Computational Physics on Graphics Processing Units

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012, Helsinki, Finland, June 10-13, 201

Sparse Modeling for Image and Vision Processing

In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. In statistics and machine learning, the sparsity principle is used to perform model selection---that is, automatically selecting a simple model among a large collection of them. In signal processing, sparse coding consists of representing data with linear combinations of a few dictionary elements. Subsequently, the corresponding tools have been widely adopted by several scientific communities such as neuroscience, bioinformatics, or computer vision. The goal of this monograph is to offer a self-contained view of sparse modeling for visual recognition and image processing. More specifically, we focus on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.Comment: 205 pages, to appear in Foundations and Trends in Computer Graphics and Visio

Present and Future of Gravitational Wave Astronomy

The first detection on Earth of a gravitational wave signal from the coalescence of a binary black hole system in 2015 established a new era in astronomy, allowing the scientific community to observe the Universe with a new form of radiation for the first time. More than five years later, many more gravitational wave signals have been detected, including the first binary neutron star coalescence in coincidence with a gamma ray burst and a kilonova observation. The field of gravitational wave astronomy is rapidly evolving, making it difficult to keep up with the pace of new detector designs, discoveries, and astrophysical results. This Special Issue is, therefore, intended as a review of the current status and future directions of the field from the perspective of detector technology, data analysis, and the astrophysical implications of these discoveries. Rather than presenting new results, the articles collected in this issue will serve as a reference and an introduction to the field. This Special Issue will include reviews of the basic properties of gravitational wave signals; the detectors that are currently operating and the main sources of noise that limit their sensitivity; planned upgrades of the detectors in the short and long term; spaceborne detectors; a data analysis of the gravitational wave detector output focusing on the main classes of detected and expected signals; and implications of the current and future discoveries on our understanding of astrophysics and cosmology

Grid generation for the solution of partial differential equations

A general survey of grid generators is presented with a concern for understanding why grids are necessary, how they are applied, and how they are generated. After an examination of the need for meshes, the overall applications setting is established with a categorization of the various connectivity patterns. This is split between structured grids and unstructured meshes. Altogether, the categorization establishes the foundation upon which grid generation techniques are developed. The two primary categories are algebraic techniques and partial differential equation techniques. These are each split into basic parts, and accordingly are individually examined in some detail. In the process, the interrelations between the various parts are accented. From the established background in the primary techniques, consideration is shifted to the topic of interactive grid generation and then to adaptive meshes. The setting for adaptivity is established with a suitable means to monitor severe solution behavior. Adaptive grids are considered first and are followed by adaptive triangular meshes. Then the consideration shifts to the temporal coupling between grid generators and PDE-solvers. To conclude, a reflection upon the discussion, herein, is given

The interactions between gold nanoparticles and their self-assembly

Gold nanoparticles (AuNPs) are one of the most promising building blocks to fabricate versatile nanostructures. Such nanostructures have the great potential to enable new gold-based nanomaterials or nanocomposites with specific properties by precisely controlling the interactions (potential energies and/or forces) between them. In other words, the interactions between AuNPs are therefore regarded as one of the key factors governing particles’ self-assembly process that can drive multiple AuNPs to form ordered structures as required. Quantifying the interactions between them and understanding of their self-assembly process are of great importance and yet still challenging. In this study, molecular dynamics (MD) simulations are performed to calculate the interactions (e.g., potential energies) between AuNPs. The MD results reveal that a more effective force model between AuNPs can be developed as a function of their surface separation compared with the conventional Hamaker equation. In addition, MD simulations examine several effects (i.e., particle size, shape, rotation, surface patch, surfactant, as well as configuration) on their interactions. The results demonstrate that the different impacts of these factors (e.g., the hindrance of surfactant). Apart from spherical gold nanoparticles, interactions between gold nanorods (AuNRs) are also be quantified by MD simulations. The interparticle forces of AuNRs can be expressed as a function of their surface separation and the rotation angle since the rotational movement is applied on AuNR. Further, the MD-derived interparticle force models of gold nanospheres are integrated into discrete element method (DEM) to explore their self-assembly process. To the best of our knowledge, this might be the first time that the MD-based interparticle force models are integrated into DEM to explore the self-assembly process of gold nanoparticles. The results show that ordered nanostructures are ultimately constructed. Specifically, the mean coordination number (CN) of AuNPs (3 nm in size) is up to 5.99 and two major large clusters is observed under the simulation conditions at the equilibrated state. The completion of this study not only allows us to evaluate the interactions between AuNPs by MD simulation, but profoundly, the MD-DEM coupling approach opens a new window to unfold the self-assembly process of AuNPs

A numerical method for fluid-structure interactions of slender rods in turbulent flow

This thesis presents a numerical method for the simulation of fluid-structure interaction (FSI) problems on high-performance computers. The proposed method is specifically tailored to interactions between Newtonian fluids and a large number of slender viscoelastic structures, the latter being modeled as Cosserat rods. From a numerical point of view, such kind of FSI requires special techniques to reach numerical stability. When using a partitioned fluid-structure coupling approach this is usually achieved by an iterative procedure, which drastically increases the computational effort. In the present work, an alternative coupling approach is developed based on an immersed boundary method (IBM). It is unconditionally stable and exempt from any global iteration between the fluid part and the structure part. The proposed FSI solver is employed to simulate the flow over a dense layer of vegetation elements, usually designated as canopy flow. The abstracted canopy model used in the simulation consists of 800 strip-shaped blades, which is the largest canopy-resolving simulation of this type done so far. To gain a deeper understanding of the physics of aquatic canopy flows the simulation data obtained are analyzed, e.g., concerning the existence and shape of coherent structures