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Determination of wind-fed model parameters of neutron stars in high-mass X-ray binaries

Published online by Cambridge University Press:  12 September 2022

Ali Taani Open the ORCID record for Ali Taani [Opens in a new window] ,
Shigeyuki Karino ,
Liming Song ,
Chengmin Zhang  and
Sylvain Chaty
Ali Taani*
Affiliation:
Physics Department, Faculty of Science, Al Balqa Applied University, Salt 19117, Jordan
Shigeyuki Karino
Affiliation:
Faculty of Science and Engineering, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, Fukuoka 813-8503, Japan
Liming Song
Affiliation:
Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
Chengmin Zhang
Affiliation:
National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China School of Physics, University of Chinese Academy of Sciences, Beijing 100049, China
Sylvain Chaty
Affiliation:
Université Paris Cité, CNRS, AstroParticule et Cosmologie, Paris F-75013, France
*
Corresponding author: Ali Taani, email: [email protected]
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Abstract

We have studied several neutron star high-mass X-ray binaries (HMXBs) with super-giant (SG) companions using a wind-fed binary model associated with the magnetic field. By using the concept of torque balance, the magnetic field parameter determines the mass accretion rate. This would help us to consider the relationship between wind velocity and mass-loss rate. These parameters significantly improve our understanding of the accretion mechanism. The wind velocity is critical in determining the X-ray features. This can be used to identify the ejection process and the stochastic variations in their accretion regimes. However, even in systems with a long orbital period, an accretion disk can be created when the wind velocity is slow. This will allow the HMXB of both types, SG and Be, to be better characterised by deriving accurate properties from these binaries. In addition, we have performed segmentation in the parameter space of donors intended for several SG-HMXB listed in our sample set. The parameter space can be categorised into five regimes, depending on the possibility of disk formation associated with accretion from the stellar wind. This can give a quantitative clarification of the observed variability and the properties of these objects. For most of the systems, we show that the derived system parameters are consistent with the assumption that the system is emitting X-rays through direct accretion. However, there are some sources (LMC X-4, Cen X-3 and OAO1657-415) that are not in the direct accretion regime, although they share similar donor parameters. This may indicate that these systems are transitioning from a normal wind accretion phase to partial RLOF regimes.

Keywords

Binaries: X-rays: binariesformation: magnetic fieldssupergiant starswind-fed model
Type
Research Article
Information
Publications of the Astronomical Society of Australia , Volume 39 , 2022 , e040
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Astronomical Society of Australia

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References

Bachetti, M., et al. 2014, Natur 514, 202 Google Scholar
Bodaghee, A., et al. 2016, ApJ, 823, 146 Google Scholar
Bondi, H., & Hoyle, F. 1944, MNRAS, 104, 273 Google Scholar
Bonning, E. W., & Falanga, M. 2005, A&A, 436, L31 Google Scholar
Bozzo, E., Falanga, M., & Stella, L. 2008, ApJ, 683, 1031 Google Scholar
Cai, Y., Taani, A., Zhao, Y.-H., & Zhang, C. M. 2012, ChA&A, 36, 137 Google Scholar
Campana, S., et al. 2002, ApJ, 580, 389 Google Scholar
Chaty, S., et al. 2008, A& A, 484, 783 Google Scholar
Clark, G. W., et al. 1990, ApJ, 353, 274 Google Scholar
Coburn, W., et al. 2002, ApJ, 580, 394 Google Scholar
Cusumano, G., et al. 1998, A&A, 338, L79 Google Scholar
Cusumano, G., et al. 2010, MNRAS, 406, 16 Google Scholar
D’Ai, A., et al. 2011, A&A, 532, A73 Google Scholar
Dai, Z. B., et al. 2017, A&A, 606, 45 Google Scholar
DeCesar, M. E., Pottschmidt, K., & Wilms, J. 2009, ATel, 2036 Google Scholar
den Hartog, P. R., et al. 2006, A&A, 451, 587 Google Scholar
Denis, M., Bulik, T., & Marcinkowski, R. 2010, AcA, 60, 75D Google Scholar
Donati, J.-F., et al. 2011, MNRAS, 412, 2454 Google Scholar
El Mellah, I., Sander, A. A. C., Sundqvist, J. O., & Keppens, R. 2019a, A&A, 622, 189A Google Scholar
El Mellah, I., Sundqvist, J. O., & Keppens, R. 2019b, A&A, 622, L3 Google Scholar
Falanga, M., et al. 2015, A&A, 577, A130 Google Scholar
Ferrigno, C., et al. 2011, A&A, 532, 76A Google Scholar
Frank, J., King, A., & Raine, D. J. 2002, Accretion Power in Astrophysics (3rd edn.; Cambridge University Press)Google Scholar
Frebel, A., & Norris, J. E. 2015, ARA&A 53, 631 Google Scholar
Fürst, F., et al. 2014, ApJ, 784, L40 Google Scholar
Giménez-García, A., et al. 2016, A&A, 591A, 26G Google Scholar
Ghosh, P., & Lamb, F. K. 1979, ApJ, 234,296 Google Scholar
Heindl, W. A., et al. 2003, ATel, 200,1 Google Scholar
Hirai, R., & Mandel, I. 2021, PASA, 38, 056 Google Scholar
Hurley, J. R., Pols, O. R., & Tout, C. A. 2000, MNRAS, 315, 543 Google Scholar
Jenke, P. A., Finger, M. H., Wilson-Hodge, C. A., & Camero-Arranz, A. 2012, ApJ, 759, 124 Google Scholar
Karino, S., & Miller, J. C. 2016, MNRAS, 462, 3476K CrossRefGoogle Scholar
Karino, S., Nakamura, K., & Taani, A. 2019, PASJ, 71, 58 CrossRefGoogle Scholar
Karino, S. 2020, PASJ, 72, 95 Google Scholar
Kasen, D., et al. 2017, Natur, 551, 80 Google Scholar
Kretschmar, P., et al. 2021, A&A, 652, 95 Google Scholar
Kreykenbohm, I., et al. 2002, A&A, 395, 129 Google Scholar
Kreykenbohm, I., et al. 2005, A&A, 433, 45 Google Scholar
la Barbera, A., et al. 2001, ApJ, 553, 375 Google Scholar
Lutovinov, A., Tsygankov, S., & Postnov, K. 2017, MNRAS, 466, 593 CrossRefGoogle Scholar
Makishima, K., et al. 1999, ApJ, 525, L97 Google Scholar
Mardini, M. K., et al. 2019a, ApJ, 882, 27 Google Scholar
Mardini, M. K., et al. 2019b, ApJ, 875, 89 Google Scholar
Mardini, M. K., et al. 2020, ApJ, 903, 88 Google Scholar
Mason, A. B., et al. 2009, A&A, 505, 281 Google Scholar
Mason, A. B., et al. 2012, MNRAS, 422, 199 Google Scholar
Mushtukov, A., Suleimanov, V., Tsygankov, S., & Poutanen, J. 2015, MNRAS, 454, 2539 Google Scholar
Nagase, F., et al. 1991, ApJ, 375, 49 Google Scholar
Nespoli, E., Fabregat, J., & Mennickent, R. E. 2010, A&A, 516, A106 Google Scholar
Nishimura, O. 2005, PASJ, 57, 769 Google Scholar
Orlandini, M., et al. 1999, A&A, 349, L9 Google Scholar
Pfahl, E., et al. 2002, ApJ, 574, 364 Google Scholar
Podsiadlowski, P., et al. 2004, ApJ, 612, 1044 Google Scholar
Postnov, k., & Yungelson, L. 2006, LRR, 9, 6 Google Scholar
Pottschmidt, K., et al. 2011, AIPC, 1427, 60 Google Scholar
Puls, J., Vink, J. S., & Najarro, F. 2008, A&AR, 16, 209 Google Scholar
Rawls, M. L., et al. 2011, ApJ, 730, 25 Google Scholar
Reig, P., et al. 2016, A&A, 590, A122 Google Scholar
Reig, P., & Zezas, A. 2018, A&A, 613A, 52R Google Scholar
Reynolds, A. P., et al. 1999, A&A, 349, 873R Google Scholar
Rivers, E., et al. 2010, ApJ, 709, 179 Google Scholar
Robba, N. R., et al. 2001, ApJ, 562, 950 Google Scholar
Rodes-Roca, J. J., et al. 2009, A&A, 508, 395 Google Scholar
Santangelo, A., et al. 1998, ApJ, 340, 55 Google Scholar
Sanwal, D., Pavlov, G., & Zavlin, V. E. 2002, ApJ, 574, L61 Google Scholar
Schanne, S., et al. 2007, 622, 479 Google Scholar
Shakura, N., Postnov, K., & Hjalmarsdotter, L. 2013, MNRAS, 428, 670 Google Scholar
Shakura, N., Postnov, K., Kochetkova, A., & Hjalmarsdotter, L. 2012, MNRAS, 420, 216 Google Scholar
Stella, L., White, N. E., & Rosner, R. 1986, ApJ, 308, 669 Google Scholar
Taani, A. 2015, JJP, 8, 149 Google Scholar
Taani, A. 2016, RAA, 16, 101 Google Scholar
Taani, A., & Khasawneh, A. 2017, JPhCS, 869, 012090 CrossRefGoogle Scholar
Taani, A., & Vallejo, J. C. 2017, PASA, 34, 24 Google Scholar
Taani, A., et al. 2019a, JPhCS, 1258, 012029 Google Scholar
Taani, A., et al. 2019b, RA&A, 19, 12 Google Scholar
Taani, A., et al. 2020, JJP, 13, 243 Google Scholar
Taani, A., Vallejo, J. C., & Abu-Saleem, M. 2022, JHEAP, 35, 83 Google Scholar
Trüemper, J., et al. 1978, ApJ, 219, 105 Google Scholar
Tsygankov, S., Mushtukov, A. A., Suleimanov, V. F., & Poutanen, J. 2016, MNRAS, 457, 1101 Google Scholar
Ustyugova, G. V., et al. 2006, ApJ, 646, 304 Google Scholar
van den Heuvel, E. P. J. 2009, Ap&SSL, Springer-Verlag, 359, 125 Google Scholar
Vink, J. S., de Koter, A., & Lamers, H. J. G. L. M. 2001, A&A, 369, 574 Google Scholar
Voges, W., et al. 1982, 263, 803 Google Scholar
Walter, R., Lutovinov, A., & Bozzo, E. 2015, A&ARv, 23, 2W Google ScholarPubMed
Wheaton, W., et al. 1979, Natur, 282, 240 Google Scholar
Wei, Y. C., et al. 2010, CPL, 27, 9801,Google Scholar
Wilson, C., Finger, M., & Camero-Arranz, A. 2008 ApJ, 678, 1263 Google Scholar
Yamamoto, T., et al. 2011, PASJ, 63, 751 Google Scholar
Ye, C. Q., et al. 2019, ASS, 83, 230 Google Scholar
Ye, C. Q., et al. 2020, Ap&SS, 365, 126 Google Scholar
Zahn, J.-P. 1977, A&A, 57, 383 Google Scholar