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Coordinated Hydrodynamic and Astrophysical Research, Modeling, and Synthesis (CHARMS)

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<b>Left</b> – Surface density distribution of a forming circumplanetary disk in a protoplanetary disk with the Antares three-dimensional global simulation. A planet of one-Jupiter mass is placed at (x,y) = (5.2,0) au. The color scale is stretched logarithmically. The level boundaries of the nested-grid mesh refinement are shown in white lines. <b>Center</b> – Temperature distribution of the disk obtained with the radiative transfer code Hyperion. The photon sources are the central 4500-K star and an accreting planet of ~1000 K at 5.2 au from the star. The circumplanetary dust is heated up to ~ 1000 K and produces thermal emission. <b>Right</b> – Monochromatic synthetic image corresponding to the 1-mm dust continuum imaging, obtained with Hyperion. The surface brightness is logarithmically stretched in units of MJy/arcsec<sup>2</sup>.

Dust Radiative Transfer on a Global Hydrodynamic Simulation of a Forming Circumplanetary Disk

HIGH-RESOLUTION CO OBSERVATION OF THE CARBON STAR CIT 6

A sample picture based on the radiative transfer code Perspective exploring a very early stage disk formed within the MHD model of Li et al. (2014). The picture shows gas column density and linear polarization component q along the line of sight, inclined 15 degrees from the midplane. The early disk in the model shows a spiral-like shape, presumably created by the magnetic field aligned along the rotational plane of the original cloud. (Väisälä, Shang et al., a work in progress)

Polarization Calculation and Visualization from MHD Simulation Data

Illustration of wind model (left) and attempts to reproduce the velocity pattern of the blue lobe of the I04166 jet (right). The upper part of the left illustration shows two pieces of spherical shell layers, whose velocities point purly in spherical-r directions. The lower part shows how they appear on a position-velocity diagram, where two tooth-like features is seen. Such features greatly resemble the observed velocity pattern in the right. In the upper-right panel we plot the observed CO J=2–1 and CO J=3–2 emissions with blue contours, and the green line segments are model predictions. The color scale in the lower-right panel shows the synthesized CO J=2–1 PV diagram from one of our MHD numerical simulations. The good agreement demonstrates the feasibility of the wind geometry model. The simulated data was convolved with a Gaussian beam of 420 AU FWHM before extracting the PV diagram to better mimic the observation result.

Ejection History of Protostellar Outflow IRAS 04166+2706

$Density plots in log scale from simulations of two-temperature outflow model. (Left) Mosaic of simulations demonstrating effects of varying temperature and magnetization degree. Panel indices of (a) to (c) shows decreasing magnetic field strength, and (1) to (3) shows increasing wind temperature. The central axial jet is less collimated and the shell structure is widened when magnetic force is relatively unimportant. (Right) Comparisons that demonstrates the effect of poloidal magnetic field. The top panel is run with poloidal field and the lower without. Thick solid line is where wind mass fraction is 1%, and thick dashed line is where bulk velocities equal the ambient sound speed. The shell is mode corrugated in cases without poloidal field (Wang et al. 2015)$

A Two-temperature Model of Magnetized Protostellar Outflows

Visualization of RT Simulation

Distribution of the logarithm of the mass density ρ and velocity field (unit vectors) on the equatorial plane, for Models I (left panel, non-rotating) and J (right, rotating) that include both ambipolar diffusion and (enhanced) Ohmic dissipation for magnetic decoupling at small radii. Again, both models show filamentary structures in the inner protostellar accretion flow driven by magnetic interchange instability.

Protostellar Accretion Flows Destabilized by Magnetic Flux Redistribution

<b>Effects of temperature and magnetization on molecular outflows:</b> the structure of the base of outflows at 1000 yr is shown with different physical conditions. Panels (a) to (c) shows the Alfvénic Mach number from 6, 30, to 90 [decreasing magnetic field strength]; and (1) to (3) shows the wind temperature from 10 K, 400 K, to 2000 K [increasing wind temperature]. These corresponds to different plasma beta parameter (β<sub>plasma</sub> ≣ 8πa<sup>2</sup>ρ/B<sup>2</sup>) from 0.001 to 46. The central axial jet is less collimated and the shell structure is widened when β<sub>plasma</sub> increases. In these cases, the poloidal magnetic field in the toroid is not included.

Two-Temperature Model for Magnetized Protostellar Outflows

CHARMS is the acronym for "Coordinated Hydrodynamic and Astrophysical Research, Modeling, and Synthesis", an ASIAA/TIARA initiative that focuses on bridging the theory and numerical astrophysics with cutting-edge observational astrophysics. In the era of high-sensitivity and high-resolution spectroimaging instrumentations such as ALMA, consistent treatment of radiation processes based on numerical simulations is required for sensible comparisons between theory and observations. In achieving the goal, software packages that solve hydrodynamic/magnetohydrodynamic equations, consider chemical evolution, and calculate radiative transfer processes are being actively developed under the CHARMS initiative.

Since 2008, CHARMS has established three main development directions, which include the hydrodynamic/magnetohydrodynamic simulation package (ZeusTW), the hydrodynamic simulation package with the abilities of timely chemical evolution (KM1/KM2), and the simulation package for astrophysical radiative transfer (SPARX). These packages have been applied to several science projects including the collapse of protostellar cores and the formation of circumstellar disks, formation and evolution of lowmass protostellar jets and outflows, formation of protoplanets and circumplanetary disks, physics in the photon-dominated regions, and the evolution of low-mass stars beyond main sequence. We anticipate growing needs of numerical modeling, data analysis, and data interpretation in these and other research fields, and will continue to provide support for those demands.