OPUS 4 | Physik

A numerical renormalization group approach to dissipative quantum impurity systems (2011)

David Roosen

The miniaturization of electronics is reaching its limits. Structures necessary to build integrated circuits from semiconductors are shrinking and could reach the size of only a few atoms within the next few years. It will be at the latest at this point in time that the physics of nanostructures gains importance in our every day life. This thesis deals with the physics of quantum impurity models. All models of this class exhibit an identical structure: the simple and small impurity only has few degrees of freedom. It can be built out of a small number of atoms or a single molecule, for example. In the simplest case it can be described by a single spin degree of freedom, in many quantum impurity models, it can be treated exactly. The complexity of the description arises from its coupling to a large number of fermionic or bosonic degrees of freedom (large meaning that we have to deal with particle numbers of the order of 10^{23}). An exact treatment thus remains impossible. At the same time, physical effects which arise in quantum impurity systems often cannot be described within a perturbative theory, since multiple energy scales may play an important role. One example for such an effect is the Kondo effect, where the free magnetic moment of the impurity is screened by a "cloud" of fermionic particles of the quantum bath. The Kondo effect is only one example for the rich physics stemming from correlation effects in many body systems. Quantum impurity models, and the oftentimes related Kondo effect, have regained the attention of experimental and theoretical physicists since the advent of quantum dots, which are sometimes also referred to as as artificial atoms. Quantum dots offer a unprecedented control and tunability of many system parameters. Hence, they constitute a nice "playground" for fundamental research, while being promising candidates for building blocks of future technological devices as well. Recently Loss' and DiVincenzo's proposal of a quantum computing scheme based on spins in quantum dots, increased the efforts of experimentalists to coherently manipulate and read out the spins of quantum dots one by one. In this context two topics are of paramount importance for future quantum information processing: since decoherence times have to be large enough to allow for good error correction schemes, understanding the loss of phase coherence in quantum impurity systems is a prerequisite for quantum computation in these systems. Nonequilibrium phenomena in quantum impurity systems also have to be understood, before one may gain control of manipulating quantum bits. As a first step towards more complicated nonequilibrium situations, the reaction of a system to a quantum quench, i.e. a sudden change of external fields or other parameters of the system can be investigated. We give an introduction to a powerful numerical method used in this field of research, the numerical renormalization group method, and apply this method and its recent enhancements to various quantum impurity systems. The main part of this thesis may be structured in the following way: - Ferromagnetic Kondo Model, - Spin-Dynamics in the Anisotropic Kondo and the Spin-Boson Model, - Two Ising-coupled Spins in a Bosonic Bath, - Decoherence in an Aharanov-Bohm Interferometer.

Commissioning of the ALICE High-Level Trigger (2012)

Jochen Thäder

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.

Coulomb dissociation of 31Cl and 32Ar - constraining the rp process (2012)

Christoph Langer

The subject of this thesis aimed at a better understanding of the spectacular X-ray burst. The most likely astrophysical site is a very dense neutron star, which accretes H/He-rich matter from a close companion. While falling towards the neutron star, the matter is heated up and a thermonuclear runaway is ignited. The exact description of this process is dominated by the properties of a few proton-rich radioactive isotopes, which have a low interaction probability, hence a high abundance. The topic of this thesis was therefore an investigation of the short-lived, proton-rich isotopes 31Cl and 32Ar. The Coulomb dissociation method is the modern technique of choice. Excitations with energies up to 20 MeV can be induced by the Lorentz contracted Coulomb ﬁeld of a lead target. At the GSI Helmholtzzentrum für Schwerionenforschung GmbH in Darmstadt, Germany, a Ar beam was accelerated to an energy of 825 AMeV and fragmented in a beryllium target. The fragment separator was used to select the desired isotopes with a remaining energy of 650 AMeV. They were subsequently directed onto a 208 Pb target in the ALAND/LAND setup. The measurement was performed in inverse kinematics. All reaction products were detected and inclusive and exclusive measurements of the respective Coulomb dissociation cross sections were possible. During the analysis of the experiment, it was possible to extract the energy-diﬀerential excitation spectrum of 31Cl, and to constrain astrophysically important parameters for the time-reversed 30S(p,γ)31Cl reaction. A single resonance at 0.443(37) MeV dominates the stellar reaction rate, which was also deduced and compared to previous calculations. The integrated Coulomb dissociation cross section of this resonance was determined to 15(6) mb. The astrophysically important one- and two-proton emission channels were analyzed for 32Ar and energy-diﬀerential excitation spectra could be derived. The integrated Coulomb dissociation cross section for two proton emission were determined with two diﬀerent techniques. The inclusive measurement yields a cross section of 214(29stat)(20sys) mb, whereas the exclusive reconstruction results in a cross section of 226(14stat)(23sys) mb. Both results are in very good agreement. The Coulomb dissociation cross section for the one-proton emission channel is extracted solely from the exclusive measurement and is 54(8stat)(6sys) mb. Furthermore, the development of the Low Energy Neutron detector Array (LENA) for the upcoming R3B setup is described. The detector will be utilized in charge-exchange reactions to detect the low-energy recoil neutrons from (p,n)-type reactions. These reaction studies are of particular importance in the astrophysical context and can be used to constrain half lifes under stellar conditions. In the frame of this work, prototypes of the detector were built and successfully commissioned in several international laboratories. The analysis was supported by detailed simulations of the detection characteristics.

Density functional theory and dynamical mean field theory: applications to correlated electron materials (2012)

Johannes Ferber

The study of systems whose properties are governed by electronic correlations is a corner stone of modern solid-state physics. Often, such systems feature unique and distinct properties like Mott metal-insulator transitions, rich phase diagrams, and high sensitivity to subtle changes in the applied conditions. Whereas the standard approach to electronic structure calculations, density functional theory (DFT), is able to address the complexity of real-world materials but is known to have serious limitations in the description of correlations, the dynamical mean-field theory (DMFT) has become an established method for the treatment of correlated fermions, first on the level of minimal models and later in combination with DFT, termed LDA+DMFT. This thesis presents theoretical calculations on different materials exhibiting correlated physics, where we aim at covering a range in terms of systems --from rather weakly correlated to strongy correlated-- as well as in terms of methods, from DFT calculations to combined LDA+DMFT calculations. We begin with a study on a selection of iron pnictides, a recently discovered family of high-temperature superconductors with varying degree of correlation strength, and show that their magnetic and optical properties can be assessed to some degree within DFT, despite the correlated nature of these systems. Next, extending our analysis to the inclusion of correlations in the framework of LDA+DMFT, we discuss the electronic structure of the iron pnictide LiFeAs which we find to be well described by Fermi liquid theory with regard to many of its properties, yet we see distinct changes in its Fermi surface upon inclusion of correlations. We continue the study of low-energy properties and specifically Fermi surfaces on two more iron pnictides, LaFePO and LiFeP, and predict a topology change of their Fermi surfaces due to the effect of correlations, with possible implications for their superconducting properties. In our last study, we close the circle by presenting LDA+DMFT calculations on an organic molecular crystal on the verge of a Mott metal-insulator transition; there, we find the spectral and optical properties to display signatures of strong electronic correlations beyond Fermi liquid theory.

Die Untersuchung der Ionisationsdynamik von Heliumdimeren in Stößen mit Alpha-Teilchen (2011)

Jasmin Titze

Dynamical effects and disorder in ultracold bosonic matter (2012)

Ulf Bissbort

In this thesis, various aspects on the theoretical description of ultracold bosonic atoms in optical lattices are investigated. After giving a brief introduction to the fundamental concepts of BECs, atomic physics, interatomic interactions and experimental procedures in chapter (1), we derive the Bose-Hubbard model from first principles in chapter (2). In this chapter, we also introduce and discuss a technique to efficiently determine Wannier states, which, in contrast to current techniques, can also be extended to inhomogeneous systems. This technique is later extended to higher dimensional, non-separable lattices in chapter (5). The many-body physics and phases of the Bose-Hubbard is shortly presented in chapter (3) in conjunction with Gutzwiller mean-field theory, and the recently devised projection operator approach. We then return to the derivation of an improved microscopic many-body Hamiltonian, which contains higher band contributions in the presence of interactions in chapter (4). We then move on to many-particle theory. To demonstrate the conceptual relations required in the following chapter, we derive Bogoliubov theory in chapter (5.3.4) in three different ways and discuss the connections. Furthermore, this derivation goes beyond the usual version discussed in most textbooks and papers, as it accounts for the fact, that the quasi-particle Hamiltonian is not diagonalizable in the condensate and the eigenvectors have to be completed by additional vectors to form a basis. This leads to a qualitatively different quasi-particle Hamiltonian and more intricate transformation relations as a result. In the following two chapters (7, 8), we derive an extended quasi-particle theory, which goes beyond Bogoliubov theory and is not restricted to weak interactions or a large condensate fraction. This quasi-particle theory naturally contains additional modes, such as the amplitude mode in the strongly interacting condensate. Bragg spectroscopy, a momentum-resolved spectroscopic technique, is introduced and used for the first experimental detection of the amplitude mode at finite quasi-momentum in chapter (9). The closely related lattice modulation spectroscopy is discussed in chapter (10). The results of a time-dependent simulation agree with experimental data, suggesting that also the amplitude mode, and not the sound mode, was probed in these experiments. In chapter (11) the dynamics of strongly interacting bosons far from equilibrium in inhomogeneous potentials is explored. We introduce a procedure that, in conjunction with the collapse and revival of the condensate, can be used to create exotic condensates, while particularly focusing on the case of a quadratic trapping potential. Finally, in chapter (12), we turn towards the physics of disordered systems derive and discuss in detail the stochastic mean-field theory for the disordered Bose-Hubbard model.

Electron-tunneling studies on CeCoIn5 heavy-fermion thin films and microstructures (2012)

Oleksandr Foyevtsov

Investigation of low-temperature electronic properties of MBE grown CeCoIn5 and CeIn3 thin films by means of electron tunneling and quantum electron interference effects.

Electroweak quantum chemistry: Parity violation in spectra of chiral molecules containing heavy atoms (2012)

Sophie Nahrwold

The intriguing effects of electroweak induced parity violation (PV) in molecules have yet to be observed, but experiments on molecular PV promise to provide fascinating insights. They potentially offer a novel testing ground for the low energy sector of the standard model and, in addition, a successful measurement of PV differences between the two enantiomers of a chiral molecule could promote a deeper understanding of molecular chirality, by essentially establishing a new link between particle physics and biochemistry. A key challenge in the design of such experiments is the identification of suitable molecules, which in turn requires widely applicable computational schemes for the prediction of PV experimental signals. To this end, a quasirelativistic density functional theory approach to the calculation of PV effects in nuclear magnetic resonance (NMR) spectra of chiral molecules has been developed and implemented during the course of this thesis. It includes relativistic as well as electron--correlation effects and has been used extensively in the screening of molecules possibly suited for a first observation of molecular PV. Some relevant compound classes have been identified, but none of their selected representatives are predicted to exhibit PV NMR frequency shifts that can be detected under current experimental restrictions. In order to advance the design of molecules which exhibit particularly large PV signals in experiments, systematic effects on PV NMR frequency splittings such as scaling with nuclear charge, conformational dependence and the impact of atomic substitution around the NMR active nucleus have been studied. Previously predicted scaling laws were confirmed and it was determined that the environment of the NMR active nucleus, both in terms of conformation and atomic composition, can be tuned to increase PV frequency shifts by several orders of magnitude. In addition to molecules suited for NMR experiments, a fascinating chiral actinide compound was studied with regard to PV frequency shifts in vibrational spectra. This compound displays the largest such shift ever predicted for an existing molecule, which lies well within the attainable experimental resolution. The challenge now lies in making it compatible with current experimental setups.

Gas system, gas quality monitor and detector control of the ALICE Transition Radiation Detector and studies for a pre-trigger data read-out system (2012)

Nora Pitz

The main purpose of the Transition Radiation Detector (TRD) located in the central barrel of ALICE (A Large Ion Collider Experiment) is electron identification for separation from pions at momenta pt > 1 GeV/c, since in this momentum range the measurements of the specific energy loss (dE/dx) of the Time Projection Chamber (TPC) is no longer sufficient. Furthermore, it provides a fast trigger for high transverse momentum charged particles (pt > 3 GeV/c) and makes a significant contribution to the optimization of the tracking of reaction products in heavy-ion collisions. Its whole setup comprises 18 supermodules out of which 13 are presently operational and mounted cylindrically around the beam axis of the Large Hadron Collider (LHC). A supermodule contains either 30 or 24 chambers, each consisting of a radiator for transition radiation creation, a drift and an amplifying region followed by the read-out electronics. In total, the TRD is an array of 522 chambers operated with about 28 m3 of a Xe-CO2 [85-15%] gas mixture. During the work of this thesis, the testing, commissioning, operation and maintenance of detector parts, the gas system and its online quality monitor, improvements on the detector control user-interface and studies about a new pre-trigger module for data read-out have been accomplished. The TRD gas system mixes, distributes and circulates the operational gas mixture through the detector. Its overall optimization has been achieved by minimizing gas leakage, surveying, controlling, maintaining and continuously improving it as well as designing and carrying out upgrades. Gas quality monitors of the type \GOOFIE" (Gas prOportional cOunter For drIfting Electrons) can be used in gaseous detectors as on-line monitors of the electron drift velocity, gain and gas properties. One of these devices has been implemented within the TRD gas system, while another one surveys the gas of the TPC. Both devices had to be adapted to the specific needs of the detectors, were under constant surveillance and control, and needed to be further developed on both hardware and software side. To improve the operation of the TRD, modifications on its DCS software (Detector Control System) used for monitoring, controlling, operating, regulating and configuring of hardware and computing devices have been carried out. The DCS is designed to enable an operator to interact with equipment through user interfaces that display the information from the system. The main focus of this work was laid on the optimization of the usability and design of the user interface. The front-end electronics of the TRD require an early start signal (\pre-trigger") from the fast forward detectors or the Time-Of-Flight detector during the running periods. The realization of a new hardware concept for the read-out of the TRD pre-trigger system has been studied and first tests were performed. This new module called PIMDDL (Pre-trigger Interface Module Detector Data Link) is meant to acquire all data necessary to simulate and predict the full pre-trigger functionality, and to verify its proper operation. Furthermore, it shall provide all functionalities of the so-called Control Box Bottom as well as keep the functionalities of the already existing PIM (Pre-trigger Interface Module) in order to combine and replace these two modules in the future.

Identifikationsverfahren mit Reaktions-Diffusions-Netzwerken zur Analyse hirnelektrischer Aktivität bei Epilepsie (2011)

Frank Gollas

In dieser Arbeit wurden Verfahren zur Identifikation hirnelektrischer Aktivität mit Zellularen Nichtlinearen Netzwerken (CNN), im Besonderen Reaktions-Diffusions-Netzwerken, entwickelt und untersucht. Mit Hilfe der eingeführten Methoden wurden Langzeitaufzeichnungen hirnelektrischer Aktivität bei Epilepsie analysiert und mittels eines automatisierten Verfahrens ermittelt, inwieweit sich mögliche Voranfallszustände vom anfallsfreien Zustand im statistischen Sinne trennen lassen. Zunächst wurde ein Überblick über CNN gegeben und deren Beschreibung durch Systeme gekoppelter Differentialgleichungen dargestellt. Weiterhin wurden die Möglichkeiten der Informationsverarbeitung mit CNN durch Ausnutzung von Gleichgewichtszuständen oder der vollständigen raum-zeitlichen Dynamik der Netzwerke diskutiert. Zusätzlich wurde die Klasse der Reaktions-Diffusions-Netzwerke (RD-CNN) eingeführt. Für die Repräsentation der hierbei benötigten weitgehend allgemeinen nichtlinearen Zellkopplungsvorschriften wurden polynomiale Gewichtsfunktionen vorgeschlagen. Mit einer Darstellung der Theorie der Lokalen Aktivität wurden notwendige Bedingungen für emergentes Verhalten in RD-CNN angegeben. Die statistische Bewertung von Vorhersagemodellen wurde aus theoretischer Sicht beleuchtet. Mit der Receiver Operating Characteristic (ROC) wurde eine Analysemethode zur Beurteilung der Vorhersagekraft des zeitlichen Verlaufs von Kenngrößen bezüglich bevorstehender epileptischer Anfälle vorgestellt. 155 5 Zusammenfassung Als nächstes wurden Überlegungen zur numerischen Simulation von CNN und deren flexible und erweiterbare programmtechnische Umsetzung entwickelt. Die daraus resultierende und im Rahmen dieser Arbeit entstandene objektorientierte Simulationsumgebung FORCE++ wurde konzeptionell und im Hinblick auf die Softwarearchitektur vorgestellt. Die Verfahren zur numerischen Simulation wurden auf die Problemstellung der Systemidentifikation mit CNN angewandt. Dazu wurden Netzwerke derart bestimmt, dass deren Zellausgangswerte entsprechende Signalwerte des beobachteten, zu identifizierenden Systems approximieren. Da die Parameter der zu bestimmenden CNN im vorliegenden Fall der Untersuchung hirnelektrischer Aktivität nicht bekannt sind und nicht direkt abgeleitet werden können, wurden überwachte Lernverfahren zur Bestimmung der Netzwerke eingesetzt. Hierbei wurden Lernverfahren verschiedener Klassen für die Identifikation mit CNN mit polynomialen Gewichtsfunktionen untersucht. Die Leistungsfähigkeit des vorgestellten Identifikationsverfahrens wurde anhand bekannter Systeme einer genauen Betrachtung unterzogen. Dabei wurde festgestellt, dass die betrachteten Systeme mit hoher Genauigkeit durch CNN repräsentiert werden konnten. Exemplarisch wurde das Parametergebiet lokaler Aktivität für ein RD-CNN berechnet und durch numerische Simulationen die Ausbildung von Mustern innerhalb des Netzwerkes nachgewiesen. Nach einem einleitenden Überblick über die medizinischen Hintergründe von Epilepsie und der Erfassung hirnelektrischer Aktivität wurde eine vergleichende Übersicht über den Stand veröffentlichter Studien zur Vorhersage epileptischer Anfälle gegeben. Für die Anwendung des hier vorgestellten Identifikationsverfahrens zur Analyse hirnelektrischer Aktivität wurde zunächst die Genauigkeit der Approximation kurzer, als quasi-stationär betrachteter Abschnitte, von EEG- 156 5 Zusammenfassung Signalen untersucht. Durch gezielte Erhöhung der Komplexität herangezogener Netzwerke konnte hier die Genauigkeit der Repräsentation von EEG-Signalverläufen deutlich verbessert werden. Dabei wurde zudem die Verallgemeinerungsfähigkeit der ermittelten Netzwerke untersucht, wobei festgestellt wurde, dass auch solche Signalwerte mit guter Genauigkeit approximiert werden, die nicht im Identifikationsverfahren durch die überwachte Parameteroptimierung berücksichtigt waren. Um speziell den Einfluss der Information aus der Korrelation benachbarter Elektrodensignale zu untersuchen, wurde ein Verfahren zur multivariaten Prädiktion mit Discrete Time CNN (DT-CNN) entwickelt. Hierbei werden durch ein CNN Signalwerte der betrachteten Elektrode aus vergangenen, korrelierten Signalwerten von Nachbarelektroden geschätzt. Für diese Aufgabenstellung konnte eine Methode zur Bestimmung der Netzwerkparameter im optimalen Sinn, alleine aus den statistischen Eigenschaften der Elektrodensignale angegeben werden. Dadurch gelang eine erhebliche Reduzierung der Rechenkomplexität, die eine umfangreiche Untersuchung intrakranieller Langzeitableitungen ermöglichte. Zur Analyse von Langzeitaufzeichnungen mit dem RD-CNN Identifikationsverfahren, wurden die numerischen Berechnungen zur Simulation von CNN mit FORCE++ auf einem durchsatz-orientierten Hochleistungs- Rechnernetzwerk durchgeführt. Mit den so gewonnen Ergebnissen konnten vergleichende Analysen vorgenommen werden. Zudem wurden Untersuchungen zum Vorliegen lokaler Aktivität in den ermittelten RD-CNN durchgeführt. Die bei den beschriebenen Verfahren extrahierten Kenngrößen hirnelektrischer Aktivität wurden durch ein automatisiertes Verfahren auf ihre Vorhersagekraft für epileptische Anfälle bewertet. Dabei wurde untersucht, inwieweit der anfallsfreie Zustand und ein angenommener 157 5 Zusammenfassung Voranfallszustand durch die jeweils betrachtete Kenngröße im statistischen Sinn diskriminiert werden kann. Durch parallele Analysen mit Anfallszeitsurrogaten wurden hierzu ergänzende Signifikanztests durchgeführt. Nach Auswertung von mehrtägigen Hirnstromsignalen verschiedener Patienten konnte festgestellt werden, dass mit den in dieser Arbeit entwickelten Verfahren Kenngrößen hirnelektrischer Aktivität bestimmt werden konnten, welche offenbar die Identifikation potentieller Voranfallszustände ermöglichen. Auch wenn für eine breite medizinische Anwendung die Spezifität und Sensitivität noch weiter verbessert werden muss, so können doch die erzielten Ergebnisse einen wesentlichen Schritt hin zu einer implantierbaren, CNN-basierten Plattform zur Erkennung und Verhinderung epileptischer Anfälle darstellen. Die Berechnungen für das Identifikationsverfahren mit RD-CNN könnten dabei durch zukünftige, spezialisierte schaltungstechnische Realisierungen für mehrschichtige CNN mit polynomialen Gewichtsfunktionen eine erhebliche Beschleunigung erfahren.

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