371 research outputs found
A performance portable, fully implicit Landau collision operator with batched linear solvers
Modern accelerators use hierarchically parallel programming models that
enable massive multithreading within a processing element (PE), with multiple
PEs per device driven by traditional processes. Batching is a technique for
exposing PE-level parallelism in algorithms that previously ran on entire
processes or multiple threads within a single MPI process. Kinetic
discretizations of magnetized plasmas, for example, advance the Vlasov-Maxwell
system, which is then followed by a fully implicit time advance of a collision
operator. These collision advances are independent at each spatial point and
are well suited to batch processing.
This paper builds on previous work on a high-performance, fully nonlinear
Landau collision operator by batching the linear solver, as well as batching
the spatial point problems and adding new support for multiple grids for highly
multiscale, multi-species problems. An anisotropic relaxation verification test
that agrees well with previous published results and analytical solutions is
presented. The performance of the NVIDIA A100 and AMD MI250X nodes is
evaluated, with a detailed hardware utilization analysis on the A100. For
portability, the entire Landau operator time advance is implemented in Kokkos
and is available in the PETSc numerical library
Neutrinos from horizon to sub-galactic scales
A first determination of the mass scale set by the lightest neutrino remains a crucial outstanding challenge for cosmology and particle physics, with profound implications for the history of the Universe and physics beyond the Standard Model. In this thesis, we present the results from three methodological papers and two applications that contribute to our understanding of the cosmic neutrino background.
First, we introduce a new method for the noise-suppressed evaluation of neutrino phase-space statistics. Its primary application is in cosmological N-body simulations, where it reduces the computational cost of simulating neutrinos by orders of magnitude without neglecting their nonlinear evolution. Second, using a recursive formulation of Lagrangian perturbation theory, we derive higher-order neutrino corrections and show that these can be used for the accurate and consistent initialisation of cosmological neutrino simulations. Third, we present a new code for the initialisation of neutrino particles, accounting both for relativistic effects and the full Boltzmann hierarchy. Taken together, these papers demonstrate that with the combination of the methods described therein, we can accurately simulate the evolution of the neutrino background over 13.8 Gyr from the linear and ultra-relativistic regime at down to the non-relativistic yet nonlinear regime at . Moreover, they show that the accuracy of large-scale structure predictions can be controlled at the sub-percent level needed for a neutrino mass determination.
In a first application of these methods, we present a forecast for direct detection of the neutrino background, taking into account the gravitational enhancement (or indeed suppression) of the local density due to the Milky Way and the observed large-scale structure within 200 Mpc/h. We determine that the large-scale structure is more important than the Milky Way for neutrino masses below 0.1 eV, predict the orientation of the neutrino dipole, and study small-scale anisotropies. We predict that the angular distribution of neutrinos is anti-correlated with the projected matter density, due to the capture or deflection of neutrinos by massive objects along the line of sight.
Finally, we present the first results from a new suite of hydrodynamical simulations, which includes the largest ever simulation with neutrinos and galaxies. We study the extent to which variations in neutrino mass can be treated independently of astrophysical processes, such as feedback from supernovae and black holes. Our findings show that baryonic feedback is weakly dependent on neutrino mass, with feedback being stronger for models with larger neutrino masses. By studying individual dark matter halos, we attribute this effect to the increased baryon density relative to cold dark matter and a reduction in the binding energies of halos. We show that percent-level accurate modelling of the matter power spectrum in a cosmologically interesting parameter range is only possible if the cosmology-dependence of feedback is taken into account
The Effective Mean-Free-Path of the Solar Wind
The high temperature and rarefied ionised gas (plasma) that constitutes the corona of the sun escapes the gravitational bound and flows out into interplanetary space. This plasma is called the solar wind. It is characterised by a long collision mean-free-path (i.e., weakly collisional); it is not in thermodynamic equilibrium. While the plasma is ultimately governed by a kinetic equation, it does appear that the solar wind is described by fluid equations, where it is assumed to be at equilibrium. This is in stark contradiction to the long collision mean-free-path. The suggestion is that collisionless relaxation processes are playing a strong role in dictating the dynamics of the solar wind. These processes are wave-particle interactions that cause the plasma to relax towards equilibrium, i.e., they are effective collision processes. This thesis takes a novel route to measure the effective mean-free-path of the solar wind, by modelling compressive fluctuations of arbitrary effective mean-free-path, and making a robust comparison to solar wind observations. The effective mean-free-path is measured to be approximately 10 times shorter than the collisional mean-free-path. It is shown to be consistent with and justify decades of past solar wind research that use fluid equations. The theory for the numerical model is derived from first principles and is shown to coincide with previous results, and draw together many concepts about compressive plasma waves. The solar wind dataset used in this thesis was not previously used for scientific analysis, so verification of the data quality is demonstrated. In addition, data analysis tools are constructed to measure some of the potential effective collision mechanisms. The analysis is tested on simulation data, to verify the accuracy, by measuring key quantities in identifying the relevant role of various effective collision mechanisms. The analysis of the numerical simulation data is shown to be satisfactory and can be employed on spacecraft data. This measurement resolves a long-standing debate on the utility and accuracy of fluid equations in studying the solar wind. The direct measurement of the effective mean-free-path is important for the field of plasma physics because it dictates the transport and thermodynamics of weakly collisional plasmas
Noncollisional plasmoid instability based on a gyrofluid and gyrokinetic integrated approach
In this work, the development of two-dimensional current sheets with respect
to tearing-modes, in collisionless plasmas with a strong guide field, is
analysed. During their non-linear evolution, these thin current sheets can
become unstable to the formation of plasmoids, which allows the magnetic
reconnection process to reach high reconnection rates. We carry out a detailed
study of the impact of a finite , which also implies finite electron
Larmor radius effects, on the collisionless plasmoid instability. This study is
conducted through a comparison of gyrofluid and gyrokinetic simulations. The
comparison shows in general a good capability of the gyrofluid models in
predicting the plasmoid instability observed with gyrokinetic simulations. We
show that the effects of promotes the plasmoid growth. The impact of
the closure applied during the derivation of the gyrofluid model is also
studied through the comparison of the energy variation
Exponential integrators: tensor structured problems and applications
The solution of stiff systems of Ordinary Differential Equations (ODEs), that typically arise after spatial discretization of many important evolutionary Partial Differential Equations (PDEs), constitutes a topic of wide interest in numerical analysis. A prominent way to numerically integrate such systems involves using exponential integrators. In general, these kinds of schemes do not require the solution of (non)linear systems but rather the action of the matrix exponential and of some specific exponential-like functions (known in the literature as phi-functions). In this PhD thesis we aim at presenting efficient tensor-based tools to approximate such actions, both from a theoretical and from a practical point of view, when the problem has an underlying Kronecker sum structure. Moreover, we investigate the application of exponential integrators to compute numerical solutions of important equations in various fields, such as plasma physics, mean-field optimal control and computational chemistry. In any case, we provide several numerical examples and we perform extensive simulations, eventually exploiting modern hardware architectures such as multi-core Central Processing Units (CPUs) and Graphic Processing Units (GPUs). The results globally show the effectiveness and the superiority of the different approaches proposed
Kinetic stability of Chapman-Enskog plasmas
In this paper, we investigate the kinetic stability of classical, collisional
plasma - that is, plasma in which the mean-free-path of constituent
particles is short compared to the length scale over which fields and bulk
motions in the plasma vary macroscopically, and the collision time is short
compared to the evolution time. Fluid equations are typically used to describe
such plasmas, since their distribution functions are close to being Maxwellian.
The small deviations from the Maxwellian distribution are calculated via the
Chapman-Enskog (CE) expansion in , and determine macroscopic
momentum and heat fluxes in the plasma. Such a calculation is only valid if the
underlying CE distribution function is stable at collisionless length scales
and/or time scales. We find that at sufficiently high plasma , the CE
distribution function can be subject to numerous microinstabilities across a
wide range of scales. For a particular form of the CE distribution function
arising in magnetised plasma, we provide a detailed analytic characterisation
of all significant microinstabilities, including peak growth rates and their
associated wavenumbers. Of specific note is the discovery of several new
microinstabilities, including one at sub-electron-Larmor scales (the 'whisper
instability') whose growth rate in some parameter regimes is large compared to
other instabilities. Our approach enables us to construct the kinetic stability
maps of classical, two-species collisional plasma in terms of , the
electron inertial scale and . This work is of general consequence
in emphasising the fact that high- collisional plasmas can be
kinetically unstable; for strongly magnetised CE plasmas, the condition for
instability is . In this situation, the determination of
transport coefficients via the standard CE approach is not valid.Comment: 182 pages total (99 main text, remaining appendices), 31 figure
2022 Review of Data-Driven Plasma Science
Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required
Magnetic flutter effect on validated edge turbulence simulations
Small magnetic fluctuations () are intrinsically
present in a magnetic confinement plasma due to turbulent currents. While the
perpendicular transport of particles and heat is typically dominated by
fluctuations of the electric field, the parallel stream of plasma is affected
by fluttering magnetic field lines. In particular through electrons, this
indirectly impacts the turbulence dynamics. Even in low beta conditions, we
find that turbulent transport can be reduced by more than a factor
2 when magnetic flutter is included in our validated edge turbulence
simulations of L-mode ASDEX Upgrade. The primary reason for this is the
stabilization of drift-Alfv\'en-waves, which reduces the phase shifts of
density and temperature fluctuations with respect to potential fluctuations.
This stabilization can be qualitatively explained by linear analytical theory,
and appreciably reinforced by the flutter nonlinearity. As a secondary effect,
the steeper temperature gradients and thus higher increase the impact
of the ion-temperature-gradient mode on overall turbulent transport. With
increasing beta, the stabilizing effect on turbulence increases,
balancing the destabilization by induction, until direct electromagnetic
perpendicular transport is triggered. We conclude that including flutter is
crucial for predictive edge turbulence simulations
A Two-dimensional Numerical Study of Ion-Acoustic Turbulence
We investigate the linear and nonlinear evolution of the ion-acoustic
instability in a collisionless plasma via two-dimensional (2D2V) Vlasov-Poisson
numerical simulations. We initialize the system in a stable state and gradually
drive it towards instability with an imposed, weak external electric field,
thus avoiding super-critical initial conditions that are physically
unrealizable. The nonlinear evolution of ion-acoustic turbulence (IAT) is
characterized in detail, including the particles' distribution functions,
particle heating, (two-dimensional) wave spectrum, and the resulting anomalous
resistivity. An important result is that no steady saturated nonlinear state is
ever reached in our simulations: strong ion heating suppresses the instability,
which implies that the anomalous resistivity associated with IAT is transient
and short-lived. Electron-acoustic waves (EAWs) are triggered during the late
nonlinear evolution of the system, caused by strong modifications to the
particle distribution induced by IAT
Energy Conversion in Plasmas out of Local Thermodynamic Equilibrium: A Kinetic Theory Perspective
The study of energy conversion in collisionless plasmas that are not in local thermodynamic equilibrium (LTE) is at the leading edge of plasma physics research. Plasma constituents in such systems can exhibit highly structured phase space densities that deviate significantly from that of a Maxwellian. A standard approach has emerged in recent years for investigating energy conversion between bulk flow and thermal energy in collisionless plasmas using the non-LTE generalization of the first law of thermodynamics. The primary focus is placed on pressure-strain interaction (PS) term, with a particular emphasis on its non-LTE piece called Pi − D. Recent studies have found that Pi − D can be negative, which makes its identification as collisionless viscous heating counterintuitive. A kinetic understanding of Pi − D has been limited. We argue that the non-LTE generalization of the first law of thermodynamics and subsequent attempts to extend thermodynamics overlooks the kinetic aspects associated with phase space densities having arbitrary shapes that can deviate significantly from a Maxwellian. Only changes in work due to compression that changes the zeroth moment of the phase space density, i.e., the number density, and Pi − D and heat flux which change the second moment, i.e., effective temperature are considered by the non-LTE generalization of the first law of thermodynamics. However, it remains agnostic to energy conversion associated with changes to any higher moment of the phase space density. We address these limitations by first developing a kinetic understanding of Pi − D and introducing an alternative decomposition of the PS term in Cartesian coordinates which separates the physics of converging/ diverging flows from shear deformation. We further find that in magnetic field-aligned coordinates, the PS term can be decomposed into eight groups of terms, each corresponding to a different physical mechanism. Lastly, we develop a first-principles theory of the energy conversion associated with all higher moments of the phase space density. Using particle-in-cell simulations of a well understood non-LTE system, i.e., two-dimensional antiparallel magnetic reconnection, we first examine the decompositions of PS term in both Cartesian and magnetic field-aligned coordinates. This enables us to identify the predominant mechanisms contributing to positive and negative PS terms during reconnection, thereby facilitating the interpretation of numerical and observational data. Additionally, simulation results reveal that energy conversion associated with higher-order moments can be locally significant by being a substantial fraction of the internal energy and even surpassing it in regions characterized by strongly non-LTE phase space densities. These results may be useful in numerous plasma settings, such as heliospheric, planetary, and astrophysical plasmas, and for other non-LTE phenomenon such as turbulence, shocks and wave-particle interactions
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