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Grain alignment and dust evolution physics with polarisation (GRADE-POL). I. Dust polarisation modelling for isolated starless cores

Le Ngoc Tram, Thiem Hoang, Alex Lazarian, Daniel Seifried, B-G Andersson, Thushara G. S. Pillai, Bao Truong, Pham Ngoc Diep, Lapo Fanciullo

TL;DR

GRADE-POL develops a forward-modeling framework to interpret multi-wavelength dust polarisation in isolated starless cores through magnetically enhanced radiative torque (MRAT) alignment of oblate Astrodust grains. The model couples a starless-core density and radiation field profile with size- and shape-dependent grain alignment (via $f(a)$, $a_{ m align}$, and MRAT) to predict $p_{ m ext}/A_{ m V}$ and $p_{ m em}$ across optical to submillimetre wavelengths. Application to the Pipe-109 core shows that perfect alignment of large grains ($a \gg a_{ m align}$) together with grain growth (increasing $a_{ m max}$) and elongation is needed to reproduce observed polarisation in $R$-band, $H$-band, and $870\,\mu$m. The results provide first evidence that MRAT operates in starless cores and that anisotropic grain growth accompanies MRAT, with observable signatures in the polarisation spectra. The work establishes GRADE-POL as a tool to constrain MRAT physics and grain evolution using multi-wavelength polarimetry.

Abstract

The polarisation of light induced by aligned interstellar dust serves as a significant tool in investigating cosmic magnetic fields, dust properties, and poses a challenge in characterising the polarisation of the cosmic microwave background and other sources. To establish dust polarisation as a reliable tool, the physics of the grain alignment process needs to be studied thoroughly. The Magnetically enhanced Radiative Torque (MRAT) alignment is the only mechanism that can induce highly efficient alignment of grains with magnetic fields required by polarisation observations of the diffuse interstellar medium. Our numerical modelling of dust polarisation using the MRAT theory demonstrated that the alignment efficiency of starlight polarisation ($p_{\rm ext}/A_{\rm V}$) and the degree of thermal dust polarisation ($p_{\rm em}$) first decrease slowly with increasing visual extinction ($A_{\rm V}$) and then falls steeply as $\propto A^{-1}_{\rm V}$ at large $A_{\rm V}$ due to the loss of grain alignment, which explains the phenomenon known as polarisation holes. Visual extinction at the transition from shallow to steep slope ($A^{\rm loss}_{\rm V}$) increases with the maximum grain size. By applying physical profiles suitable for a starless core 109 in the Pipe Nebula (Pipe-109), our model successfully reproduces the existing observations of starlight polarisation at R-band ($0.65\,μ$m) and H-band ($1.65\,μ$m), as well as emission polarisation at submillimetre ($870\,μ$m). Successful modelling of observational data requires perfect alignment of large grains as evidence of the MRAT mechanism, and larger maximum size with higher elongation at higher $A_{\rm V}$. The latter reveals the first evidence for the new model of anisotropic grain growth induced by magnetic grain alignment.

Grain alignment and dust evolution physics with polarisation (GRADE-POL). I. Dust polarisation modelling for isolated starless cores

TL;DR

GRADE-POL develops a forward-modeling framework to interpret multi-wavelength dust polarisation in isolated starless cores through magnetically enhanced radiative torque (MRAT) alignment of oblate Astrodust grains. The model couples a starless-core density and radiation field profile with size- and shape-dependent grain alignment (via , , and MRAT) to predict and across optical to submillimetre wavelengths. Application to the Pipe-109 core shows that perfect alignment of large grains () together with grain growth (increasing ) and elongation is needed to reproduce observed polarisation in -band, -band, and m. The results provide first evidence that MRAT operates in starless cores and that anisotropic grain growth accompanies MRAT, with observable signatures in the polarisation spectra. The work establishes GRADE-POL as a tool to constrain MRAT physics and grain evolution using multi-wavelength polarimetry.

Abstract

The polarisation of light induced by aligned interstellar dust serves as a significant tool in investigating cosmic magnetic fields, dust properties, and poses a challenge in characterising the polarisation of the cosmic microwave background and other sources. To establish dust polarisation as a reliable tool, the physics of the grain alignment process needs to be studied thoroughly. The Magnetically enhanced Radiative Torque (MRAT) alignment is the only mechanism that can induce highly efficient alignment of grains with magnetic fields required by polarisation observations of the diffuse interstellar medium. Our numerical modelling of dust polarisation using the MRAT theory demonstrated that the alignment efficiency of starlight polarisation () and the degree of thermal dust polarisation () first decrease slowly with increasing visual extinction () and then falls steeply as at large due to the loss of grain alignment, which explains the phenomenon known as polarisation holes. Visual extinction at the transition from shallow to steep slope () increases with the maximum grain size. By applying physical profiles suitable for a starless core 109 in the Pipe Nebula (Pipe-109), our model successfully reproduces the existing observations of starlight polarisation at R-band (m) and H-band (m), as well as emission polarisation at submillimetre (m). Successful modelling of observational data requires perfect alignment of large grains as evidence of the MRAT mechanism, and larger maximum size with higher elongation at higher . The latter reveals the first evidence for the new model of anisotropic grain growth induced by magnetic grain alignment.

Paper Structure

This paper contains 26 sections, 20 equations, 12 figures, 1 table.

Figures (12)

  • Figure 1: Coordinate system of the starless core on the (x,z)-plane with the ${\hat{z}}$ direction towards the observer. The position in the plane of the sky is defined by $r_{0}$. Each line of sight, $\hat{s}$, corresponds to a distinct visual extinction, $A_{\rm V}$, calculated from the gas volume density profile along this direction. At a location $r_{i}$ on the sight line, the physical parameters (such as gas density, temperature, and radiation field) are assumed to be uniform on the dashed circle.
  • Figure 2: (Top panel): Full map on the plane of the sky ($\hat{x}\hat{y}$ plane) of the line-of-sight visual extinction. (Bottom panel): Alignment size along the line of sight ($\hat{x}\hat{z}$ plane). We adopt $n_{0}=5\times 10^{5}\,\rm cm^{-3}$, $r_{\rm flat}=0.024\,\rm pc$, $\alpha=2$, $U_{0}=1$, $\gamma=0.3$, oblate grains (axial ratio of 1.4) with $a_{\rm max}=1\,\mu$m, $\beta=-3.5$, and $f_{\rm max}=1$. This setup mimics the scale of the Pipe-109 starless core, whose data will be used later in this work.
  • Figure 3: Polarisation spectrum $p_{\rm ext}/A_{\rm V}$ vs. $\lambda$ of starlight dust polarisation for different lines of sight ($A_{\rm V}$), shown for maximum grain sizes of 0.25$\,\mu$m (left panel) and 0.5$\,\mu$m (right panel). For $\lambda\leq 10\,\mu$m, the spectral feature is broader for larger maximum grain size. When $A_{\rm V}$ is low, smaller $a_{\rm max}$ yields a greater amplitude; however, this relationship inverts as $A_{\rm V}$ increases. The oblate grains with an axial ratio of 1.4 are adopted.
  • Figure 4: Relation between $p/A_{\rm V}$ and $A_{\rm V}$ for starlight polarisation at optical wavelength (R band, left panel) and near-IR (H band, right panel) wavelengths. Different lines represent different maximum grain sizes. The dots mark locations where the slope changes from $<-1$ to $\simeq -1$. A slope of $-1$ indicates the complete loss of grain alignment.
  • Figure 5: (Left panel): Relation between $A^{\rm loss}_{\rm V}$, where the grain completely loses its alignment, and maximum grain size. This plot is shown for several commonly used wavelengths from optical to near-IR. (Right panel): Relationship between the wavelength of peak starlight polarisation, $\lambda_{\rm max}$, and $A_{\rm V}$. The value of $\lambda_{\rm max}$ increases initially and then remains steady as $A_{\rm V}$ increases.
  • ...and 7 more figures