tackle this problem, we equipped the β-hairpin fold of a tryptophan zipper with pairs of non-canonical amino acids, one serving as a VET injector and one as a VET sensor in a femtosecond pump probe experiment. Accompanying extensive non-equilibrium molecular dynamics simulations combined with a master equation analysis unravel the VET pathways. Our joint experimental/computational endeavor reveals the efficiency of backbone vs. contact transport, showing that even if cutting short backbone stretches of only 3 to 4 amino acids in a protein, hydrogen bonds are the dominant VET pathway.
Experimental and theoretical studies of fluctuations in nucleus-nucleus interactions at high energies have started to play a major role in understanding of the concept of strong interactions. The elaborated procedures have been developed to disentangle different processes happening during nucleus-nucleus collisions. The fluctuations caused by a variation of the number of nucleons which participated in a collision are frequently considered the unwanted one. The methods to reduce the impact of these fluctuations in fixed-target experiments are reviewed and tested. They can be of key importance in the following ongoing fixed-target heavy-ion experiments: NA61/SHINE at the CERN SPS, STAR-FXT at the BNL RHIC, BMN at JINR Nuclotron, HADES at the GSI SIS18 and in future experiments such as NA60+ at the CERN SPS, CBM at the FAIR SIS100, JHITS at J-PARC-HI MR.
We review the properties of the strongly interacting quark-gluon plasma (QGP) at finite temperature T and baryon chemical potential µB as created in heavy-ion collisions at ultrarelativistic energies. The description of the strongly interacting (non-perturbative) QGP in equilibrium is based on the effective propagators and couplings from the Dynamical QuasiParticle Model (DQPM) that is matched to reproduce the equation-of-state of the partonic system above the deconfinement temperature Tc from lattice QCD. Based on a microscopic transport description of heavy-ion collisions, we discuss which observables are sensitive to the QGP creation and its properties.
A deep convolutional neural network (CNN) is developed to study symmetry energy (Esym(ρ)) effects by learning the mapping between the symmetry energy and the two-dimensional (transverse momentum and rapidity) distributions of protons and neutrons in heavy-ion collisions. Supervised training is performed with labeled data-set from the ultrarelativistic quantum molecular dynamics (UrQMD) model simulation. It is found that, by using proton spectra on event-by-event basis as input, the accuracy for classifying the soft and stiff Esym(ρ) is about 60% due to large event-by-event fluctuations, while by setting event-summed proton spectra as input, the classification accuracy increases to 98%. The accuracies for 5-label (5 different Esym(ρ)) classification task are about 58% and 72% by using proton and neutron spectra, respectively. For the regression task, the mean absolute errors (MAE) which measure the average magnitude of the absolute differences between the predicted and actual L (the slope parameter of Esym(ρ)) are about 20.4 and 14.8 MeV by using proton and neutron spectra, respectively. Fingerprints of the density-dependent nuclear symmetry energy on the transverse momentum and rapidity distributions of protons and neutrons can be identified by convolutional neural network algorithm.
The deuteron coalescence parameter 𝐵2 in proton+proton and nucleus+nucleus collisions in the energy range of √s N N = 900–7000 GeV for proton + proton and √s N N = 2–2760 GeV for nucleus + nucleus collisions is analyzed with the Ultrarelativistic Quantum Molecular Dynamics (UrQMD) transport model, supplemented by an event-by-event phase space coalescence model for deuteron and anti-deuteron production. The results are compared to data by the E866, E877, PHENIX, STAR and ALICE experiments. The 𝐵2 values are calculated from the final spectra of protons and deuterons. At lower energies, √s N N ≤ 20 GeV, B2 drops drastically with increasing energy. The calculations confirm that this is due to the increasing freeze-out volume reflected in B2 ∼ 1/V . At higher energies, √s N N ≥ 20 GeV, B2 saturates at a constant level. This qualitative change and the vanishing of the volume suppression is shown to be due to the development of strong radial flow with increasing energy. The flow leads to strong space-momentum correlations which counteract the volume effect.
The β-barrel assembly machinery (BAM) consisting of the central β-barrel BamA and four other lipoproteins mediates the folding of the majority of the outer membrane proteins. BamA is placed in an asymmetric bilayer and its lateral gate is suggested to be the functional hotspot. Here we used in situ pulsed electron-electron double resonance spectroscopy to characterize BamA in the native outer membrane. In the detergent micelles, the data is consistent with mainly an inward-open conformation of BamA. The native membrane considerably enhanced the conformational heterogeneity. The lateral gate and the extracellular loop 3 exist in an equilibrium between different conformations. The outer membrane provides a favorable environment for occupying multiple conformational states independent of the lipoproteins. Our results reveal a highly dynamic behavior of the lateral gate and other key structural elements and provide direct evidence for the conformational modulation of a membrane protein in situ.
Geometrical frustration among interacting spins combined with strong quantum fluctuations destabilize long-range magnetic order in favor of more exotic states such as spin liquids. By following this guiding principle, a number of spin liquid candidate systems were identified in quasi-two-dimensional (quasi-2D) systems. For 3D, however, the situation is less favorable as quantum fluctuations are reduced and competing states become more relevant. Here we report a comprehensive study of thermodynamic, magnetic and dielectric properties on single crystalline and pressed-powder samples of PbCuTe2O6, a candidate material for a 3D frustrated quantum spin liquid featuring a hyperkagome lattice. Whereas the low-temperature properties of the powder samples are consistent with the recently proposed quantum spin liquid state, an even more exotic behavior is revealed for the single crystals. These crystals show ferroelectric order at TFE ≈ 1 K, accompanied by strong lattice distortions, and a modified magnetic response—still consistent with a quantum spin liquid—but with clear indications for quantum critical behavior.
Abstract
The endoplasmic reticulum (ER) is a key organelle of membrane biogenesis and crucial for the folding of both membrane and secretory proteins. Sensors of the unfolded protein response (UPR) monitor the unfolded protein load in the ER and convey effector functions for maintaining ER homeostasis. Aberrant compositions of the ER membrane, referred to as lipid bilayer stress, are equally potent activators of the UPR. How the distinct signals from lipid bilayer stress and unfolded proteins are processed by the conserved UPR transducer Ire1 remains unknown. Here, we have generated a functional, cysteine-less variant of Ire1 and performed systematic cysteine crosslinking experiments in native membranes to establish its transmembrane architecture in signaling-active clusters. We show that the transmembrane helices of two neighboring Ire1 molecules adopt an X-shaped configuration independent of the primary cause for ER stress. This suggests that different forms of stress converge in a common, signaling-active transmembrane architecture of Ire1.
Summary
The endoplasmic reticulum (ER) is a hotspot of lipid biosynthesis and crucial for the folding of membrane and secretory proteins. The unfolded protein response (UPR) controls the size and folding capacity of the ER. The conserved UPR transducer Ire1 senses both unfolded proteins and aberrant lipid compositions to mount adaptive responses. Using a biochemical assay to study Ire1 in signaling-active clusters, Väth et al. provide evidence that the neighboring transmembrane helices of clustered Ire1 form an ‘X’ irrespectively of the primary cause of ER stress. Hence, different forms of ER stress converge in a common, signaling-active transmembrane architecture of Ire1.