Revisiting Kinematic Fast Dynamo in 3-dimensional magnetohydrodynamic plasmas: Dynamo transition from non-Helical to Helical flows

Dynamos wherein magnetic field is produced from velocity fluctuations are fundamental to our understanding of several astrophysical and/or laboratory phenomena. Though fluid helicity is known to play a key role in the onset of dynamo action, its effect is yet to be fully understood. In this work, a fluid flow proposed recently [Yoshida et al. Phys. Rev. Lett. 119, 244501 (2017)] is invoked such that one may inject zero or finite fluid helicity using a control parameter, at the beginning of the simulation. Using a simple kinematic fast dynamo model, we demonstrate unambiguously the strong dependency of short scale dynamo on fluid helicity. In contrast to conventional understanding, it is shown that fluid helicity does strongly influence the physics of short scale dynamo. To corroborate our findings, late time magnetic field spectra for various values of injected fluid helicity is presented along with rigorous ``geometric'' signatures of the 3D magnetic field surfaces, which shows a transition from ``untwisted'' to ``twisted'' sheet to ``cigar'' like configurations. It is also shown that one of the most studied ABC dynamo model is not the ``fastest'' dynamo model for problems with lower magnetic Reynolds number. This work brings out, for the first time, the role of fluid helicity in moving from ``non-dynamo'' to ``dynamo'' regime systematically

Three Dimensional Pseudo-Spectral Compressible Magnetohydrodynamic GPU Code for Astrophysical Plasma Simulation

This paper presents the benchmarking and scaling studies of a GPU accelerated three dimensional compressible magnetohydrodynamic code. The code is developed keeping an eye to explain the large and intermediate scale magnetic field generation is cosmos as well as in nuclear fusion reactors in the light of the theory given by Eugene Newman Parker. The spatial derivatives of the code are pseudo-spectral method based and the time solvers are explicit. GPU acceleration is achieved with minimal code changes through OpenACC parallelization and use of NVIDIA CUDA Fast Fourier Transform library (cuFFT). NVIDIAs unified memory is leveraged to enable over-subscription of the GPU device memory for seamless out-of-core processing of large grids. Our experimental results indicate that the GPU accelerated code is able to achieve upto two orders of magnitude speedup over a corresponding OpenMP parallel, FFTW library based code, on a NVIDIA Tesla P100 GPU. For large grids that require out-of-core processing on the GPU, we see a 7x speedup over the OpenMP, FFTW based code, on the Tesla P100 GPU. We also present performance analysis of the GPU accelerated code on different GPU architectures - Kepler, Pascal and Volta

Long time fate of two-dimensional incompressible high Reynolds number Navier-Stokes turbulence: A quantitative comparison between theory and simulation

Predicting the long time or late time states of two-dimensional incompressible, high Reynolds number, slowly decaying turbulence has been one of the long-standing problems. Using ``point vortices'' as ``inviscid'' building blocks, which do not respect incompressibility, statistical mechanical models conserving only total energy and zero total circulation result in the well-known sinh-Poisson relation between vorticity and stream function. On the other hand, statistical mechanics of ``inviscid patch'' vortices, which respects incompressibility by conserving regions of zero and nonzero vorticity, predicts a generalized relaxed state, which has never been systematically compared with direct numerical simulations (DNS). In this study, starting from highly packed regions of nonzero initial vorticity, we demonstrate using high resolution, high Reynolds number DNS that the late time states agree with predictions from patch vortex models. As total circulation is reduced or diluted, we show that late time states of our DNS systematically and unambiguously lead to the sinh-Poisson relationship between vorticity and stream function. We believe that our quantitative findings solve one of the long-standing problems in two-dimensional turbulence