Lagrangian fluid approach for the modeling of peculiarities of the interstellar dust distribution in the astrospheres/heliosphere

Abstract

Interstellar dust penetrates into the heliosphere/astrosphere due to relative motion of the Sun and the local interstellar medium (LISM). Inside the heliosphere/astrosphere and at the heliospheric boundaries, where the solar/stellar wind interacts with LISM, distribution of the interstellar dust is modified due to an action of electromagnetic forces, the solar gravitation and radiation pressure. In this paper we show that the distribution of the interstellar dust particles in the heliosphere has peculiarities of high density layers. In order to understand the nature of the peculiarities Osiptsov’s Lagrangian method has been employed and developed for the case when the force acting on the particles has discontinuity as it is for the electromagnetic force at the helioshperic current sheet. In the result of the modeling we demonstrate existence of multiple layers of high density of the interstellar dust located at 0.03 - 10 AU north and south with respect to the heliospheric current sheet.

Effects of dispersion of the dust velocity in the LISM on the interstellar dust distribution inside the heliosphere

“…In this paper we demonstrated that the singularities of the ISD density in the heliosphere, discovered using the Lagrangian approach in Mishchenko et al (2020), can also be found by the Monte-Carlo simulations. This requires super-small computational cells.…”

Effects of dispersion of the dust velocity in the LISM on the interstellar dust distribution inside the heliosphere

“…In this paper we demonstrated that the singularities of the ISD density in the heliosphere, discovered using the Lagrangian approach in Mishchenko et al (2020), can also be found by the Monte-Carlo simulations. This requires super-small computational cells.…”

The unexpected role of heliospheric boundaries in facilitating interstellar dust penetration at 1–5 AU

“…The ISD number density increases in the vicinity of these caustics. This effect was discussed by Mishchenko et al (2020) for the stationary case and by Godenko & Izmodenov (2024) for the nonstationary case. These areas of the ISD accumulation appear in the plane Z = 0 for the two considered models, but the locations, shapes, and sizes of these areas differ significantly.…”

Robust interpolation for dispersed gas‐droplet flows using statistical learning with the fully Lagrangian approach

“…For $$$ St=10 $$$ this behaviour is also observed, with the fold lines exhibiting a higher number density than for $$$ St=1 $$$, and the trailing edge of the droplet field containing both regions of lower number density and distinct layers of folds as observed from the discontinuities in the droplet field in Figure 5E. The successful capturing of these fold layers shows that kernel regression is able to retain this level of detail from the FLA number density data, and account for this phenomenon at a far lower computational cost than direct trajectory methods 15 …”

“…The successful capturing of these fold layers shows that kernel regression is able to retain this level of detail from the FLA number density data, and account for this phenomenon at a far lower computational cost than direct trajectory methods. 15 The x profiles of the number density field in Figure 5B,D,F exhibit the different levels of variation in number density that the kernel regression procedure is able to reproduce. For intervals where there is no data for a given profile, the number density is zero as there are no droplets present at that point.…”

Effects of dispersion of the dust velocity in the LISM on the interstellar dust distribution inside the heliosphere

“…In this paper we demonstrated that the singularities of the ISD density in the heliosphere, discovered using the Lagrangian approach in Mishchenko et al (2020), can also be found by the Monte-Carlo simulations. This requires super-small computational cells.…”

The unexpected role of heliospheric boundaries in facilitating interstellar dust penetration at 1–5 AU

“…The ISD number density increases in the vicinity of these caustics. This effect was discussed by Mishchenko et al (2020) for the stationary case and by Godenko & Izmodenov (2024) for the nonstationary case. These areas of the ISD accumulation appear in the plane Z = 0 for the two considered models, but the locations, shapes, and sizes of these areas differ significantly.…”

Robust interpolation for dispersed gas‐droplet flows using statistical learning with the fully Lagrangian approach

“…For $$$ St=10 $$$ this behaviour is also observed, with the fold lines exhibiting a higher number density than for $$$ St=1 $$$, and the trailing edge of the droplet field containing both regions of lower number density and distinct layers of folds as observed from the discontinuities in the droplet field in Figure 5E. The successful capturing of these fold layers shows that kernel regression is able to retain this level of detail from the FLA number density data, and account for this phenomenon at a far lower computational cost than direct trajectory methods 15 …”

“…The successful capturing of these fold layers shows that kernel regression is able to retain this level of detail from the FLA number density data, and account for this phenomenon at a far lower computational cost than direct trajectory methods. 15 The x profiles of the number density field in Figure 5B,D,F exhibit the different levels of variation in number density that the kernel regression procedure is able to reproduce. For intervals where there is no data for a given profile, the number density is zero as there are no droplets present at that point.…”

Effects of dispersion of the dust velocity in the LISM on the interstellar dust distribution inside the heliosphere

“…In this paper we demonstrated that the singularities of the ISD density in the heliosphere, discovered using the Lagrangian approach in Mishchenko et al (2020), can also be found by the Monte-Carlo simulations. This requires super-small computational cells.…”

The unexpected role of heliospheric boundaries in facilitating interstellar dust penetration at 1–5 AU

“…The ISD number density increases in the vicinity of these caustics. This effect was discussed by Mishchenko et al (2020) for the stationary case and by Godenko & Izmodenov (2024) for the nonstationary case. These areas of the ISD accumulation appear in the plane Z = 0 for the two considered models, but the locations, shapes, and sizes of these areas differ significantly.…”

Robust interpolation for dispersed gas‐droplet flows using statistical learning with the fully Lagrangian approach

“…For $$$ St=10 $$$ this behaviour is also observed, with the fold lines exhibiting a higher number density than for $$$ St=1 $$$, and the trailing edge of the droplet field containing both regions of lower number density and distinct layers of folds as observed from the discontinuities in the droplet field in Figure 5E. The successful capturing of these fold layers shows that kernel regression is able to retain this level of detail from the FLA number density data, and account for this phenomenon at a far lower computational cost than direct trajectory methods 15 …”

“…The successful capturing of these fold layers shows that kernel regression is able to retain this level of detail from the FLA number density data, and account for this phenomenon at a far lower computational cost than direct trajectory methods. 15 The x profiles of the number density field in Figure 5B,D,F exhibit the different levels of variation in number density that the kernel regression procedure is able to reproduce. For intervals where there is no data for a given profile, the number density is zero as there are no droplets present at that point.…”