Magnetic Braking of the Rotational Molecular Cloud Cores, Revisited

Document Type : Research Paper

Authors

Department of Theoretical Physics, Faculty of Science, University of Mazandaran, P. O. Box 47416-95447, Babolsar, Iran

Abstract

The phenomenon of magnetic braking is one of the significant physical effects of the magnetic field in rotating molecular clouds. Here, we revisit the work of Nakano (1989). In addition to receiving his results, we investigate the effects of the density ratio (between periphery of the core to its  mean density), and the density condensations around the core. We consider the density profile of the surrounding medium as r-η, where r is the distance from the core center and η is a constant between 0 and 4. Regarding the presence of some dense regions around the molecular cloud cores, a Gaussian function is added to the density profile to represent these condensations in the surrounding medium. The numerical method is used in the Laplace space to ascertain the dependency of the angular velocity of the core to the time. The results show that for larger η values, the time scale of the magnetic braking increases. Moreover, the presence of condensation does not have a significant effect on the magnetic braking. Also, the the results show that the magnetic braking being stronger with increasing density ratio. This increasing indicates that the magnetic field is more firmly bonded to the bulk materials. This effect strengthens the magnetic tension force and slows down the core faster that indicates the importance of the magnetic braking. The results show that increasing density slope and/or decreasing density ratio are somewhat effective in weakening the magnetic braking and resolving its catastrophic effect. 

Keywords

References

[1] Hennebelle, P., & Inutsuka, S.-i. 2019, Frontiers in Astronomy and Space Sciences, 6, 5.
[2] Mestel, L. 1965, QJRAS, 6, 161.
[3] Gillis, J., Mestel, L., & Paris, R. B. 1974, Ap&SS, 27, 167.
[4] Mouschovias, T. C., & Paleologou, E. V. 1980, ApJ, 237, 877.
[5] Konigl, A. 1987, ApJ, 320, 726.
[6] Basu, S., & Mouschovias, T. C. 1994, ApJ, 432, 720.
[7] Allen, A., Li, Z.-Y., Shu F. H., 2003, ApJ, 599, 363.
[8] Arfken, G. B., Weber, H. J., 2005, Mathematical Methods for Physicists. Elsevier Academic Press, New York.
[9] Aguilar-Marin, P., Chavez-Bacilio, M., & Jauregui-Rosas, S. 2018, Eur. J. Phys., 39, 035204.
[10] Boss, A. P. 2007, ApJ, 685, 1136.
[11] Boss, A. P. 2009, ApJ, 97, 1940.
[12] Codella, C., Cabrit, S., Gueth, F., Podio, L., Leurini, S., Bachiller, R., Gusdorf, A., Lefloch, B., & Nisini, B. 2014, A&A, 568, L5.
[13] Dapp, W. B., & Basu, S. 2010, A&A, .521, 4.
[14] Dapp, W. B., Basu, S., & Kunz, M. W. 2012, A&A, .541, 18.
[15] Fehér, O., Tóth, L. V., Ward-Thompson, D., Kirk, J., Kraus, A., Pelkonen, V. M., Pintér, S., & Zahorecz, S. 2016, A&A, 590, A75.
[16] Galli, D., Lizano, S., Shu, F. H., & Allen, A. 2006, ApJ, 647, 374.
[17] Galli, D., Cai, M., Lizano, S., & Shu, F. H. 2009, RMxAC, 36, 143.
[18] Joos, M., Hennebelle, P., & Ciardi, A. 2012, A&A, 543, 22.
[19] Koley, A. 2022, MNRAS,516, 185.
[20] Krumholz, M. R., Crutcher, R. M., & Hull, C. L. H. 2013, ApJL, 767, L11.
[21] Langer, W. D., Velusamy, T., Kuiper, T. B. H., Levin, S., Olsen, E., & Migenes, V. 1995, ApJ, 453, 293.
[22] Lee, C.-F., Li, Z.-Y., Ho, P. T. P., Hirano, N., Zhang, Q., & Shang, H. 2017, Sci. Adv., 3, e1602935.
[23] Li, Z.-Y., Krasnopolsky, R., & Shang, H. 2013, ApJ, 774, 12.
[24] Lam, K. H., Li, Z. -Y., Chen, C. -Y., Tomida, K., & Zhao, B. 2019, MNRAS, 482, 5326.
[25] Machida, M. N., Inutsuka, S.-I., & atsumoto, T. 2011, PASJ, 63, 555.
[26] Marchand, P., Commerçon, B., & Chabrier, G. 2018, A&A, 619, 16.
[27] Mellon, R. R., & Li, Z.-Y. 2008, ApJ, 681, 1356.
[28] Mellon, R. R., & Li, Z.-Y. 2009, ApJ, 698, 922.
[29] Molina-Bolivar, J. A., & Abella-Palacios, A. J. 2012, Eur. J. Phys, 33, 697.
[30] Nakano, T. 1989, MNRAS, 241, 495 (N89).
[31] Pasquale, O., & Ambrosis, A. D., 2012, Am. J. Phys., 80, 27.
[32] Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. 1992, Numerical recipes in FORTRAN 77: The art of scientific computing. Cambridge University Press, New York.
[33] Santos-Lima, R., de Gouveia Dal Pino, E. M., & Lazarian, A. 2012, ApJ, 747, 21.
[34] Seifried, D., Banerjee, R., Pudritz, R. E., & Klessen, R. S. 2012, MNRAS, 423, L40.
[35] Seifried, D., Banerjee, R., Pudritz, R. E., & Klessen, R. S. 2013, MNRAS, 432, 3320.
[36] Stahler, S. W., & Palla, F. 2004, The Formation of Stars. Wiley-VCH, New York.
[37] Tomida, K., Okuzumi, S., & Machida, M. N. 2015, MNRAS, 801, 20.
[38] Tsukamoto, Y., Iwasaki, K., Okuzumi, S., Machida, M. N., & Inutsuka S. 2015a, MNRAS, 452, 278.
[39] Tsukamoto, Y., Iwasaki, K., Okuzumi, S., Machida, M. N., & Inutsuka S. 2015b, ApJL, 810, L26.
[40] Unofre, B. P. 2020, Phys. Educ., 55, 035025.
[41] Vaytet, N., Commerçon, B., Masson J., González, M., & Chabrier, G. 2018, A&A, 615, 18.
[42] Wurster, J., Bate, M. R., & Price, D. J. 2016, MNRAS, 547, 1037.
[43] Wurster, J., Bate, M. R., & Price, D. J. 2019, MNRAS, 489, 1719.
[44] Wurster, J. 2021, MNRAS, 501, 5873.
[45] Yen, H.-W., Koch, P. M., Hul, C. L. H., Ward-Thompson, D., Bastien, P., Hasegawa, T., Kwon, W., Lai, S.-P., Qiu, K., & Ching, T.-C. 2021, ApJ, 907, 33.
[46] Zhao, B., Caselli, P., Li, Z. -Y., Krasnopolsky, R., Shang, H., & Nakamura, F. 2016, MNRAS, 460, 2050.
[47] Zhao, B., Caselli, P., Li, Z. -Y., Krasnopolsky, R. 2018, MNRAS, 473, 4868.
[48] Zhao, B., Caselli, P., Li Z. -Y., Krasnopolsky, R., Shang, H., & Lam, K. H. 2021, MNRAS, 505, 5142.
Iranian Journal of Astronomy and Astrophysics
Volume 11, Issue 4
January 2025
Pages 311-324

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