176 research outputs found
Supersonic turbulence in 3D isothermal flow collision
Colliding supersonic bulk flows shape observable properties and internal
physics of various astrophysical objects, like O-star winds, molecular clouds,
galactic sheets, binaries, or gamma-ray bursts. Using numerical simulations, we
show that the bulk flows leave a clear imprint on the collision zone, its mean
properties and the turbulence it naturally develops. Our model setup consists
of 3D head-on colliding isothermal hydrodynamical flows with Mach numbers
between 2 and 43. Simulation results are in line with expectations from
self-similarity: root mean square Mach numbers (Mrms) scale linearly with
upstream Mach numbers, mean densities remain limited to a few times the
upstream density. The density PDF is not log-normal. The turbulence is
inhomogeneous: weaker in the zone center than close to the confining shocks. It
is anisotropic: while Mrms is generally supersonic, Mrms transverse to the
upstream flow is always subsonic. We argue that uniform, isothermal, head-on
colliding flows generally disfavor isotropic, supersonic turbulence. The
anisotropy carries over to other quantities like the density variance - Mach
number relation. Structure functions differ depending on whether they are
computed along a line-of-sight perpendicular or parallel to the upstream flow.
We suggest that such line-of-sight effects should be kept in mind when
interpreting turbulence characteristics derived from observations.Comment: 20 pages, 14 figures, 4 tables, accepted by Astronomy and
Astrophysic
The energetics of relativistic magnetic reconnection: ion-electron repartition and particle distribution hardness
Collisionless magnetic reconnection is a prime candidate to account for
flare-like or steady emission, outflow launching, or plasma heating, in a
variety of high-energy astrophysical objects, including ones with relativistic
ion-electron plasmas. But the fate of the initial magnetic energy in a
reconnection event remains poorly known: what is the amount given to kinetic
energy, the ion/electron repartition, and the hardness of the particle
distributions? We explore these questions with 2D particle-in-cell simulations
of ion-electron plasmas. We find that 45 to 75% of the total initial magnetic
energy ends up in kinetic energy, this fraction increasing with the inflow
magnetization. Depending on the guide field strength, ions get from 30 to 60%
of the total kinetic energy. Particles can be separated into two populations
that only weakly mix: (i) particles initially in the current sheet, heated by
its initial tearing and subsequent contraction of the islands; and (ii)
particles from the background plasma that primarily gain energy via the
reconnection electric field when passing near the X-point. Particles (ii) tend
to form a power-law with an index , that
depends mostly on the inflow Alfv\'en speed and magnetization
of species , with for electrons to for increasing .
The highest particle Lorentz factor, for ions or electrons, increases roughly
linearly with time for all the relativistic simulations. This is faster, and
the spectra can be harder, than for collisionless shock acceleration. We
discuss applications to microquasar and AGN coronae, to extragalactic jets, and
to radio lobes. We point out situations where effects such as Compton drag or
pair creation are important.Comment: 15 pages, submitted to A&
Lithium depletion in solar-like stars: effect of overshooting based on realistic multi-dimensional simulations
We study lithium depletion in low-mass and solar-like stars as a function of
time, using a new diffusion coefficient describing extra-mixing taking place at
the bottom of a convective envelope. This new form is motivated by
multi-dimensional fully compressible, time implicit hydrodynamic simulations
performed with the MUSIC code. Intermittent convective mixing at the convective
boundary in a star can be modeled using extreme value theory, a statistical
analysis frequently used for finance, meteorology, and environmental science.
In this letter, we implement this statistical diffusion coefficient in a
one-dimensional stellar evolution code, using parameters calibrated from
multi-dimensional hydrodynamic simulations of a young low-mass star. We propose
a new scenario that can explain observations of the surface abundance of
lithium in the Sun and in clusters covering a wide range of ages, from
50 Myr to 4 Gyr. Because it relies on our physical model of convective
penetration, this scenario has a limited number of assumptions. It can explain
the observed trend between rotation and depletion, based on a single additional
assumption, namely that rotation affects the mixing efficiency at the
convective boundary. We suggest the existence of a threshold in stellar
rotation rate above which rotation strongly prevents the vertical penetration
of plumes and below which rotation has small effects. In addition to providing
a possible explanation for the long standing problem of lithium depletion in
pre-main sequence and main sequence stars, the strength of our scenario is that
its basic assumptions can be tested by future hydrodynamic simulations.Comment: 7 pages, 3 figures, Accepted for publication in ApJ Letter
Apar-T: code, validation, and physical interpretation of particle-in-cell results
We present the parallel particle-in-cell (PIC) code Apar-T and, more
importantly, address the fundamental question of the relations between the PIC
model, the Vlasov-Maxwell theory, and real plasmas.
First, we present four validation tests: spectra from simulations of thermal
plasmas, linear growth rates of the relativistic tearing instability and of the
filamentation instability, and non-linear filamentation merging phase. For the
filamentation instability we show that the effective growth rates measured on
the total energy can differ by more than 50% from the linear cold predictions
and from the fastest modes of the simulation.
Second, we detail a new method for initial loading of Maxwell-J\"uttner
particle distributions with relativistic bulk velocity and relativistic
temperature, and explain why the traditional method with individual particle
boosting fails.
Third, we scrutinize the question of what description of physical plasmas is
obtained by PIC models. These models rely on two building blocks:
coarse-graining, i.e., grouping of the order of p~10^10 real particles into a
single computer superparticle, and field storage on a grid with its subsequent
finite superparticle size. We introduce the notion of coarse-graining dependent
quantities, i.e., quantities depending on p. They derive from the PIC plasma
parameter Lambda^{PIC}, which we show to scale as 1/p. We explore two
implications. One is that PIC collision- and fluctuation-induced thermalization
times are expected to scale with the number of superparticles per grid cell,
and thus to be a factor p~10^10 smaller than in real plasmas. The other is that
the level of electric field fluctuations scales as 1/Lambda^{PIC} ~ p. We
provide a corresponding exact expression.
Fourth, we compare the Vlasov-Maxwell theory, which describes a phase-space
fluid with infinite Lambda, to the PIC model and its relatively small Lambda.Comment: 24 pages, 14 figures, accepted in Astronomy & Astrophysic
An ensemble-based approach to climate reconstructions
Data assimilation is a promising approach to obtain climate reconstructions that are both consistent with observations of the past and with our understanding of the physics of the climate system as represented in the climate model used. Here, we investigate the use of ensemble square root filtering (EnSRF) – a technique used in weather forecasting – for climate reconstructions. We constrain an ensemble of 29 simulations from an atmosphere-only general circulation model (GCM) with 37 pseudo-proxy temperature time series. Assimilating spatially sparse information with low temporal resolution (semi-annual) improves the representation of not only temperature, but also other surface properties, such as precipitation and even upper air features such as the intensity of the northern stratospheric polar vortex or the strength of the northern subtropical jet. Given the sparsity of the assimilated information and the limited size of the ensemble used, a localisation procedure is crucial to reduce "overcorrection" of climate variables far away from the assimilated information
COLLABORATIVE VALIDATION OF USER-CONTRIBUTED DATA USING A GEOSPATIAL BLOCKCHAIN APPROACH: THE SIMILE CASE STUDY
Abstract. Internet decentralization nowadays represents a critical topic to be addressed. It protects the users' privacy, promotes data ownership, eliminates single points of failure and data censorship. An element that has an important role in decentralization is blockchain technology. Although blockchain has revolutionised sectors like the financial one with Bitcoin, there are still some fields where it needs to be further developed. One of these is geospatial data sharing and citizen science, where features like decentralization, immutability and transparency are needed. This study focuses on the description of a decentralized application developed specifically for geospatial data-point sharing and validation. As an example, the Informative System for the Integrated Monitoring of Insubric Lakes and their Ecosystems (SIMILE) is used. This application is developed in the Velas blockchain infrastructure and implements a combination of a Discrete Global Grid System (DGGS) with smart contracts. Two types of smart contracts were created, a cell and a registry smart contract. The cell smart contracts are individual for each DGGS partition and contain the list of observations present in a specific area. The registry smart contracts keep track of all the DGGS cells added to the system. Currently, SIMILE observations are validated by public authorities, which requires time that is not always available. Therefore, a fully working prototype was developed to solve this. Here users can add and manage personal observations and validate the ones belonging to other users. This work demonstrates the feasibility of creating decentralized applications for geographical data validation as a citizen science solution
One-dimensional thermal pressure-driven expansion of a pair cloud into an electron-proton plasma
Recently a filamentation instability was observed when a laser-generated pair
cloud interacted with an ambient plasma. The magnetic field it drove was strong
enough to magnetize and accelerate the ambient electrons. It is of interest to
determine if and how pair cloud-driven instabilities can accelerate ions in the
laboratory or in astrophysical plasma. For this purpose, the expansion of a
localized pair cloud with the temperature 400 keV into a cooler ambient
electron-proton plasma is studied by means of one-dimensional particle-in-cell
(PIC) simulations. The cloud's expansion triggers the formation of electron
phase space holes that accelerate some protons to MeV energies. Forthcoming
lasers might provide the energy needed to create a cloud that can accelerate
protons.Comment: 5 pages 4 figures, accepted for publication in Physics of Plasma
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