Polarization observations reveal scale-dependent differences in magnetic field morphology between molecular clouds and clumps, a velocity-dispersion correlation, and unreliable field-strength estimates that contradict flux conservation.
Improving the Accuracy of Magnetic Field Tracing by Velocity Gradients: Principal Component Analysis
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abstract
Tracing of the magnetic field with Velocity Gradient Technique (VGT) allows observers to probe magnetic field directions with spectroscopic data. In this paper, we employ the method of Principal Component Analysis (PCA) to extract the spectroscopic information most valuable for VGT. By using synthetic observation data from numerical simulations, we show that PCA acts in a way similar to spatial filtering along the velocity axis. We study both subsonic and supersonic simulations and show that with the PCA filtering the tracing of magnetic fields by the VGT is significantly improved. Using 21 cm GALFA data, we demonstrate that the PCA filtering improves the alignment of the velocity gradients and the Planck dust polarization.
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RAT alignment boosted by B-star radiation plus DG alignment reproduces super-Serkowski spectra in HD 30614 and HD 204827 while standard RAT alone fits Serkowski spectra in HD 37903 and HD 161056.
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Characterising magnetic fields at the onset of star cluster formation: From giant molecular clouds to infrared dark clumps
Polarization observations reveal scale-dependent differences in magnetic field morphology between molecular clouds and clumps, a velocity-dispersion correlation, and unreliable field-strength estimates that contradict flux conservation.
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Grain Alignment and Dust Evolution Physics with Polarisation (GRADE-POL). II. On the physical basis of Serkowski and super-Serkowski polarisation spectra
RAT alignment boosted by B-star radiation plus DG alignment reproduces super-Serkowski spectra in HD 30614 and HD 204827 while standard RAT alone fits Serkowski spectra in HD 37903 and HD 161056.