The Cosmic Symphony: Magnetic Fields and Turbulence Across Clouds, Galaxies, to Galaxy Clusters
ORAL · Invited
Abstract
To measure 3D magnetic fields in the interstellar medium, this talk presents two innovative techniques based on turbulence anisotropy: the Velocity Gradient Technique and the physics-informed convolutional neural network. The talk will demonstrate how these techniques serve as transformative tools for probing 3D magnetic fields, advancing our understanding of the intricate interplay between turbulence and magnetism across cosmic scales. The new turbulence-based approach overcomes the limitations of traditional polarization measurements. It provides unprecedented insights into the magnetic field structure of various astrophysical systems, from accretion disks to the halos of galaxy clusters. It opens avenues for separating CMB polarization arising from enigmatic cosmological B-modes from the galactic foreground. Combined with numerical modeling, this research yields unique insights into the physics of matter accretion to supermassive black holes, star formation, and cosmic ray propagation.
–
Publication: 1. (Hu et al. 2018) Hu, Y., Yuen, K. H., & Lazarian, A. 2018, MNRAS, 480, 1333. doi:10.1093/mnras/sty1807.<br>2. (Hu et al. 2020a) Hu, Y., Lazarian, A., & Yuen, K. H. 2020, ApJ, 897, 123. doi:10.3847/1538-4357/ab9948.<br>3. (Hu et al. 2020b) Hu, Y., Yuen, K. H., & Lazarian, A. 2020, ApJ, 888, 96. doi:10.3847/1538-4357/ab60a5.<br>4. (Hu et al. 2020c) Hu, Y., Lazarian, A., Li, Y., et al. 2020, ApJ, 901, 162. doi:10.3847/1538-4357/abb1c3.<br>5. (Hu et al. 2021a) Hu, Y., Lazarian, A., & Stanimirovic, S. 2021, ApJ, 912, 2. doi:10.3847/1538-4357/abedb7.<br>6. (Hu et al. 2021b) Hu, Y., Xu, S., & Lazarian, A. 2021, ApJ, 911, 37. doi:10.3847/1538-4357/abea18<br>7. (Hu et al. 2022a) Hu, Y., Federrath, C., Xu, S., et al. 2022, MNRAS, 513, 2100. doi:10.1093/mnras/stac972.<br>8. (Hu et al. 2022b) Hu, Y., Xu, S., Stone, J. M., et al. 2022, ApJ, 941, 133. doi:10.3847/1538-4357/ac9ebc.<br>9. (Hu et al. 2022c) Hu, Y., Lazarian, A., & Xu, S. 2022, MNRAS, 512, 2111. doi:10.1093/mnras/stac319.<br>10. (Hu et al. 2022d) Hu, Y., Lazarian, A., Beck, R., et al. 2022, ApJ, 941, 92. doi:10.3847/1538-4357/ac9df0.<br>11. (Hu et al. 2022e) Hu, Y., Lazarian, A., & Wang, Q. D. 2022, MNRAS, 511, 829. doi:10.1093/mnras/stac159.<br>12. (Hu et al. 2022f) Hu, Y., Lazarian, A., & Wang, Q. D. 2022, MNRAS, 513, 3493. doi:10.1093/mnras/stac1060.<br>13. (Hu et al. 2023a) Hu, Y., Lazarian, A., Alina, D., et al. 2023, MNRAS, 524, 2994. doi:10.1093/mnras/stad1924.<br>14. (Hu & Lazarian 2023a) Hu, Y. & Lazarian, A. 2023, MNARS 519, 3736. doi:10.1093/mnras/stac3744.<br>15. (Hu & Lazarian 2023b) Hu, Y. & Lazarian, A. 2023, MNRAS, 524, 4431. doi:10.1093/mnras/stad2158.<br>16. (Hu et al. 2023b) Hu, Y. & Lazarian, A. 2023, MNRAS, 524, 2379. doi:10.1093/mnras/stad1996.<br>17. (Hu et al. 2024a) Hu, Y., Xu, S., Arzamasskiy, L., et al. 2024, MNRAS, 527, 3945. doi:10.1093/mnras/stad3493.<br>18. (Hu et al. 2024b) Hu, Y., Stuardi, C., Lazarian, A., et al. 2024, Nature Communications, 15, 1006. doi:10.1038/s41467-024-45164-8.<br>19. (Hu et al. 2024c) Hu, Y., Lazarian, A., Wu, Y., et al. 2024, MNRAS, 527, 11240. doi:10.1093/mnras/stad3766.<br>20. (Liu et al. 2024) Liu, M., Hu, Y., & Lazarian, A. 2024, MNRAS, 530, 1066. doi:10.1093/mnras/stae863.
Presenters
-
Yue Hu
Institute for Advanced Study
Authors
-
Yue Hu
Institute for Advanced Study