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Register a new userThe Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained
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The Pencil Code is a highly modular physics-oriented simulation code that can be adapted to a wide range of applications. It is primarily designed to solve partial differential equations (PDEs) of compressible hydrodynamics and has lots of add-ons ranging from astrophysical magnetohydrodynamics (MHD) to meteorological cloud microphysics and engineering applications in combustion. Nevertheless, the framework is general and can also be applied to situations not related to hydrodynamics or even PDEs, for example when just the message passing interface or input/output strategies of the code are to be used. The code can also evolve Lagrangian (inertial and noninertial) particles, their coagulation and condensation, as well as their interaction with the fluid.
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This paper describes the design and implementation of our new multi-group, multi-dimensional radiation hydrodynamics (RHD) code Fornax and provides a suite of code tests to validate its application in a wide range of physical regimes. Instead of focusing exclusively on tests of neutrino radiation hydrodynamics relevant to the core-collapse supernova problem for which Fornax is primarily intended, we present here classical and rigorous demonstrations of code performance relevant to a broad range of multi-dimensional hydrodynamic and multi-group radiation hydrodynamic problems. Our code solves the comoving-frame radiation moment equations using the M1 closure, utilizes conservative high-order reconstruction, employs semi-explicit matter and radiation transport via a high-order time stepping scheme, and is suitable for application to a wide range of astrophysical problems. To this end, we first describe the philosophy, algorithms, and methodologies of Fornax and then perform numerous stringent code tests, that collectively and vigorously exercise the code, demonstrate the excellent numerical fidelity with which it captures the many physical effects of radiation hydrodynamics, and show excellent strong scaling well above 100k MPI tasks.
Context: Stellar clusters are benchmarks for theories of star formation and evolution. The high precision parallax data of the Gaia mission allows significant improvements in the distance determination to stellar clusters and its stars. In order to have accurate and precise distance determinations, systematics like the parallax spatial correlations need to be accounted for, especially for stars in small sky regions. Aims: Provide the astrophysical community with a free and open code designed to simultaneously infer cluster parameters (i.e. distance and size) and the distances to its stars using Gaia parallax measurements. It includes cluster oriented prior families and is specifically designed to deal with the Gaia parallax spatial correlations. Methods: A Bayesian hierarchical model is created to allow the inference of both the cluster parameters and distances to its stars. Results: Using synthetic data that mimics Gaia parallax uncertainties and spatial correlations, we observe that our cluster oriented prior families result in distance estimates with smaller errors than those obtained with an exponentially decreasing space density prior. In addition, the treatment of the parallax spatial correlations minimizes errors in the estimated cluster size and stellar distances and avoids the underestimation of uncertainties. Although neglecting the parallax spatial correlations has no impact on the accuracy of cluster distance determinations, it underestimates the uncertainties and may result in measurements that are incompatible with the true value. Conclusions: The combination of prior knowledge with the treatment of Gaia parallax spatial correlations produces accurate (error <10%) and trustworthy estimates (i.e. true values contained within the 2$sigma$ uncertainties) of clusters distances for clusters up to ~5 kpc, and cluster sizes for clusters up to ~1 kpc.
Aims: We developed a new method of estimating the stellar parameters Teff, log g, [M/H], and elemental abundances. This method was implemented in a new code, SP_Ace (Stellar Parameters And Chemical abundances Estimator). This is a highly automated code suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R=2,000-20,000). Methods: After the astrophysical calibration of the oscillator strengths of 4643 absorption lines covering the wavelength ranges 5212-6860AA and 8400-8924AA, we constructed a library that contains the equivalent widths (EW) of these lines for a grid of stellar parameters. The EWs of each line are fit by a polynomial function that describes the EW of the line as a function of the stellar parameters. The coefficients of these polynomial functions are stored in a library called the $GCOG$ library. SP_Ace, a code written in FORTRAN95, uses the GCOG library to compute the EWs of the lines, constructs models of spectra as a function of the stellar parameters and abundances, and searches for the model that minimizes the $chi^2$ deviation when compared to the observed spectrum. The code has been tested on synthetic and real spectra for a wide range of signal-to-noise and spectral resolutions. Results: SP_Ace derives stellar parameters such as Teff, log g, [M/H], and chemical abundances of up to ten elements for low to medium resolution spectra of FGK-type stars with precision comparable to the one usually obtained with spectra of higher resolution. Systematic errors in stellar parameters and chemical abundances are presented and identified with tests on synthetic and real spectra. Stochastic errors are automatically estimated by the code for all the parameters. A simple Web front end of SP_Ace can be found at http://dc.g-vo.org/SP_ACE, while the source code will be published soon.
We provide a detailed description of the Chimera code, a code developed to model core collapse supernovae in multiple spatial dimensions. The core collapse supernova explosion mechanism remains the subject of intense research. Progress to date demonstrates that it involves a complex interplay of neutrino production, transport, and interaction in the stellar core, three-dimensional stellar core fluid dynamics and its associated instabilities, nuclear burning, and the foundational physics of the neutrino-stellar core weak interactions and the equations of state of all stellar core constituents -particularly, the nuclear equation of state associated with nucleons, both free and bound in nuclei. Chimera, by incorporating detailed neutrino transport, realistic neutrino-matter interactions, three-dimensional hydrodynamics, realistic nuclear, leptonic, and photonic equations of state, and a nuclear reaction network, along with other refinements, can be used to study the role of neutrino radiation, hydrodynamic instabilities, and a variety of input physics in the explosion mechanism itself. It can also be used to compute observables such as neutrino signatures, gravitational radiation, and the products of nucleosynthesis associated with core collapse supernovae. The code contains modules for neutrino transport, multidimensional compressible hydrodynamics, nuclear reactions, a variety of neutrino interactions, equations of state, and modules to provide data for post-processing observables such as the products of nucleosynthesis, and gravitational radiation. Chimera is an evolving code, being updated periodically with improved input physics and numerical refinements. We detail here the current version of the code, from which future improvements will stem, which can in turn be described as needed in future publications.
We present Phantom, a fast, parallel, modular and low-memory smoothed particle hydrodynamics and magnetohydrodynamics code developed over the last decade for astrophysical applications in three dimensions. The code has been developed with a focus on stellar, galactic, planetary and high energy astrophysics and has already been used widely for studies of accretion discs and turbulence, from the birth of planets to how black holes accrete. Here we describe and test the core algorithms as well as modules for magnetohydrodynamics, self-gravity, sink particles, H_2 chemistry, dust-gas mixtures, physical viscosity, external forces including numerous galactic potentials as well as implementations of Lense-Thirring precession, Poynting-Robertson drag and stochastic turbulent driving. Phantom is hereby made publicly available.
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