EDP Sciences logo
Subscriber Authentication Point
Search
Menu
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 [Google Scholar]
  7. Best, P. N., & Heckman, T. M. 2012, MNRAS, 421, 1569 [Google Scholar]
  8. Best, P. N., Kauffmann, G., Heckman, T. M., et al. 2005, MNRAS, 362, 25 [Google Scholar]
  9. Best, P. N., Ker, L. M., Simpson, C., Rigby, E. E., & Sabater, J. 2014, MNRAS, 445, 955 [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 [Google Scholar]
  13. Calistro Rivera, G., Williams, W. L., Hardcastle, M. J., et al. 2017, MNRAS, 469, 3468 [Google Scholar]
  14. Callingham, J. R., Ekers, R. D., Gaensler, B. M., et al. 2017, ApJ, 836, 174 [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 [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 [Google Scholar]
  20. Condon, J. J. 1992, ARA&A, 30, 575 [Google Scholar]
  21. Condon, J. J., Cotton, W. D., Greisen, E. W., et al. 1998, AJ, 115, 1693 [Google Scholar]
  22. Condon, J. J., Cotton, W. D., & Broderick, J. J. 2002, AJ, 124, 675 [Google Scholar]
  23. Condon, J. J., Cotton, W. D., Fomalont, E. B., et al. 2012, ApJ, 758, 23 [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 [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 [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 [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 [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 [Google Scholar]
  37. Garn, T., Green, D. A., Riley, J. M., & Alexander P. 2008a, MNRAS, 383, 75 [Google Scholar]
  38. Garn, T., Green, D. A., Riley, J. M., & Alexander, P. 2008b, MNRAS, 387, 1037 [Google Scholar]
  39. Gregory, P. C., & Condon, J. J. 1991, ApJS, 75, 1011 [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 [Google Scholar]
  43. Hardcastle, M. J., Gürkan, G., van Weeren, R. J., et al. 2016, MNRAS, 462, 1910 [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 [Google Scholar]
  49. Hurley-Walker, N., Callingham, J. R., Hancock, P. J., et al. 2017, MNRAS, 464, 1146 [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) [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 [Google Scholar]
  60. Lockman, F. J., Jahoda, K., & McCammon, D. 1986, ApJ, 302, 432 [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 [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 [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 [Google Scholar]
  71. Mooney, S., Quinn, J., Callingham, J. R., et al. 2019, A&A, 622, A14 [CrossRef] [EDP Sciences] [Google Scholar]
  72. Morabito, L. K., Deller, A. T., Röttgering, H., et al. 2016, MNRAS, 461, 2676 [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 [Google Scholar]
  75. Murphy, E. J., Momjian, E., Condon, J. J., et al. 2017a, ApJ, 839, 35 [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 [Google Scholar]
  82. Owen, F. N. 2018, ApJS, 235, 34 [Google Scholar]
  83. Owen, F. N., Morrison, G. E., Klimek, M. D., & Greisen, E. W. 2009, AJ, 137, 4846 [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 [Google Scholar]
  86. Powell, M. J. D. 1964, Comput. J., 7, 155 [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 [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 [Google Scholar]
  95. Schinnerer, E., Smolčić, V., Carilli, C. L., et al. 2007, ApJS, 172, 46 [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 [Google Scholar]
  100. Smirnov, O. M., & Tasse, C. 2015, MNRAS, 449, 2668 [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 [Google Scholar]
  110. Taylor, A. R., Stil, J. M., Grant, J. K., et al. 2007, ApJ, 666, 201 [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 [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 [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 [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 [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]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.