Computer simulations of slowly relaxing systems in external fields

Eine der offenen Fragen der aktuellen Physik ist das Verständnis von Systemen im Nichtgleichgewicht. Im Gegensatz zu der Gleichgewichtsphysik ist in diesem Bereich aktuell kein Formalismus bekannt der ein systematisches Beschreiben der unterschiedlichen Systeme ermöglicht. Um das Verständnis über diese Systeme zu vergrößern werden in dieser Arbeit zwei unterschiedliche Systeme studiert, die unter einem externen Feld ein starkes nichtlineares Verhalten zeigen. Hierbei handelt es sich zum einen um das Verhalten von Teilchen unter dem Einfluss einer extern angelegten Kraft und zum anderen um das Verhalten eines Systems in der Nähe des kritischen Punktes unter Scherung. Das Modellsystem in dem ersten Teil der Arbeit ist eine binäre Yukawa Mischung, die bei tiefen Temperaturen einen Glassübergang zeigt. Dies führt zu einer stark ansteigenden Relaxationszeit des Systems, so dass man auch bei kleinen Kräften relativ schnell ein nichtlineares Verhalten beobachtet. In Abhängigkeit der angelegten konstanten Kraft können in dieser Arbeit drei Regime, mit stark unterschiedlichem Teilchenverhalten, identifiziert werden. In dem zweiten Teil der Arbeit wird das Ising-Modell unter Scherung betrachtet. In der Nähe des kritischen Punkts kommt es in diesem Modell zu einer Beeinflussung der Fluktuationen in dem System durch das angelegte Scherfeld. Dies hat zur Folge, dass das System stark anisotrop wird und man zwei unterschiedliche Korrelationslängen vorfindet, die mit unterschiedlichen Exponenten divergieren. Infolgedessen lässt sich der normale isotrope Formalismus des "finite-size scaling" nicht mehr auf dieses System anwenden. In dieser Arbeit wird gezeigt, wie dieser auf den anisotropen Fall zu verallgemeinern ist und wie damit die kritischen Punkte, sowie die dazu gehörenden kritischen Exponenten berechnet werden können.

A mesoscopic simulation method for electrolyte solutions

This thesis deals with the development of a novel simulation technique for macromolecules in electrolyte solutions, with the aim of a performance improvement over current molecular-dynamics based simulation methods. In solutions containing charged macromolecules and salt ions, it is the complex interplay of electrostatic interactions and hydrodynamics that determines the equilibrium and non-equilibrium behavior. However, the treatment of the solvent and dissolved ions makes up the major part of the computational effort. Thus an efficient modeling of both components is essential for the performance of a method. With the novel method we approach the solvent in a coarse-grained fashion and replace the explicit-ion description by a dynamic mean-field treatment. Hence we combine particle- and field-based descriptions in a hybrid method and thereby effectively solve the electrokinetic equations. The developed algorithm is tested extensively in terms of accuracy and performance, and suitable parameter sets are determined. As a first application we study charged polymer solutions (polyelectrolytes) in shear flow with focus on their viscoelastic properties. Here we also include semidilute solutions, which are computationally demanding. Secondly we study the electro-osmotic flow on superhydrophobic surfaces, where we perform a detailed comparison to theoretical predictions.

Modeling and simulation of fibrinogen and its adsorption behavior

In this thesis different approaches for the modeling and simulation of the blood protein fibrinogen are presented. The approaches are meant to systematically connect the multiple time and length scales involved in the dynamics of fibrinogen in solution and at inorganic surfaces. The first part of the thesis will cover simulations of fibrinogen on an all atom level. Simulations of the fibrinogen protomer and dimer are performed in explicit solvent to characterize the dynamics of fibrinogen in solution. These simulations reveal an unexpectedly large and fast bending motion that is facilitated by molecular hinges located in the coiled-coil region of fibrinogen. This behavior is characterized by a bending and a dihedral angle and the distribution of these angles is measured. As a consequence of the atomistic detail of the simulations it is possible to illuminate small scale behavior in the binding pockets of fibrinogen that hints at a previously unknown allosteric effect. In a second step atomistic simulations of the fibrinogen protomer are performed at graphite and mica surfaces to investigate initial adsorption stages. These simulations highlight the different adsorption mechanisms at the hydrophobic graphite surface and the charged, hydrophilic mica surface. It is found that the initial adsorption happens in a preferred orientation on mica. Many effects of practical interest involve aggregates of many fibrinogen molecules. To investigate such systems, time and length scales need to be simulated that are not attainable in atomistic simulations. It is therefore necessary to develop lower resolution models of fibrinogen. This is done in the second part of the thesis. First a systematically coarse grained model is derived and parametrized based on the atomistic simulations of the first part. In this model the fibrinogen molecule is represented by 45 beads instead of nearly 31,000 atoms. The intra-molecular interactions of the beads are modeled as a heterogeneous elastic network while inter-molecular interactions are assumed to be a combination of electrostatic and van der Waals interaction. A method is presented that determines the charges assigned to beads by matching the electrostatic potential in the atomistic simulation. Lastly a phenomenological model is developed that represents fibrinogen by five beads connected by rigid rods with two hinges. This model only captures the large scale dynamics in the atomistic simulations but can shed light on experimental observations of fibrinogen conformations at inorganic surfaces.

Visualization Techniques For The Analysis Of Network Simulation Results

The Simulation Automation Framework for Experiments (SAFE) streamlines the de- sign and execution of experiments with the ns-3 network simulator. SAFE ensures that best practices are followed throughout the workflow a network simulation study, guaranteeing that results are both credible and reproducible by third parties. Data analysis is a crucial part of this workflow, where mistakes are often made. Even when appearing in highly regarded venues, scientific graphics in numerous network simulation publications fail to include graphic titles, units, legends, and confidence intervals. After studying the literature in network simulation methodology and in- formation graphics visualization, I developed a visualization component for SAFE to help users avoid these errors in their scientific workflow. The functionality of this new component includes support for interactive visualization through a web-based interface and for the generation of high-quality, static plots that can be included in publications. The overarching goal of my contribution is to help users create graphics that follow best practices in visualization and thereby succeed in conveying the right information about simulation results.

Adaptive sensing for target tracking applications

In a statistical inference scenario, the estimation of target signal or its parameters is done by processing data from informative measurements. The estimation performance can be enhanced if we choose the measurements based on some criteria that help to direct our sensing resources such that the measurements are more informative about the parameter we intend to estimate. While taking multiple measurements, the measurements can be chosen online so that more information could be extracted from the data in each measurement process. This approach fits well in Bayesian inference model often used to produce successive posterior distributions of the associated parameter. We explore the sensor array processing scenario for adaptive sensing of a target parameter. The measurement choice is described by a measurement matrix that multiplies the data vector normally associated with the array signal processing. The adaptive sensing of both static and dynamic system models is done by the online selection of proper measurement matrix over time. For the dynamic system model, the target is assumed to move with some distribution and the prior distribution at each time step is changed. The information gained through adaptive sensing of the moving target is lost due to the relative shift of the target. The adaptive sensing paradigm has many similarities with compressive sensing. We have attempted to reconcile the two approaches by modifying the observation model of adaptive sensing to match the compressive sensing model for the estimation of a sparse vector.

Atomic Quantum Simulation of U(N) and SU(N) Abelian Lattice Gauge Theories

Using ultracold alkaline-earth atoms in optical lattices, we construct a quantum simulator for U(N) and SU(N) lattice gauge theories with fermionic matter based on quantum link models. These systems share qualitative features with QCD, including chiral symmetry breaking and restoration at nonzero temperature or baryon density. Unlike classical simulations, a quantum simulator does not suffer from sign problems and can address the corresponding chiral dynamics in real time.

Real-time simulation of large open quantum spin systems driven by dissipation

We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

Real-time simulation of nonequilibrium transport of magnetization in large open quantum spin systems driven by dissipation

Using quantum Monte Carlo, we study the nonequilibrium transport of magnetization in large open strongly correlated quantum spin-12 systems driven by purely dissipative processes that conserve the uniform or staggered magnetization, disregarding unitary Hamiltonian dynamics. We prepare both a low-temperature Heisenberg ferromagnet and an antiferromagnet in two parts of the system that are initially isolated from each other. We then bring the two subsystems in contact and study their real-time dissipative dynamics for different geometries. The flow of the uniform or staggered magnetization from one part of the system to the other is described by a diffusion equation that can be derived analytically.

3D Direct Simulation Monte Carlo Modelling of the Inner Gas Coma of Comet 67P/Churyumov-Gerasimenko: A Parameter Study

Direct Simulation Monte Carlo (DSMC) is a powerful numerical method to study rarefied gas flows such as cometary comae and has been used by several authors over the past decade to study cometary outflow. However, the investigation of the parameter space in simulations can be time consuming since 3D DSMC is computationally highly intensive. For the target of ESA's Rosetta mission, comet 67P/Churyumov-Gerasimenko, we have identified to what extent modification of several parameters influence the 3D flow and gas temperature fields and have attempted to establish the reliability of inferences about the initial conditions from in situ and remote sensing measurements. A large number of DSMC runs have been completed with varying input parameters. In this work, we present the simulation results and conclude on the sensitivity of solutions to certain inputs. It is found that among cases of water outgassing, the surface production rate distribution is the most influential variable to the flow field.

Computer Networks Virtualization with GNS3: Evaluating a solution to optimize resources and achieve a distance learning

Designing educational resources allow students to modify their learning process. In particular, on-line and downloadable educational resources have been successfully used in engineering education the last years [1]. Usually, these resources are free and accessible from web. In addition, they are designed and developed by lecturers and used by their students. But, they are rarely developed by students in order to be used by other students. In this work-in-progress, lecturers and students are working together to implement educational resources, which can be used by students to improve the learning process of computer networks subject in engineering studies. In particular, network topologies to model LAN (Local Area Network) and MAN (Metropolitan Area Network) are virtualized in order to simulate the behavior of the links and nodes when they are interconnected with different physical and logical design.

Adaptive phase measurements in linear optical quantum computation

Photon counting induces an effective non-linear optical phase shift in certain states derived by linear optics from single photons. Although this non-linearity is non-deterministic, it is sufficient in principle to allow scalable linear optics quantum computation (LOQC). The most obvious way to encode a qubit optically is as a superposition of the vacuum and a single photon in one mode-so-called 'single-rail' logic. Until now this approach was thought to be prohibitively expensive (in resources) compared to 'dual-rail' logic where a qubit is stored by a photon across two modes. Here we attack this problem with real-time feedback control, which can realize a quantum-limited phase measurement on a single mode, as has been recently demonstrated experimentally. We show that with this added measurement resource, the resource requirements for single-rail LOQC are not substantially different from those of dual-rail LOQC. In particular, with adaptive phase measurements an arbitrary qubit state a alpha/0 > + beta/1 > can be prepared deterministically.

The practicality of adaptive phase estimation

Adaptive phase estimation is the process of estimating the phase of an electromagnetic field via a continually changing measurement. The measurement is varied in an attempt to optimize it at each moment. In this paper, we show that adaptive phase estimation is more accurate than nonadaptive phase estimation for continuous beams of light even when small time delays in the feedback are present. (c) 2005 Pleiades Publishing Inc.

Adaptive phase measurements for narrowband squeezed beams

We have previously [Phys. Rev. A 65, 043803 (2002)] analyzed adaptive measurements for estimating the continuously varying phase of a coherent beam, and a broadband squeezed beam. A real squeezed beam must have finite photon flux N and hence can be significantly squeezed only over a limited frequency range. In this paper we analyze adaptive phase measurements of this type for a realistic model of a squeezed beam. We show that, provided it is possible to suitably choose the parameters of the beam, a mean-square phase uncertainty scaling as (N/kappa)(-5/8) is possible, where kappa is the linewidth of the beam resulting from the fluctuating phase. This is an improvement over the (N/kappa)(-1/2) scaling found previously for coherent beams. In the experimentally realistic case where there is a limit on the maximum squeezing possible, the variance will be reduced below that for coherent beams, though the scaling is unchanged.

Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids

Fluctuations of liquids at the scales where the hydrodynamic and atomistic descriptions overlap are considered. The importance of these fluctuations for atomistic motions is discussed and examples of their accurate modelling with a multi-space-time-scale fluctuating hydrodynamics scheme are provided. To resolve microscopic details of liquid systems, including biomolecular solutions, together with macroscopic fluctuations in space-time, a novel hybrid atomistic-fluctuating hydrodynamics approach is introduced. For a smooth transition between the atomistic and continuum representations, an analogy with two-phase hydrodynamics is used that leads to a strict preservation of macroscopic mass and momentum conservation laws. Examples of numerical implementation of the new hybrid approach for the multiscale simulation of liquid argon in equilibrium conditions are provided. © 2014 The Author(s) Published by the Royal Society.

The multiscale entropy algorithm and its variants: a review

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