GRChombo : Numerical Relativity with Adaptive Mesh Refinement

In this work, we introduce GRChombo: a new numerical relativity code which incorporates full adaptive mesh refinement (AMR) using block structured Berger-Rigoutsos grid generation. The code supports non-trivial "many-boxes-in-many-boxes" mesh hierarchies and massive parallelism through the Message Passing Interface (MPI). GRChombo evolves the Einstein equation using the standard BSSN formalism, with an option to turn on CCZ4 constraint damping if required. The AMR capability permits the study of a range of new physics which has previously been computationally infeasible in a full 3+1 setting, whilst also significantly simplifying the process of setting up the mesh for these problems. We show that GRChombo can stably and accurately evolve standard spacetimes such as binary black hole mergers and scalar collapses into black holes, demonstrate the performance characteristics of our code, and discuss various physics problems which stand to benefit from the AMR technique.Comment: 48 pages, 24 figure

The Nondeterministic Waiting Time Algorithm: A Review

We present briefly the Nondeterministic Waiting Time algorithm. Our technique for the simulation of biochemical reaction networks has the ability to mimic the Gillespie Algorithm for some networks and solutions to ordinary differential equations for other networks, depending on the rules of the system, the kinetic rates and numbers of molecules. We provide a full description of the algorithm as well as specifics on its implementation. Some results for two well-known models are reported. We have used the algorithm to explore Fas-mediated apoptosis models in cancerous and HIV-1 infected T cells

Disclosure, Trust and Persuasion in Insurance Markets

This high-stakes experiment investigates the effect on buyers of mandatory disclosures concerning an insurance policy's value for money (the claims ratio) and the seller's commission. These information disclosures have virtually no effect despite most buyers claiming to value such information. Instead, our data reveal that whether the subject is generally trusting plays an important role. Trust is clearly associated with greater willingness to pay for insurance. Unlike in previous work, trust in our setting is not about obligations being fulfilled. The contract is complete, simple and the possibility of breach is negligible. However, as for much B2C insurance marketing, face-to-face selling plays a crucial role in our experimental design. Trusting buyers are more suggestible, so take advice more readily and buy more insurance, although they are no more risk averse than the uninsured. Moreover, trusting buyers feel less pressured by sellers, and are more confident in their decisions which suggests that they are easier to persuade. Therefore, in markets where persuasion is important, public policy designed to increase consumer information is likely to be ineffective.insurance selling, trust, persuasion

The role of high- and low-temperature ocean crust alteration for the marine calcium budget

Calcium (Ca) is a key element for the understanding of the chemical evolution of the ocean and for the global climate on long geological time scales. This is because Ca is interacting with the carbon cycle and is a major constituent of continental weathering. Beside continental runoff, mid-ocean ridges are of quantitative importance for the marine Ca elemental and isotope budget. Variations of hydrothermal circulation of seawater through oceanic crust have been recognized to play a significant role for the oceanic Ca mass and isotope balance. Hydrothermal activity leads to a chemical alteration of the circulating seawater at low- and high temperatures during water-rock interaction, the formation of Ca-bearing minerals, and during phase separation. Within the framework of the subproject 'CARLA' in the 'Special Priority Program SPP 1144' Ca isotope ratios (d44/40Ca) in hydrothermal fluids sampled from the Logatchev hydrothermal field (15°N/45°W) and the Ascension area (4 11°S) have been investigated in detail in order to further constrain the global Ca cycling

Design and optimization of a portable LQCD Monte Carlo code using OpenACC

The present panorama of HPC architectures is extremely heterogeneous, ranging from traditional multi-core CPU processors, supporting a wide class of applications but delivering moderate computing performance, to many-core GPUs, exploiting aggressive data-parallelism and delivering higher performances for streaming computing applications. In this scenario, code portability (and performance portability) become necessary for easy maintainability of applications; this is very relevant in scientific computing where code changes are very frequent, making it tedious and prone to error to keep different code versions aligned. In this work we present the design and optimization of a state-of-the-art production-level LQCD Monte Carlo application, using the directive-based OpenACC programming model. OpenACC abstracts parallel programming to a descriptive level, relieving programmers from specifying how codes should be mapped onto the target architecture. We describe the implementation of a code fully written in OpenACC, and show that we are able to target several different architectures, including state-of-the-art traditional CPUs and GPUs, with the same code. We also measure performance, evaluating the computing efficiency of our OpenACC code on several architectures, comparing with GPU-specific implementations and showing that a good level of performance-portability can be reached.Comment: 26 pages, 2 png figures, preprint of an article submitted for consideration in International Journal of Modern Physics