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Institute
- Physik (3598) (remove)
Intense ion beams with small phase space occupation (high brilliance) are mandatory to keep beam losses low in high current injector accelerators like those planned for FAIR. The low energy beam transport from the ion source towards the linac has to keep the emittance growth low and has to support the optimization of the ion source tune. The Frankfurt Neutron Source Facility FRANZ is currently under construction. An intense beam of protons (2 MeV, 200 mA) will be used for neutron production using the Li7(p,n)Be7 reaction for studies of the astrophysical s-process. A collimation channel, which can be adjusted to allow the transport of beams with a certain beam emittance, is an ideal tool to optimize the ion source tune in terms of beam brightness. Therefore a collimation channel in the Low Energy Beam Transport section will be used. Through defined apertures and transversal phase space rotation using focusing solenoids the beam halo as well as unwanted H2+ and H3+ fractions will be cut. Theoretical studies which were carried out so far and a first design of the setup will be presented.
Fluctuations of conserved quantities such as baryon number, charge, and strangeness are sensitive to the correlation length of the hot and dense matter created in relativistic heavy-ion collisions and can be used to search for the QCD critical point. We report the first measurements of the moments of net-kaon multiplicity distributions in Au+Au collisions at √sNN = 7.7, 11.5, 14.5, 19.6, 27, 39, 62.4, and 200 GeV. The collision centrality and energy dependence of the mean (M), variance (σ 2), skewness (S), and kurtosis (κ) for net-kaon multiplicity distributions as well as the ratio σ 2/M and the products Sσ and κσ 2 are presented. Comparisons are made with Poisson and negative binomial baseline calculations as well as with UrQMD, a transport model (UrQMD) that does not include effects from the QCD critical point. Within current uncertainties, the net-kaon cumulant ratios appear to be monotonic as a function of collision energy.
While the existence of a strongly interacting state of matter, known as “quark-gluon plasma” (QGP), has been established in heavy ion collision experiments in the past decade, the task remains to map out the transition from the hadronic matter to the QGP. This is done by measuring the dependence of key observables (such as particle suppression and elliptic flow) on the collision energy of the heavy ions. This procedure, known as "beam energy scan", has been most recently performed at the Relativistic Heavy Ion Collider (RHIC).
Utilizing a Boltzmann+hydrodynamics hybrid model, we study the collision energy dependence of initial state eccentricities and the final state elliptic and triangular flow. This approach is well suited to investigate the relative importance of hydrodynamics and hadron transport at different collision energies.
We study the two-flavor color superconductivity of low-temperature quark matter in the vicinity of chiral phase transition in the quark–meson model where the interactions between quarks are generated by pion and sigma exchanges. Starting from the Nambu–Gorkov propagator in real-time formulation we obtain finite temperature (real axis) Eliashberg-type equations for the quark self-energies (gap functions) in terms of the in-medium spectral function of mesons. Exact numerical solutions of the coupled nonlinear integral equations for the real and imaginary parts of the gap function are obtained in the zero temperature limit using a model input spectral function. We find that these components of the gap display a complicated structure with the real part being strongly suppressed above , 2Δ0 where Δ0 is its on-shell value. We find Δ0 ≈ 40 MeV close to the chiral phase transition.
An incoming or outgoing hadron in a hard collision with large momentum transfer gets squeezed in the transverse direction to its momentum. In the case of nuclear targets, this leads to the reduced interaction of such hadrons with surrounding nucleons which is known as color transparency (CT). The identification of CT in exclusive processes on nuclear targets is of significant interest not only by itself but also due to the fact that CT is a necessary condition for the applicability of factorization for the description of the corresponding elementary process. In this paper we discuss the semiexclusive processes A(e,e′π+) , A(π−,l−l+) and A(γ,π−p) . Since CT is closely related to hadron formation mechanism, the reduced interaction of ’pre-hadrons’ with nucleons is a common feature of generic high-energy inclusive processes on nuclear targets, such as hadron attenuation in deep inelastic scattering (DIS). We will discuss the novel way to study hadron formation via slow neutron production induced by a hard photon interaction with a nucleus. Finally, the opportunity to study hadron formation effects in heavy-ion collisions in the NICA regime will be considered.
The meaning of a recently proposed formalism for quantization of interacting fields is discussed by studying the consequences of the time-dependent unitary transformation which is essential for this approach. It turns out that non-relativistic quantum electrodynamics in dipole approximation may serve as a useful, although rather singular, example for this method. In the relativistic case a different point of view is suggested in order to avoid inconsistent interpretation. It is further possible to give arguments for a reasonable choice of the unitary transformation concerned.
A new era in experimental nuclear physics has begun with the start-up of the Large Hadron Collider at CERN and its dedicated heavy-ion detector system ALICE. Measuring the highest energy density ever produced in nucleus-nucleus collisions, the detector has been designed to study the properties of the created hot and dense medium, assumed to be a Quark-Gluon Plasma.
Comprised of 18 high granularity sub-detectors, ALICE delivers data from a few million electronic channels of proton-proton and heavy-ion collisions.
The produced data volume can reach up to 26 GByte/s for central Pb–Pb
collisions at design luminosity of L = 1027 cm−2 s−1 , challenging not only the data storage, but also the physics analysis. A High-Level Trigger (HLT) has been built and commissioned to reduce that amount of data to a storable value prior to archiving with the means of data filtering and compression without the loss of physics information. Implemented as a large high performance compute cluster, the HLT is able to perform a full reconstruction of all events at the time of data-taking, which allows to trigger, based on the information of a complete event. Rare physics probes, with high transverse momentum, can be identified and selected to enhance the overall physics reach of the experiment.
The commissioning of the HLT is at the center of this thesis. Being deeply embedded in the ALICE data path and, therefore, interfacing all other ALICE subsystems, this commissioning imposed not only a major challenge, but also a massive coordination effort, which was completed with the first proton-proton collisions reconstructed by the HLT. Furthermore, this thesis is completed with the study and implementation of on-line high transverse momentum triggers.
The femtoscopic study of pairs of identical pions is particularly suited to investigate the effective source function of particle emission, due to the resulting Bose-Einstein correlation signal. In small collision systems at the LHC, pp in particular, the majority of the pions are produced in resonance decays, which significantly affect the profile and size of the source. In this work, we explicitly model this effect in order to extract the primordial source in pp collisions at s√=13 TeV from charged π-π correlations measured by ALICE. We demonstrate that the assumption of a Gaussian primordial source is compatible with the data and that the effective source, resulting from modifications due to resonances, is approximately exponential, as found in previous measurements at the LHC. The universality of hadron emission in pp collisions is further investigated by applying the same methodology to characterize the primordial source of K-p pairs. The size of the primordial source is evaluated as a function of the transverse mass (mT) of the pairs, leading to the observation of a common scaling for both π-π and K-p, suggesting a collective effect. Further, the present results are compatible with the mT scaling of the p-p and p−Λ primordial source measured by ALICE in high multiplicity pp collisions, providing compelling evidence for the presence of a common emission source for all hadrons in small collision systems at the LHC. This will allow the determination of the source function for any hadron--hadron pairs with high precision, granting access to the properties of the possible final-state interaction among pairs of less abundantly produced hadrons, such as strange or charmed particles.
The structure and flexibility of RNA depends sensitively on the microenvironment. Using pulsed electron-electron double-resonance (PELDOR)/double electron-electron resonance (DEER) spectroscopy combined with advanced labeling techniques, we show that the structure of double-stranded RNA (dsRNA) changes upon internalization into Xenopus lævis oocytes. Compared to dilute solution, the dsRNA A-helix is more compact in cells. We recapitulate this compaction in a densely crowded protein solution. Atomic-resolution molecular dynamics simulations of dsRNA semi-quantitatively capture the compaction, and identify non-specific electrostatic interactions between proteins and dsRNA as a possible driver of this effect.
Anisotropic collective flow of protons resulting from non-central heavy ion collisions is a unique hadronic observable providing information about the early stage of the nuclear collision. The analysis of collective flow in the energy regime between 1-2 AGeV enables the study of the phase diagram of hadronic matter at a high baryochemical potential µb, as well as the analysis of the equation of state at densities up to the threefold of the ground state density ρ0.
The algorithms of the standard event plane method and the scalar product method are used to analyse directed and elliptic flow of protons in a centrality range of 0-40 % most central events.
Prior to the analysis of experimental data, the respective influence of the reconstruction procedure on the algorithms is examined using Monte Carlo simulations based on the Ultra relativistic Quantum Molecular Dynamics (UrQMD) model.
Subsequently, experimental data measured in April 2012 with the High Acceptance DiElectron Spectrometer (HADES) is analysed using both methods. About 7.3 · 109 Au+Au events at a kinetic beam energy of 1.23 AGeV, equivalent to a centre of mass energy of √sNN = 2.42 GeV were recorded. A multi-differential analysis is feasible as the HADES detector provides a good transverse momentum and rapidity coverage.
Both algorithms result in identical values for directed and elliptic flow across all centrality classes within the observable phase space of protons. The calculated integrated value of v2 at mid rapidity is in good agreement with world data.
Intermediate Mass Ratio Inspirals (IMRIs) will be observable with space-based gravitational wave detectors such as the Laser Interferometer Space Antenna (LISA). To this end, the environmental effects in such systems have to be modeled and understood. These effects can include (baryonic) accretion disks and dark matter (DM) overdensities, so called spikes. For the first time, we model an IMRI system with both an accretion disk and a DM spike present and compare their effects on the inspiral and the emitted gravitational wave signal. We study the eccentricity evolution, employ the braking index and derive the dephasing index, which turn out to be complementary observational signatures. They allow us to disentangle the accretion disk and DM spike effects in the IMRI system.
Intermediate Mass Ratio Inspirals (IMRIs) will be observable with space-based gravitational wave detectors such as the Laser Interferometer Space Antenna (LISA). To this end, the environmental effects in such systems have to be modeled and understood. These effects can include (baryonic) accretion disks and dark matter (DM) overdensities, so called spikes. For the first time, we model an IMRI system with both an accretion disk and a DM spike present and compare their effects on the inspiral and the emitted gravitational wave signal. We study the eccentricity evolution, employ the braking index and derive the dephasing index, which turn out to be complementary observational signatures. They allow us to disentangle the accretion disk and DM spike effects in the IMRI system.
Hemispherical and cylindrical antenna arrays are widely used in radar-based and tomography-based microwave breast imaging systems. Based on the dielectric contrast between healthy and malignant tissue, a three-dimensional image could be formed to locate the tumor. However, conventional X-ray mammography as the golden standard in breast cancer screening produces two-dimensional breast images so that a comparison between the 3D microwave image and the 2D mammogram could be difficult. In this paper, we present the design and realisation of a UWB breast imaging prototype for the frequency band from 1 to 9 GHz. We present a refined system design in light of the clinical usage by means of a planar scanning and compare microwave images with those obtained by X-ray mammography. Microwave transmission measurements were processed to create a two-dimensional image of the breast that can be compared directly with a two-dimensional mammogram. Preliminary results from a patient study are presented and discussed showing the ability of the proposed system to locate the tumor.
In case of 4-Rod-type RFQ’s the quadrupole electrodes are excited by a series of coupled RF oscillators. As the contact planes between both electrode pairs differ, there remains an oscillating electric potential along the beam axis. This results in remarkably high longitudinal field components between the electrode ends and the RFQ tank end walls. In contrast, the electrodes of a 4-Vane RFQ are equally charged to ±|V0∕2| and only feature a quadrupole on-axis field. The entrance gap fields were investigated to serve as a longitudinal prebuncher instead of causing additional longitudinal emittance growth. The effects of the entrance gap field have been validated in beam dynamics simulations. The exit fields have to be taken into consideration for a calculation of the exact RFQ output energy.
The Δ-isobar degrees of freedom are included in the covariant density functional (CDF) theory to study the equation of state (EoS) and composition of dense matter in compact stars. In addition to Δ's we include the full octet of baryons, which allows us to study the interplay between the onset of delta isobars and hyperonic degrees of freedom. Using both the Hartree and Hartree–Fock approximation we find that Δ's appear already at densities slightly above the saturation density of nuclear matter for a wide range of the meson–Δ coupling constants. This delays the appearance of hyperons and significantly affects the gross properties of compact stars. Specifically, Δ's soften the EoS at low densities but stiffen it at high densities. This softening reduces the radius of a canonical 1.4M⊙ star by up to 2 km for a reasonably attractive Δ potential in matter, while the stiffening results in larger maximum masses of compact stars. We conclude that the hypernuclear CDF parametrizations that satisfy the 2M⊙ maximum mass constraint remain valid when Δ isobars are included, with the important consequence that the resulting stellar radii are shifted toward lower values, which is in agreement with the analysis of neutron star radii.
Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.
Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.
Different approaches are possible when it comes to modeling the brain. Given its biological nature, models can be constructed out of the chemical and biological building blocks known to be at play in the brain, formulating a given mechanism in terms of the basic interactions underlying it. On the other hand, the functions of the brain can be described in a more general or macroscopic way, in terms of desirable goals. This goals may include reducing metabolic costs, being stable or robust, or being efficient in computational terms. Synaptic plasticity, that is, the study of how the connections between neurons evolve in time, is no exception to this. In the following work we formulate (and study the properties of) synaptic plasticity models, employing two complementary approaches: a top-down approach, deriving a learning rule from a guiding principle for rate-encoding neurons, and a bottom-up approach, where a simple yet biophysical rule for time-dependent plasticity is constructed.
We begin this thesis with a general overview, in Chapter 1, of the properties of neurons and their connections, clarifying notations and the jargon of the field. These will be our building blocks and will also determine the constrains we need to respect when formulating our models. We will discuss the present challenges of computational neuroscience, as well as the role of physicists in this line of research.
In Chapters 2 and 3, we develop and study a local online Hebbian self-limiting synaptic plasticity rule, employing the mentioned top-down approach. Firstly, in Chapter 2 we formulate the stationarity principle of statistical learning, in terms of the Fisher information of the output probability distribution with respect to the synaptic weights. To ensure that the learning rules are formulated in terms of information locally available to a synapse, we employ the local synapse extension to the one dimensional Fisher information. Once the objective function has been defined, we derive an online synaptic plasticity rule via stochastic gradient descent.
In order to test the computational capabilities of a neuron evolving according to this rule (combined with a preexisting intrinsic plasticity rule), we perform a series of numerical experiments, training the neuron with different input distributions.
We observe that, for input distributions closely resembling a multivariate normal distribution, the neuron robustly selects the first principal component of the distribution, showing otherwise a strong preference for directions of large negative excess kurtosis.
In Chapter 3 we study the robustness of the learning rule derived in Chapter 2 with respect to variations in the neural model’s transfer function. In particular, we find an equivalent cubic form of the rule which, given its functional simplicity, permits to analytically compute the attractors (stationary solutions) of the learning procedure, as a function of the statistical moments of the input distribution. In this way, we manage to explain the numerical findings of Chapter 2 analytically, and formulate a prediction: if the neuron is selective to non-Gaussian input directions, it should be suitable for applications to independent component analysis. We close this section by showing how indeed, a neuron operating under these rules can learn the independent components in the non-linear bars problem.
A simple biophysical model for time-dependent plasticity (STDP) is developed in Chapter 4. The model is formulated in terms of two decaying traces present in the synapse, namely the fraction of activated NMDA receptors and the calcium concentration, which serve as clocks, measuring the time of pre- and postsynaptic spikes. While constructed in terms of the key biological elements thought to be involved in the process, we have kept the functional dependencies of the variables as simple as possible to allow for analytic tractability. Despite its simplicity, the model is able to reproduce several experimental results, including the typical pairwise STDP curve and triplet results, in both hippocampal culture and layer 2/3 cortical neurons. Thanks to the model’s functional simplicity, we are able to compute these results analytically, establishing a direct and transparent connection between the model’s internal parameters and the qualitative features of the results.
Finally, in order to make a connection to synaptic plasticity for rate encoding neural models, we train the synapse with Poisson uncorrelated pre- and postsynaptic spike trains and compute the expected synaptic weight change as a function of the frequencies of these spike trains. Interestingly, a Hebbian (in the rate encoding sense of the word) BCM-like behavior is recovered in this setup for hippocampal neurons, while dominating depression seems unavoidable for parameter configurations reproducing experimentally observed triplet nonlinearities in layer 2/3 cortical neurons. Potentiation can however be recovered in these neurons when correlations between pre- and postsynaptic spikes are present. We end this chapter by discussing the relation to existing experimental results, leaving open questions and predictions for future experiments.
A set of summary cards of the models employed, together with listings of the relevant variables and parameters, are presented at the end of the thesis, for easier access and permanent reference for the reader.
Based on data samples collected with the BESIII detector at the BEPCII collider, the process e+e−→Σ+Σ¯− is studied at center-of-mass energies s√ = 2.3960, 2.6454, and 2.9000~GeV. Using a fully differential angular description of the final state particles, the complete information of the Σ+ electromagnetic form factors in the time-like region is extracted. The relative phase between the electric and magnetic form factors is determined to be sinΔΦ = -0.67~±~0.29~(stat.)~±~0.18~(syst.) at s√ = 2.3960~GeV, ΔΦ = 55∘~±~19∘~(stat.) ±~14∘~(syst.) at s√ = 2.6454~GeV, and 78∘~±~22∘~(stat.) ±~9∘~(syst.) at s√ = 2.9000~GeV. For the first time, the phase of the hyperon electromagnetic form factors is explored in a wide range of four-momentum transfer. The evolution of the phase along with four-momentum transfer is an important input for understanding its asymptotic behavior and the dynamics of baryons.
Thermal leptogenesis, in the framework of the standard model with three additional heavy Majorana neutrinos, provides an attractive scenario to explain the observed baryon asymmetry in the universe. It is based on the out-of-equilibrium decay of Majorana neutrinos in a thermal bath of standard model particles, which in a fully quantum field theoretical formalism is obtained by solving Kadanoff-Baym equations. So far, the leading two-loop contributions from leptons and Higgs particles are included, but not yet gauge corrections. These enter at three-loop level but, in certain kinematical regimes, require a resummation to infinite loop order for a result to leading order in the gauge coupling. In this work, we apply such a resummation to the calculation of the lepton number density. The full result for the simplest “vanilla leptogenesis” scenario is by O(1) increased compared to that of quantum Boltzmann equations, and for the first time permits an estimate of all theoretical uncertainties. This step completes the quantum theory of leptogenesis and forms the basis for quantitative evaluations, as well as extensions to other scenarios.