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Home All issues Volume 648 (April 2021) A&A, 648 (2021) A2 References
Issue
A&A
Volume 648, April 2021
The LOFAR Two Meter Sky Survey
Article Number A2
Number of page(s) 20
Section Catalogs and data
DOI https://doi.org/10.1051/0004-6361/202038828
Published online 07 April 2021
  1. Akaike, H. 1998, Information Theory and an Extension of the Maximum Likelihood Principle, eds. E. Parzen, K. Tanabe, & G. Kitagawa (New York, NY: Springer New York), 199 [Google Scholar]
  2. Astropy Collaboration (Robitaille, T. P., et al.) 2013, A&A, 558, A33 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  3. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  4. Baars, J. W. M., Genzel, R., Pauliny-Toth, I. I. K., & Witzel, A. 1977, A&A, 500, 135 [NASA ADS] [Google Scholar]
  5. Becker, R. H., White, R. L., & Edwards, A. L. 1991, ApJS, 75, 1 [Google Scholar]
  6. Becker, R. H., White, R. L., & Helfand, D. J. 1995, ApJ, 450, 559 [NASA ADS] [CrossRef] [Google Scholar]
  7. Best, P. N., & Heckman, T. M. 2012, MNRAS, 421, 1569 [NASA ADS] [CrossRef] [Google Scholar]
  8. Best, P. N., Kauffmann, G., Heckman, T. M., et al. 2005, MNRAS, 362, 25 [NASA ADS] [CrossRef] [Google Scholar]
  9. Best, P. N., Ker, L. M., Simpson, C., Rigby, E. E., & Sabater, J. 2014, MNRAS, 445, 955 [NASA ADS] [CrossRef] [Google Scholar]
  10. Boggs, P. T., & Rogers, J. E. 1990, Contem. Math., 112, 183 [Google Scholar]
  11. Bondi, M., Ciliegi, P., Venturi, T., et al. 2007, A&A, 463, 519 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  12. Bower, R. G., Benson, A. J., Malbon, R., et al. 2006, MNRAS, 370, 645 [NASA ADS] [CrossRef] [Google Scholar]
  13. Calistro Rivera, G., Williams, W. L., Hardcastle, M. J., et al. 2017, MNRAS, 469, 3468 [NASA ADS] [CrossRef] [Google Scholar]
  14. Callingham, J. R., Ekers, R. D., Gaensler, B. M., et al. 2017, ApJ, 836, 174 [NASA ADS] [CrossRef] [Google Scholar]
  15. Callingham, J. R., Pope, B. J. S., Feinstein, A. D., et al. 2021, A&A, 648, A13 (LoTSS SI) [EDP Sciences] [Google Scholar]
  16. Chakraborty, A., Roy, N., Datta, A., et al. 2019, MNRAS, 490, 243 [Google Scholar]
  17. Ciliegi, P., McMahon, R. G., Miley, G., et al. 1999, MNRAS, 302, 222 [NASA ADS] [CrossRef] [Google Scholar]
  18. Ciliegi, P., Zamorani, G., Bondi, M., et al. 2005, A&A, 441, 879 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Cohen, A. S., Lane, W. M., Cotton, W. D., et al. 2007, AJ, 134, 1245 [NASA ADS] [CrossRef] [Google Scholar]
  20. Condon, J. J. 1992, ARA&A, 30, 575 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  21. Condon, J. J., Cotton, W. D., Greisen, E. W., et al. 1998, AJ, 115, 1693 [NASA ADS] [CrossRef] [Google Scholar]
  22. Condon, J. J., Cotton, W. D., & Broderick, J. J. 2002, AJ, 124, 675 [NASA ADS] [CrossRef] [Google Scholar]
  23. Condon, J. J., Cotton, W. D., Fomalont, E. B., et al. 2012, ApJ, 758, 23 [NASA ADS] [CrossRef] [Google Scholar]
  24. Coppejans, R., Cseh, D., Williams, W. L., van Velzen, S., & Falcke, H. 2015, MNRAS, 450, 1477 [Google Scholar]
  25. Coppejans, R., Cseh, D., van Velzen, S., et al. 2016, MNRAS, 459, 2455 [CrossRef] [Google Scholar]
  26. Croft, S., Bower, G. C., & Whysong, D. 2013, ApJ, 762, 93 [Google Scholar]
  27. Croston, J. H., Hardcastle, M. J., Mingo, B., et al. 2019, A&A, 622, A10 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Croton, D. J., Springel, V., White, S. D. M., et al. 2006, MNRAS, 365, 11 [NASA ADS] [CrossRef] [Google Scholar]
  29. de Gasperin, F., Dijkema, T. J., Drabent, A., et al. 2019, A&A, 622, A5 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  30. de Vries, W. H., Morganti, R., Röttgering, H. J. A., et al. 2002, AJ, 123, 1784 [NASA ADS] [CrossRef] [Google Scholar]
  31. Dewdney, P. E., Hall, P. J., Schilizzi, R. T., & Lazio, T. J. L. W. 2009, IEEE Proc., 97, 1482 [Google Scholar]
  32. Douglas, J. N., Bash, F. N., Bozyan, F. A., Torrence, G. W., & Wolfe, C. 1996, AJ, 111, 1945 [NASA ADS] [CrossRef] [Google Scholar]
  33. Duncan, K. J., Sabater, J., Röttgering, H. J. A., et al. 2019, A&A, 622, A3 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Duncan, K. J., Kondapally, R., Brown, M. J. I., et al. 2021, A&A, 648, A4 (LoTSS SI) [EDP Sciences] [Google Scholar]
  35. Ekers, R. 2012, PoS(RTS2012)007 [arXiv:1212.3497] [Google Scholar]
  36. Franzen, T. M. O., Banfield, J. K., Hales, C. A., et al. 2015, MNRAS, 453, 4020 [NASA ADS] [CrossRef] [Google Scholar]
  37. Garn, T., Green, D. A., Riley, J. M., & Alexander P. 2008a, MNRAS, 383, 75 [NASA ADS] [CrossRef] [Google Scholar]
  38. Garn, T., Green, D. A., Riley, J. M., & Alexander, P. 2008b, MNRAS, 387, 1037 [NASA ADS] [CrossRef] [Google Scholar]
  39. Gregory, P. C., & Condon, J. J. 1991, ApJS, 75, 1011 [NASA ADS] [CrossRef] [Google Scholar]
  40. Gürkan, G., Hardcastle, M. J., Best, P. N., et al. 2019, A&A, 622, A11 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  41. Hales, S. E. G., Masson, C. R., Warner, P. J., & Baldwin, J. E. 1990, MNRAS, 246, 256 [NASA ADS] [Google Scholar]
  42. Hales, S. E. G., Waldram, E. M., Rees, N., & Warner, P. J. 1995, MNRAS, 274, 447 [NASA ADS] [CrossRef] [Google Scholar]
  43. Hardcastle, M. J., Gürkan, G., van Weeren, R. J., et al. 2016, MNRAS, 462, 1910 [NASA ADS] [CrossRef] [Google Scholar]
  44. Hardcastle, M. J., Williams, W. L., Best, P. N., et al. 2019, A&A, 622, A12 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  45. Heckman, T. M., & Best, P. N. 2014, ARA&A, 58, 589 [Google Scholar]
  46. Herrera Ruiz, N., O’Sullivan, S. P., Vacca, V., et al. 2021, A&A, 648, A12 (LoTSS SI) [EDP Sciences] [Google Scholar]
  47. Hogg, D. W., Bovy, J., & Lang, D. 2010, ArXiv e-prints [arXiv:1008.4686] [Google Scholar]
  48. Hunter, J. D. 2007, Comput. Sci. Eng., 9, 90 [NASA ADS] [CrossRef] [Google Scholar]
  49. Hurley-Walker, N., Callingham, J. R., Hancock, P. J., et al. 2017, MNRAS, 464, 1146 [NASA ADS] [CrossRef] [Google Scholar]
  50. Intema, H. T., van der Tol, S., Cotton, W. D., et al. 2009, A&A, 501, 1185 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  51. Intema, H. T., Jagannathan, P., Mooley, K. P., & Frail, D. A. 2017, A&A, 598, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  52. Ivezić, Ž., Connolly, A., Vanderplas, J., & Gray, A. 2014, Statistics, Data Mining and Machine Learning in Astronomy (Princeton: Princeton University Press) [CrossRef] [Google Scholar]
  53. Jackson, N., Tagore, A., Deller, A., et al. 2016, A&A, 595, A86 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  54. Jannuzi, B. T., & Dey, A. 1999, ASP Conf. Ser., 191, 111 [Google Scholar]
  55. Jarvis, M., Taylor, R., Agudo, I., et al. 2016, in MeerKAT Science: On the Pathway to the SKA (USA: NASA), 6 [Google Scholar]
  56. Jelić, V., de Bruyn, A. G., Mevius, M., et al. 2014, A&A, 568, A101 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  57. Jones, E., Oliphant, T., Peterson, P., et al. 2001, SciPy: Open source scientific tools for Python, [Online; accessed 2014-08-26] [Google Scholar]
  58. Kondapally, R., Best, P. N., Hardcastle, M. J., et al. 2021, A&A, 648, A3 (LoTSS SI) [EDP Sciences] [Google Scholar]
  59. Lane, W. M., Cotton, W. D., van Velzen, S., et al. 2014, MNRAS, 440, 327 [NASA ADS] [CrossRef] [Google Scholar]
  60. Lockman, F. J., Jahoda, K., & McCammon, D. 1986, ApJ, 302, 432 [NASA ADS] [CrossRef] [Google Scholar]
  61. Mahatma, V. H., Hardcastle, M. J., Williams, W. L., et al. 2019, A&A, 622, A13 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  62. Mahony, E. K., Morganti, R., Prandoni, I., et al. 2016, MNRAS, 463, 2997 [NASA ADS] [CrossRef] [Google Scholar]
  63. Mandal, S., Prandoni, I., Hardcastle, M. J., et al. 2021, A&A, 648, A5 (LoTSS SI) [EDP Sciences] [Google Scholar]
  64. McKinney, W. 2010, Proceedings of the 9th Python in Science Conference, eds. S. van der Walt, & J. Millman, 5 [Google Scholar]
  65. Mechev, A., Oonk, J. B. R., Danezi, A., et al. 2017, in Proceedings of the International Symposium on Grids and Clouds (ISGC) 2017, held 5 March, 2017 at Academia Sinica, Taipei, Taiwan (ISGC2017) Online at https://pos.sissa.it/cgi-bin/reader/conf.cgi?confid=293, id.2, 2 [Google Scholar]
  66. Mevius, M. 2018, RMextract: Ionospheric Faraday Rotation calculator (USA: NASA) [Google Scholar]
  67. Mevius, M., van der Tol, S., Pandey, V. N., et al. 2016, Rad. Sci., 51, 927 [Google Scholar]
  68. Mingo, B., Croston, J. H., Hardcastle, M. J., et al. 2019, MNRAS, 488, 2701 [NASA ADS] [CrossRef] [Google Scholar]
  69. Mohan, N., & Rafferty, D. 2015, PyBDSF: Python Blob Detection and Source Finder (USA: NASA) [Google Scholar]
  70. Molenaar, G., & Smirnov, O. 2018, Astron. Comput., 24, 45 [NASA ADS] [CrossRef] [Google Scholar]
  71. Mooney, S., Quinn, J., Callingham, J. R., et al. 2019, A&A, 622, A14 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  72. Morabito, L. K., Deller, A. T., Röttgering, H., et al. 2016, MNRAS, 461, 2676 [NASA ADS] [CrossRef] [Google Scholar]
  73. Morabito, L. K., Matthews, J. H., Best, P. N., et al. 2019, A&A, 622, A15 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  74. Morrison, G. E., Owen, F. N., Dickinson, M., Ivison, R. J., & Ibar, E. 2010, ApJS, 188, 178 [NASA ADS] [CrossRef] [Google Scholar]
  75. Murphy, E. J., Momjian, E., Condon, J. J., et al. 2017a, ApJ, 839, 35 [NASA ADS] [CrossRef] [Google Scholar]
  76. Murphy, T., Kaplan, D. L., Croft, S., et al. 2017b, MNRAS, 466, 1944 [Google Scholar]
  77. Nisbet, D. 2018, PhD thesis, The University of Edinburgh, UK [Google Scholar]
  78. Ocran, E. F., Taylor, A. R., Vaccari, M., Ishwara-Chandra, C. H., & Prandoni, I. 2020, MNRAS, 491, 1127 [Google Scholar]
  79. Offringa, A. R. 2016, A&A, 595, A99 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  80. Offringa, A. R., van de Gronde, J. J., & Roerdink, J. B. T. M. 2012, A&A, 539, A95 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  81. Oliver, S., Rowan-Robinson, M., Alexander, D. M., et al. 2000, MNRAS, 316, 749 [NASA ADS] [CrossRef] [Google Scholar]
  82. Owen, F. N. 2018, ApJS, 235, 34 [NASA ADS] [CrossRef] [Google Scholar]
  83. Owen, F. N., Morrison, G. E., Klimek, M. D., & Greisen, E. W. 2009, AJ, 137, 4846 [NASA ADS] [CrossRef] [Google Scholar]
  84. Pérez, F., & Granger, B. E. 2007, Comput. Sci. Eng., 9, 21 [Google Scholar]
  85. Pleunis, Z., Bassa, C. G., Hessels, J. W. T., et al. 2017, ApJ, 846, L19 [NASA ADS] [CrossRef] [Google Scholar]
  86. Powell, M. J. D. 1964, Comput. J., 7, 155 [CrossRef] [MathSciNet] [Google Scholar]
  87. Prandoni, I., & Seymour, N. 2015, in Advancing Astrophysics with the Square Kilometre Array (SKA: New Mexico), 67 [Google Scholar]
  88. Prandoni, I., Guglielmino, G., Morganti, R., et al. 2018, MNRAS, 481, 4548 [NASA ADS] [CrossRef] [Google Scholar]
  89. Rengelink, R. B., Tang, Y., de Bruyn, A. G., et al. 1997, A&AS, 124, 259 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  90. Sabater, J., Sánchez-Expósito, S., Best, P., et al. 2017, Astron. Comput., 19, 75 [Google Scholar]
  91. Sabater, J., Best, P. N., Hardcastle, M. J., et al. 2019, A&A, 622, A17 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  92. Salvatier, J., Wiecki, T.V., F. C. 2016, Peer J Comput. Sci., 2, e55 [Google Scholar]
  93. Savitzky, A., & Golay, M. J. E. 1964, Anal. Chem., 36, 1627 [Google Scholar]
  94. Scaife, A. M. M., & Heald, G. H. 2012, MNRAS, 423, L30 [NASA ADS] [CrossRef] [Google Scholar]
  95. Schinnerer, E., Smolčić, V., Carilli, C. L., et al. 2007, ApJS, 172, 46 [NASA ADS] [CrossRef] [Google Scholar]
  96. Schwarz, G. 1978, Ann. Statist., 6, 461 [Google Scholar]
  97. Shimwell, T. W., Röttgering, H. J. A., Best, P. N., et al. 2017, A&A, 598, A104 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  98. Shimwell, T. W., Tasse, C., Hardcastle, M. J., et al. 2019, A&A, 622, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  99. Sirothia, S. K., Dennefeld, M., Saikia, D. J., et al. 2009, MNRAS, 395, 269 [NASA ADS] [CrossRef] [Google Scholar]
  100. Smirnov, O. M., & Tasse, C. 2015, MNRAS, 449, 2668 [NASA ADS] [CrossRef] [Google Scholar]
  101. Smith, D. J. B., Best, P. N., Duncan, K. J., et al. 2016, in SF2A-2016: Proceedings of the Annual meeting of the French Society of Astronomy and Astrophysics, eds. C. Reylé, J. Richard, L. Cambrésy, M. Deleuil, E. Pécontal, L. Tresse, & I. Vauglin, 271 [Google Scholar]
  102. Smolčić, V., Novak, M., Bondi, M., et al. 2017, A&A, 602, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  103. Stacey, H. R., McKean, J. P., Jackson, N. J., et al. 2019, A&A, 622, A18 [EDP Sciences] [Google Scholar]
  104. Tasse, C. 2014a, A&A, 566, A127 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  105. Tasse, C. 2014b, ArXiv e-prints [arXiv:1410.8706] [Google Scholar]
  106. Tasse, C., Hugo, B., Mirmont, M., et al. 2018, A&A, 611, A87 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  107. Tasse, C., Shimwell T., Hardcastle, M. J., et al. 2021, A&A, 648, A1 (LoTSS SI) [EDP Sciences] [Google Scholar]
  108. Taylor, M. B. 2005, ASP Conf. Ser., 347, 29 [Google Scholar]
  109. Taylor, A. R., & Jagannathan, P. 2016, MNRAS, 459, L36 [NASA ADS] [CrossRef] [Google Scholar]
  110. Taylor, A. R., Stil, J. M., Grant, J. K., et al. 2007, ApJ, 666, 201 [NASA ADS] [CrossRef] [Google Scholar]
  111. van der Tol, S., Jeffs, B. D., & van der Veen, A.-J. 2007, IEEE Transac. Signal Process., 55, 4497 [Google Scholar]
  112. van Diepen, G. N. J. 2015, Astron. Comput., 12, 174 [NASA ADS] [CrossRef] [Google Scholar]
  113. van Haarlem, M. P., Wise, M. W., Gunst, A. W., et al. 2013, A&A, 556, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  114. van Weeren, R. J., Williams, W. L., Hardcastle, M. J., et al. 2016, ApJS, 223, 2 [NASA ADS] [CrossRef] [Google Scholar]
  115. Vanderplas, J., Connolly, A., Ivezić, Ž., & Gray, A. 2012, in Conference on Intelligent Data Understanding (CIDU), 47 –54 [Google Scholar]
  116. Walt, S. v. d., Colbert, S. C., & Varoquaux, G. 2011, Comput. Sci. Eng., 13, 22 [CrossRef] [Google Scholar]
  117. Wang, L., Gao, F., Duncan, K. J., et al. 2019, A&A, 631, A109 [CrossRef] [EDP Sciences] [Google Scholar]
  118. Williams, W. L., Intema, H. T., & Röttgering, H. J. A. 2013, A&A, 549, A55 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  119. Williams, W. L., van Weeren, R. J., Röttgering, H. J. A., et al. 2016, MNRAS, 460, 2385 [NASA ADS] [CrossRef] [Google Scholar]
  120. Williams, W. L., Hardcastle, M. J., Best, P. N., et al. 2019, A&A, 622, A2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  121. Zwart, J., Wall, J., Karim, A., et al. 2015, Advancing Astrophysics with the Square Kilometre Array (SKA: New Mexico), 172 [Google Scholar]

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