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Register a new userMathematical Modelling of Astrophysical Objects and Processes
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In this review, we present some advanced algorithms and programs used in our scientific school with short description of types of astrophysical systems, which we study. However, we discuss mainly mathematical methods, which may be applied to analysis of signal of any nature - in computer science, engineering, economics, social studies, decision making etc. The variety of types of signals need a diversity of adequate complementary specific methods, in an addition to common algorithms. As an example, one may refer to vibrations, stability of mechanisms. Many mathematical equations are common in Science, Technics and Humanities.
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Partition functions and dissociation equilibrium constants are presented for 291 diatomic molecules for temperatures in the range from near absolute zero to 10000 K, thus providing data for many diatomic molecules of astrophysical interest at low temperature. The calculations are based on molecular spectroscopic data from the book of Huber and Herzberg with significant improvements from the literature, especially updated data for ground states of many of the most important molecules by Irikura. Dissociation energies are collated from compilations of experimental and theoretical values. Partition functions for 284 species of atoms for all elements from H to U are also presented based on data collected at NIST. The calculated data are expected to be useful for modelling a range of low density astrophysical environments, especially star-forming regions, protoplanetary disks, the interstellar medium, and planetary and cool stellar atmospheres. The input data, which will be made available electronically, also provides a possible foundation for future improvement by the community.
The dispersal phase of planet-forming disks via winds driven by irradiation from the central star and/or magnetic fields in the disk itself is likely to play an important role in the formation and evolution of planetary systems. Current theoretical models lack predictive power to adequately constrain observations. We present PRIZMO, a code for evolving thermochemistry in protoplanetary disks capable of being coupled with hydrodynamical and multi-frequency radiative transfer codes. We describe the main features of the code, including gas and surface chemistry, photochemistry, microphysics, and the main cooling and heating processes. The results of a suite of benchmarks, which include photon-dominated regions, slabs illuminated by radiation spectra that include X-ray, and well-established cooling functions evaluated at different temperatures show good agreement both in terms of chemical and thermal structures. The development of this code is an important step to perform quantitative spectroscopy of disk winds, and ultimately the calculation of line profiles, which is urgently needed to shed light on the nature of observed disk winds.
The number of publications of aperture-synthesis images based on optical long-baseline interferometry measurements has recently increased due to easier access to visible and infrared interferometers. The interferometry technique has now reached a technical maturity level that opens new avenues for numerous astrophysical topics requiring milli-arcsecond model-independent imaging. In writing this paper our motivation was twofold: 1) review and publicize emblematic excerpts of the impressive corpus accumulated in the field of optical interferometry image reconstruction; 2) discuss future prospects for this technique by selecting four representative astrophysical science cases in order to review the potential benefits of using optical long baseline interferometers. For this second goal we have simulated interferometric data from those selected astrophysical environments and used state-of-the-art codes to provide the reconstructed images that are reachable with current or soon-to-be facilities. The image reconstruction process was blind in the sense that reconstructors had no knowledge of the input brightness distributions. We discuss the impact of optical interferometry in those four astrophysical fields. We show that image reconstruction software successfully provides accurate morphological information on a variety of astrophysical topics and review the current strengths and weaknesses of such reconstructions. We investigate how to improve image reconstruction and the quality of the image possibly by upgrading the current facilities. We finally argue that optical interferometers and their corresponding instrumentation, existing or to come, with 6 to 10 telescopes, should be well suited to provide images of complex sceneries.
We solve the Tolman-Oppenheimer-Volkoff equation using an equation of state (EoS) calculated in holographic QCD. The aim is to use compact astrophysical objects like neutron stars as an indicator to test holographic equations of state. We first try an EoS from a dense D4/D8/textoverline {D8} model. In this case, however, we could not find a stable compact star, a star satisfying pressure-zero condition with a radius $R$, $p(R)=0$, within a reasonable value of the radius. This means that the EoS from the D4/D8/textoverline {D8} model may not support any stable compact stars or may support one whose radius is very large. This might be due to a deficit of attractive force from a scalar field or two-pion exchange in the D4/D8/textoverline {D8} model. Then, we consider D4/D6 type models with different number of quark flavors, $N_f=1,2,3$. Though the mass and radius of a holographic star is larger than those of normal neutron stars, the D4/D6 type EoS renders a stable compact star.
The goal of AIMS (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm -- interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. AIMS is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.
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