MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics

Numerical modeling of the singlet proximity effect in a superconductor-ferromagnet trilayer

We investigate superconductor-insulator-ferromagnet-superconductor Josephson junctions using the quasiclassical Green's functional theory in the “dirty limit,” where the elastic scattering length ℓ is much shorter than the characteristic decay length in the ferromagnet. We manipulate the governing Usadel equations for entry into numerical analysis and develop a numerical model to explore the behavior of the superconducting Green's functions in the trilayer, avoiding the linearizing approximation usually found in the literature. We then review the results of the numerical calculation for the behavior of the Green's function under the variation of the ferromagnet thickness df, the ferromagnet's internal magnetization strength h, the strength of the proximity effect γ, and the interface transparency γBi. These results are compared to analytical, numerical, and experimental results in the existing literature. We close with suggestions for future research

MADNESS: a multiresolution, adaptive numerical environment for scientific simulation

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision that are based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics

QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images