Direct numerical simulation of the turbulent flow around a Flettner rotor.

The three-dimensional turbulent flow around a Flettner rotor, i.e. an engine-driven rotating cylinder in an atmospheric boundary layer, is studied via direct numerical simulations (DNS) for three different rotation speeds ([Formula: see text]).

Programming Quantum Neural Networks on NISQ Systems: An Overview of Technologies and Methodologies.

Noisy Intermediate-Scale Quantum (NISQ) systems and associated programming interfaces make it possible to explore and investigate the design and development of quantum computing techniques for Machine Learning (ML) applications. Among the most recent quantum ML approaches, Quantum Neural Networks (QNN) emerged as an important tool for data analysis. With the QNN advent, higher-level programming interfaces for QNN have been developed.

Artificial intelligence in virtual screening: Models versus experiments.

A typical drug discovery project involves identifying active compounds with significant binding potential for selected disease-specific targets. Experimental high-throughput screening (HTS) is a traditional approach to drug discovery, but is expensive and time-consuming when dealing with huge chemical libraries with billions of compounds. The search space can be narrowed down with the use of reliable computational screening approaches.

In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst.

In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up to 2048 cores on KTH's Beskow Cray XC40 supercomputer and assess in situ visualization's impact on the Nek5000 performance.

A Review on Parallel Virtual Screening Softwares for High-Performance Computers.

Drug discovery is the most expensive, time-demanding, and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from large-sized chemical libraries. The lead compounds should have high-affinity binding and specificity for a target associated with a disease, and, in addition, they should have favorable pharmacodynamic and pharmacokinetic properties (grouped as ADMET properties). Overall, drug discovery is a multivariable optimization and can be carried out in supercomputers using a reliable scoring function which is a measure of binding affinity or inhibition potential of the drug-like compound.

The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged as a new essential tool to solve various challenging problems, including computing linear systems arising from PDEs, a task for which several traditional methods exist. In this work, we focus first on evaluating the potential of PINNs as linear solvers in the case of the Poisson equation, an omnipresent equation in scientific computing.

Electron and Ion Dynamics of the Solar Wind Interaction with a Weakly Outgassing Comet.

Using a 3D fully kinetic approach, we disentangle and explain the ion and electron dynamics of the solar wind interaction with a weakly outgassing comet. We show that, to first order, the dynamical interaction is representative of a four-fluid coupled system. We self-consistently simulate and identify the origin of the warm and suprathermal electron distributions observed by ESA's Rosetta mission to comet 67P/Churyumov-Gerasimenko and conclude that a detailed kinetic treatment of the electron dynamics is critical to fully capture the complex physics of mass-loading plasmas.

Rippled Quasiperpendicular Shock Observed by the Magnetospheric Multiscale Spacecraft.

Collisionless shock nonstationarity arising from microscale physics influences shock structure and particle acceleration mechanisms. Nonstationarity has been difficult to quantify due to the small spatial and temporal scales. We use the closely spaced (subgyroscale), high-time-resolution measurements from one rapid crossing of Earth's quasiperpendicular bow shock by the Magnetospheric Multiscale (MMS) spacecraft to compare competing nonstationarity processes.

Idle waves in high-performance computing.

The vast majority of parallel scientific applications distributes computation among processes that are in a busy state when computing and in an idle state when waiting for information from other processes. We identify the propagation of idle waves through processes in scientific applications with a local information exchange between the two processes. Idle waves are nondispersive and have a phase velocity inversely proportional to the average busy time.

Electromagnetic particle-in-cell simulations of the solar wind interaction with lunar magnetic anomalies.

We present the first three-dimensional fully kinetic and electromagnetic simulations of the solar wind interaction with lunar crustal magnetic anomalies (LMAs). Using the implicit particle-in-cell code iPic3D, we confirm that LMAs may indeed be strong enough to stand off the solar wind from directly impacting the lunar surface forming a mini-magnetosphere, as suggested by spacecraft observations and theory. In contrast to earlier magnetohydrodynamics and hybrid simulations, the fully kinetic nature of iPic3D allows us to investigate the space charge effects and in particular the electron dynamics dominating the near-surface lunar plasma environment.

Čerenkov emission of quasiparallel whistlers by fast electron phase-space holes during magnetic reconnection.

Kinetic simulations of magnetotail reconnection have revealed electromagnetic whistlers originating near the exhaust boundary and propagating into the inflow region. The whistler production mechanism is not a linear instability, but rather is Čerenkov emission of almost parallel whistlers from localized moving clumps of charge (finite-size quasiparticles) associated with nonlinear coherent electron phase space holes. Whistlers are strongly excited by holes without ever growing exponentially.

Energetics of kinetic reconnection in a three-dimensional null-point cluster.

We perform three-dimensional particle-in-cell simulations of magnetic reconnection with multiple magnetic null points. Magnetic field energy conversion into kinetic energy is about five times higher than in traditional Harris sheet configuration. More than 85% of initial magnetic field energy is transferred to particle energy during 25 reversed ion cyclofrequencies.

Jet deflection by very weak guide fields during magnetic reconnection.

Previous 2D simulations of reconnection using a standard model of initially antiparallel magnetic fields have detected electron jets outflowing from the x point into the ion outflow exhausts. Associated with these jets are extended "outer electron diffusion regions." New PIC simulations with an ion to electron mass ratio as large as 1836 (an H(+) plasma) now show that the jets are strongly deflected and the outer electron diffusion region is broken up by a very weak out-of-plane magnetic guide field, even though the diffusion rate itself is unchanged.