請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63949完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 朱有花(You-Hua Chu) | |
| dc.contributor.author | Chen-Fatt Lim | en |
| dc.contributor.author | 林征發 | zh_TW |
| dc.date.accessioned | 2021-06-16T17:24:05Z | - |
| dc.date.available | 2020-04-16 | |
| dc.date.copyright | 2020-04-16 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-03-16 | |
| dc.identifier.citation | Abdurro’uf, Akiyama, M. 2018, MNRAS, 479, 5083
Adelberger, K. L., Steidel, C. C., Pettini, M., et al. 2005, ApJ, 619, 697 Aird, J., Coil, A. L., & Georgakakis, A. 2017, MNRAS, 465, 3390 Alaghband-Zadeh, S., Chapman, S. C., Swinbank, A. M., et al. 2012, MNRAS, 424, 2232 Alexander, D. M., Bauer, F. E., Chapman, S. C., et al. 2005, ApJ, 632, 736 Amvrosiadis, A., Valiante, E., Gonzalez-Nuevo, J., et al. 2019, MNRAS, 483, 4649 An, F. X., Stach, S. M., Smail, I., et al. 2018, ApJ, 862, 101 An, F. X., Simpson, J. M., Smail, I., et al. 2019, ApJ, 886, 48 Aoyama, S., Hirashita, H., Lim, C.-F., et al. 2019, MNRAS, 484, 1852 Aravena, M., Decarli, R., Walter, F., et al. 2016, ApJ, 833, 68 Aretxaga, I., Hughes, D. H., Coppin, K., et al. 2007, MNRAS, 379, 1571 Aretxaga, I., Wilson, G. W., Aguilar, E., et al. 2011, MNRAS, 415, 3831 Armus, L., Mazzarella, J. M., Evans, A. S., et al. 2009, PASP, 121, 559 Arnouts, S., Cristiani, S., Moscardini, L., et al. 1999, MNRAS, 310, 540 Assef, R. J., Kochanek, C. S., Ashby, M. L. N., et al. 2011, ApJ, 728, 56 Avni, Y. 1976, ApJ, 210, 642 Barger, A. J., Cowie, L. L., & Richards, E. A. 2000, AJ, 119, 2092 Barger, A. J., Cowie, L. L., & Sanders, D. B. 1999, ApJL, 518, L5 Barger, A. J., Cowie, L. L., Sanders, D. B., et al. 1998, Nature, 394, 248 Barger, A. J., Wang, W.-H., Cowie, L. L., et al. 2012, ApJ, 761, 89 Baugh, C. M., & Efstathiou, G. 1993, MNRAS, 265, 145 Bergstra, J., & Bengio, Y. 2012, J. Mach. Learn. Res., 13, 281 Bernstein, G., & Huterer, D. 2010, MNRAS, 401, 1399 Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393 Bertoldi, F., Carilli, C., Aravena, M., et al. 2007, ApJS, 172, 132 Béthermin, M., Daddi, E., Magdis, G., et al. 2015, A&A, 573, A113 Béthermin, M., Wu, H.-Y., Lagache, G., et al. 2017, A&A, 607, A89 Blain, A. W., Chapman, S. C., Smail, I., & Ivison, R. 2004, ApJ, 611, 725 Boissier, S., Gil de Paz, A., Boselli, A., et al. 2007, ApJS, 173, 524 Bondi, M., Ciliegi, P., Venturi, T., et al. 2007, A&A, 463, 519 Boquien, M., Buat, V., Boselli, A., et al. 2012, A&A, 539, A145 Borys, C., Chapman, S., Halpern, M., & Scott, D. 2003, MNRAS, 344, 385 Bourne, N., Dunlop, J. S., Merlin, E., et al. 2017, MNRAS, 467, 1360 Bouwens, R. J., Illingworth, G. D., Franx, M., et al. 2009, ApJ, 705, 936 Bouwens, R. J., Illingworth, G. D., Oesch, P. A., et al. 2014, ApJ, 793, 115 Breiman, L. 1996, Machine Learning, 24, 123 Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000 Buat, V., Giovannoli, E., Burgarella, D., et al. 2010, MNRAS, 409, L1 Buat, V., Giovannoli, E., Heinis, S., et al. 2011, A&A, 533, A93 Buat, V., Noll, S., Burgarella, D., et al. 2012, A&A, 545, A141 Calistro Rivera, G., Hodge, J. A., Smail, I., et al. 2018, ApJ, 863, 56 Calzetti, D. 2001, PASP, 113, 1449 Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682 Calzetti, D., Kinney, A. L., & Storchi-Bergmann, T. 1994, ApJ, 429, 582 Capak, P. L., Carilli, C., Jones, G., et al. 2015, Nature, 522, 455 Casey, C. M., Narayanan, D., & Cooray, A. 2014a, PhR, 541, 45 Casey, C. M., Berta, S., Béthermin, M., et al. 2012, ApJ, 761, 140 Casey, C. M., Chen, C.-C., Cowie, L. L., et al. 2013, MNRAS, 436, 1919 Casey, C. M., Scoville, N. Z., Sanders, D. B., et al. 2014b, ApJ, 796, 95 Casey, C. M., Zavala, J. A., Spilker, J., et al. 2018, ApJ, 862, 77 Chabrier, G. 2003, PASP, 115, 763 Chang, Y.-Y., van der Wel, A., Rix, H.-W., et al. 2013, ApJ, 762, 83 Chang, Y.-Y., Le Floc’h, E., Juneau, S., et al. 2017, ApJS, 233, 19 Chang, Y.-Y., Ferraro, N., Wang, W.-H., et al. 2018, ApJ, 865, 103 Chapin, E. L., Berry, D. S., Gibb, A. G., et al. 2013, MNRAS, 430, 2545 Chapin, E. L., Hughes, D. H., & Aretxaga, I. 2009, MNRAS, 393, 653 Chapman, S. C., Blain, A. W., Ivison, R. J., & Smail, I. R. 2003, Nature, 422, 695 Chapman, S. C., Blain, A. W., Smail, I., & Ivison, R. J. 2005, ApJ, 622, 772 Chapman, S. C., Lewis, G. F., Scott, D., Borys, C., & Richards, E. 2002, ApJ, 570, 557 Chapman, S. C., Smail, I., Blain, A. W., & Ivison, R. J. 2004a, ApJ, 614, 671 Chapman, S. C., Smail, I., Windhorst, R., Muxlow, T., & Ivison, R. J. 2004b, ApJ, 611, 732 Chary, R., & Elbaz, D. 2001, ApJ, 556, 562 Chen, C.-C., Cowie, L. L., Barger, A. J., et al. 2013a, ApJ, 776, 131 —. 2013b, ApJ, 762, 81 Chen, C.-C., Smail, I., Swinbank, A. M., et al. 2015, ApJ, 799, 194 Chen, C.-C., Smail, I., Ivison, R. J., et al. 2016a, ApJ, 820, 82 Chen, C.-C., Smail, I., Swinbank, A. M., et al. 2016b, ApJ, 831, 91 Chen, C.-C., Hodge, J. A., Smail, I., et al. 2017, ApJ, 846, 108 Chomiuk, L., & Povich, M. S. 2011, AJ, 142, 197 Coil, A. L., Hennawi, J. F., Newman, J. A., Cooper, M. C., & Davis, M. 2007, ApJ, 654, 115 Coil, A. L., Newman, J. A., Cooper, M. C., et al. 2006, ApJ, 644, 671 Coil, A. L., Newman, J. A., Croton, D., et al. 2008, ApJ, 672, 153 Coil, A. L., Blanton, M. R., Burles, S. M., et al. 2011, ApJ, 741, 8 Condon, J. J. 1992, ARA&A, 30, 575 Conroy, C., Schiminovich, D., & Blanton, M. R. 2010, ApJ, 718, 184 Conselice, C. J., Chapman, S. C., & Windhorst, R. A. 2003, ApJL, 596, L5 Cooray, A., Amblard, A., Wang, L., et al. 2010, A&A, 518, L22 Coppin, K., Halpern, M., Scott, D., Borys, C., & Chapman, S. 2005, MNRAS, 357, 1022 Coppin, K., Halpern, M., Scott, D., et al. 2008, MNRAS, 384, 1597 Corre, D., Buat, V., Basa, S., et al. 2018, A&A, 617, A141 Cowie, L. L., Barger, A. J., Hsu, L.-Y., et al. 2017, ApJ, 837, 139 Cowie, L. L., Barger, A. J., & Kneib, J.-P. 2002, AJ, 123, 2197 Cowie, L. L., González-López, J., Barger, A. J., et al. 2018, ApJ, 865, 106 Cowie, L. L., Songaila, A., Hu, E. M., & Cohen, J. G. 1996, AJ, 112, 839 Cowley, W. I., Béthermin, M., Lagos, C. d. P., et al. 2017, MNRAS, 467, 1231 da Cunha, E., Walter, F., Smail, I. R., et al. 2015, ApJ, 806, 110 Dale, D. A., & Helou, G. 2002, ApJ, 576, 159 Damjanov, I., Zahid, H. J., Geller, M. J., Fabricant, D. G., & Hwang, H. S. 2018, ApJS, 234, 21 Danielson, A. L. R., Swinbank, A. M., Smail, I., et al. 2017, ApJ, 840, 78 Davis, M., & Peebles, P. J. E. 1983, ApJ, 267, 465 de Ravel, L., Kampczyk, P., Le Fèvre, O., et al. 2011, arXiv e-prints, arXiv:1104.5470. https://arxiv.org/abs/1104.5470 Delhaize, J., Smolčić, V., Delvecchio, I., et al. 2017, A&A, 602, A4 Delvecchio, I., Smolčić, V., Zamorani, G., et al. 2017, A&A, 602, A3 Dempsey, J. T., Friberg, P., Jenness, T., et al. 2013, MNRAS, 430, 2534 Dolley, T., Brown, M. J. I., Weiner, B. J., et al. 2014, ApJ, 797, 125 Downes, A. J. B., Peacock, J. A., Savage, A., & Carrie, D. R. 1986, MNRAS, 218, 31 Draine, B. T. 2006, ApJ, 636, 1114 Dudzevičiūtė, U., Smail, I., Swinbank, A. M., et al. 2019, arXiv e-prints, arXiv:1910.07524. https://arxiv.org/abs/1910.07524 Dunlop, J. S., McLure, R. J., Biggs, A. D., et al. 2017, MNRAS, 466, 861 Durkalec, A., Le Fèvre, O., Pollo, A., et al. 2015, A&A, 583, A128 Dwek, E., & Arendt, R. G. 1998, ApJL, 508, L9 Eales, S., Lilly, S., Gear, W., et al. 1999, The Astrophysical Journal, 515, 518 Eftekharzadeh, S., Myers, A. D., White, M., et al. 2015, MNRAS, 453, 2779 Elbaz, D., Dickinson, M., Hwang, H. S., et al. 2011, A&A, 533, A119 Elbaz, D., Leiton, R., Nagar, N., et al. 2018, A&A, 616, A110 Engel, H., Tacconi, L. J., Davies, R. I., et al. 2010, ApJ, 724, 233 Evans, A. S., Mazzarella, J. M., Surace, J. A., et al. 2005, ApJS, 159, 197 Fabian, A. C. 1999, MNRAS, 308, L39 Farrah, D., Rowan-Robinson, M., Oliver, S., et al. 2001, MNRAS, 326, 1333 Farrah, D., Lonsdale, C. J., Borys, C., et al. 2006, ApJL, 641, L17 Fernández Lorenzo, M., Sulentic, J., Verdes-Montenegro, L., & Argudo-Fernández, M. 2013, MNRAS, 434, 325 Fixsen, D. J., Dwek, E., Mather, J. C., Bennett, C. L., & Shafer, R. A. 1998, ApJ, 508, 123 Forrest, B., Tran, K.-V. H., Tomczak, A. R., et al. 2016, ApJL, 818, L26 Franco, M., Elbaz, D., Béthermin, M., et al. 2018, A&A, 620, A152 Frayer, D. T., Ivison, R. J., Scoville, N. Z., et al. 1998, ApJL, 506, L7 Friedman, J. H. 2000, Annals of Statistics, 29, 1189 —. 2002, Comput. Stat. Data Anal., 38, 367 G. Cochran, W. 1952, Ann. Math. Stat., 23, 315 Galliano, F. 2017, Planet. Space Sci., 149, 38 Geach, J. E., Chapin, E. L., Coppin, K. E. K., et al. 2013, MNRAS, 432, 53 Geach, J. E., Dunlop, J. S., Halpern, M., et al. 2017, MNRAS, 465, 1789 Georgantopoulos, I., Rovilos, E., & Comastri, A. 2011, A&A, 526, A46 Gilli, R., Daddi, E., Chary, R., et al. 2007, A&A, 475, 83 Goldader, J. D., Meurer, G., Heckman, T. M., et al. 2002, ApJ, 568, 651 Gordon, K. D., Clayton, G. C., Misselt, K. A., Landolt, A. U., & Wolff, M. J. 2003, ApJ, 594, 279 Goto, T., Takagi, T., Matsuhara, H., et al. 2010, A&A, 514, A6 Greve, T. R., Pope, A., Scott, D., et al. 2008, MNRAS, 389, 1489 Greve, T. R., Bertoldi, F., Smail, I., et al. 2005, MNRAS, 359, 1165 Griffin, M. J., Abergel, A., Abreu, A., et al. 2010, A&A, 518, L3 Grogin, N. A., Kocevski, D. D., Faber, S. M., et al. 2011, ApJS, 197, 35 Gruppioni, C., Pozzi, F., Rodighiero, G., et al. 2013, MNRAS, 432, 23 Hainline, L. J., Blain, A. W., Smail, I., et al. 2011, ApJ, 740, 96 Harikane, Y., Ouchi, M., Ono, Y., et al. 2016, ApJ, 821, 123 Hartley, W. G., Lane, K. P., Almaini, O., et al. 2008, MNRAS, 391, 1301 Hartley, W. G., Almaini, O., Cirasuolo, M., et al. 2010, MNRAS, 407, 1212 Hasinger, G., Miyaji, T., & Schmidt, M. 2005, A&A, 441, 417 Hasinger, G., Capak, P., Salvato, M., et al. 2018, ApJ, 858, 77 Hatsukade, B., Kohno, K., Aretxaga, I., et al. 2011, MNRAS, 411, 102 Hatsukade, B., Kohno, K., Umehata, H., et al. 2016, PASJ, 68, 36 Hatsukade, B., Kohno, K., Yamaguchi, Y., et al. 2018, PASJ, 70, 105 Hayward, C. C., Kereš, D., Jonsson, P., et al. 2011, ApJ, 743, 159 Hayward, C. C., Narayanan, D., Kereš, D., et al. 2013, MNRAS, 428, 2529 Heinis, S., Buat, V., Béthermin, M., et al. 2013, MNRAS, 429, 1113 Helou, G., Soifer, B. T., & Rowan-Robinson, M. 1985, ApJL, 298, L7 Hickox, R. C., Wardlow, J. L., Smail, I., et al. 2012, MNRAS, 421, 284 Hildebrandt, H., Pielorz, J., Erben, T., et al. 2009, A&A, 498, 725 Hodge, J. A., Swinbank, A. M., Simpson, J. M., et al. 2016, ApJ, 833, 103 Holland, W. S., Robson, E. I., Gear, W. K., et al. 1999, MNRAS, 303, 659 Holland, W. S., Bintley, D., Chapin, E. L., et al. 2013, MNRAS, 430, 2513 Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2005a, ApJ, 630, 705 —. 2006, ApJS, 163, 1 Hopkins, P. F., Hernquist, L., Cox, T. J., & Kereš, D. 2008, ApJS, 175, 356 Hopkins, P. F., Hernquist, L., Martini, P., et al. 2005b, ApJL, 625, L71 Howell, J. H., Armus, L., Mazzarella, J. M., et al. 2010, ApJ, 715, 572 Hsu, L.-Y., Cowie, L. L., Chen, C.-C., Barger, A. J., & Wang, W.-H. 2016, ApJ, 829, 25 Hughes, D. H., Serjeant, S., Dunlop, J., et al. 1998, Nature, 394, 241 Hung, C.-L., Sanders, D. B., Casey, C. M., et al. 2013, ApJ, 778, 129 Hurley, P. D., Oliver, S., Betancourt, M., et al. 2017, MNRAS, 464, 885 Hwang, H. S., Elbaz, D., Dickinson, M., et al. 2011, A&A, 535, A60 Ibar, E., Ivison, R. J., Biggs, A. D., et al. 2009, MNRAS, 397, 281 Ichikawa, T., Kajisawa, M., & Akhlaghi, M. 2012, MNRAS, 422, 1014 Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006, A&A, 457, 841 Ilbert, O., McCracken, H. J., Le Fèvre, O., et al. 2013, A&A, 556, A55 Infante, L. 1994, A&A, 282, 353 Iono, D., Wilson, C. D., Yun, M. S., et al. 2009, ApJ, 695, 1537 Ivison, R. J., Smail, I., Papadopoulos, P. P., et al. 2010a, MNRAS, 404, 198 Ivison, R. J., Alexander, D. M., Biggs, A. D., et al. 2010b, MNRAS, 402, 245 Ivison, R. J., Lewis, A. J. R., Weiss, A., et al. 2016, ApJ, 832, 78 Jenness, T., Cavanagh, B., Economou, F., & Berry, D. S. 2008, in Astronomical Society of the Pacific Conference Series, Vol. 394, Astronomical Data Analysis Software and Systems XVII, ed. R. W. Argyle, P. S. Bunclark, & J. R. Lewis, 565 Ji, Z., Giavalisco, M., Williams, C. C., et al. 2018, ApJ, 862, 135 Johnson, S. P., Wilson, G. W., Wang, Q. D., et al. 2013, MNRAS, 431, 662 Jones, E., Oliphant, T., & Peterson, P. 2001 Jose, C., Baugh, C. M., Lacey, C. G., & Subramanian, K. 2017, MNRAS, 469, 4428 Joseph, R. D., & Wright, G. S. 1985, MNRAS, 214, 87 Karim, A., Swinbank, A. M., Hodge, J. A., et al. 2013, MNRAS, 432, 2 Kashikawa, N., Yoshida, M., Shimasaku, K., et al. 2006, ApJ, 637, 631 Kennicutt, R. C., & Evans, N. J. 2012, ARA&A, 50, 531 Kim, J.-h., Wise, J. H., & Abel, T. 2009, ApJL, 694, L123 Klaassen, P., Mroczkowski, T., Bryan, S., et al. 2019, in BAAS, Vol. 51, 58 Koekemoer, A. M., Faber, S. M., Ferguson, H. C., et al. 2011, ApJS, 197, 36 Kohavi, R. 1995, in Proceedings of the 14th International Joint Conference on Artificial Intelligence - Volume 2, IJCAI’95 (San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.), 1137–1143. http://dl.acm.org/citation.cfm?id=1643031.1643047 Kong, X., Charlot, S., Brinchmann, J., & Fall, S. M. 2004, MNRAS, 349, 769 Koprowski, M. P., Dunlop, J. S., Michałowski, M. J., et al. 2017, MNRAS, 471, 4155 —. 2016a, MNRAS, 458, 4321 Koprowski, M. P., Coppin, K. E. K., Geach, J. E., et al. 2016b, ApJL, 828, L21 Kovács, A., Chapman, S. C., Dowell, C. D., et al. 2006, ApJ, 650, 592 Kriek, M., & Conroy, C. 2013, ApJL, 775, L16 Kroupa, P. 2001, MNRAS, 322, 231 Kroupa, P., & Weidner, C. 2003, ApJ, 598, 1076 Lagache, G., Dole, H., & Puget, J.-L. 2003, MNRAS, 338, 555 Laigle, C., McCracken, H. J., Ilbert, O., et al. 2016, ApJS, 224, 24 Laird, E. S., Nandra, K., Pope, A., & Scott, D. 2010, MNRAS, 401, 2763 Landy, S. D., & Szalay, A. S. 1993, ApJ, 412, 64 Lang, P., Schinnerer, E., Smail, I., et al. 2019, ApJ, 879, 54 Laurent, G. T., Aguirre, J. E., Glenn, J., et al. 2005, ApJ, 623, 742 Le Fèvre, O., Tasca, L. A. M., Cassata, P., et al. 2015, A&A, 576, A79 Lee, K.-S., Giavalisco, M., Gnedin, O. Y., et al. 2006, ApJ, 642, 63 Liang, L., Feldmann, R., Kereš, D., et al. 2019, MNRAS, 489, 1397 Lilly, S. J., Eales, S. A., Gear, W. K. P., et al. 1999, ApJ, 518, 641 Lilly, S. J., Le Fèvre, O., Renzini, A., et al. 2007, ApJS, 172, 70 Lilly, S. J., Le Brun, V., Maier, C., et al. 2009, ApJS, 184, 218 Lim, C.-F., Wang, W.-H., Smail, I., et al. 2020, ApJ, 889, 80 Limber, D. N. 1953, ApJ, 117, 134 Lin, L., Cooper, M. C., Jian, H.-Y., et al. 2010, ApJ, 718, 1158 Lin, L., Dickinson, M., Jian, H.-Y., et al. 2012, ApJ, 756, 71 Lin, L., Capak, P. L., Laigle, C., et al. 2016, ApJ, 817, 97 Lindner, R. R., Baker, A. J., Omont, A., et al. 2011, ApJ, 737, 83 Lo Faro, B., Buat, V., Roehlly, Y., et al. 2017, MNRAS, 472, 1372 MacKenzie, T. P., Scott, D., & Swinbank, M. 2016, MNRAS, 463, 10 Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415 Maddox, S. J., Dunne, L., Rigby, E., et al. 2010, A&A, 518, L11 Magliocchetti, M., Lapi, A., Negrello, M., De Zotti, G., & Danese, L. 2014, MNRAS, 437, 2263 Magliocchetti, M., Silva, L., Lapi, A., et al. 2007, Monthly Notices of the Royal Astronomical Society, 375, 1121 Magliocchetti, M., Cirasuolo, M., McLure, R. J., et al. 2008, MNRAS, 383, 1131 Magliocchetti, M., Popesso, P., Rosario, D., et al. 2013, MNRAS, 433, 127 Magnelli, B., Lutz, D., Santini, P., et al. 2012, A&A, 539, A155 Magnelli, B., Popesso, P., Berta, S., et al. 2013, A&A, 553, A132 Magnelli, B., Lutz, D., Saintonge, A., et al. 2014, A&A, 561, A86 Maraston, C., Pforr, J., Renzini, A., et al. 2010, MNRAS, 407, 830 Marsden, D., Gralla, M., Marriage, T. A., et al. 2014, MNRAS, 439, 1556 McCracken, H. J., Capak, P., Salvato, M., et al. 2010, ApJ, 708, 202 McCracken, H. J., Wolk, M., Colombi, S., et al. 2015, MNRAS, 449, 901 McLure, R. J., Dunlop, J. S., Cullen, F., et al. 2018, MNRAS, 476, 3991 Menéndez-Delmestre, K., Blain, A. W., Swinbank, M., et al. 2013, ApJ, 767, 151 Merlin, E., Fontana, A., Ferguson, H. C., et al. 2015, A&A, 582, A15 Meurer, G. R., Heckman, T. M., & Calzetti, D. 1999, ApJ, 521, 64 Michałowski, M., Hjorth, J., & Watson, D. 2010, A&A, 514, A67 Michałowski, M. J., Dunlop, J. S., Cirasuolo, M., et al. 2012a, A&A, 541, A85 Michałowski, M. J., Hayward, C. C., Dunlop, J. S., et al. 2014, A&A, 571, A75 Michałowski, M. J., Dunlop, J. S., Ivison, R. J., et al. 2012b, MNRAS, 426, 1845 Michałowski, M. J., Dunlop, J. S., Koprowski, M. P., et al. 2017, MNRAS, 469, 492 Miller, T. B., Chapman, S. C., Aravena, M., et al. 2018, Nature, 556, 469 Mitchell-Wynne, K., Cooray, A., Gong, Y., et al. 2012, The Astrophysical Journal, 753, 23 Mocanu, L. M., Crawford, T. M., Vieira, J. D., et al. 2013, ApJ, 779, 61 Mortier, A. M. J., Serjeant, S., Dunlop, J. S., et al. 2005, Monthly Notices of the Royal Astronomical Society, 363, 563 Murakami, H., Baba, H., Barthel, P., et al. 2007, PASJ, 59, S369 Murphy, E. J., Chary, R.-R., Dickinson, M., et al. 2011, ApJ, 732, 126 Myers, A. D., Brunner, R. J., Nichol, R. C., et al. 2007, ApJ, 658, 85 Myers, A. D., Brunner, R. J., Richards, G. T., et al. 2006, ApJ, 638, 622 Narayanan, D., Conroy, C., Davé, R., Johnson, B. D., & Popping, G. 2018a, ApJ, 869, 70 Narayanan, D., Davé, R., Johnson, B. D., et al. 2018b, MNRAS, 474, 1718 Neugebauer, G., Habing, H. J., van Duinen, R., et al. 1984, ApJL, 278, L1 Newman, A. B., Ellis, R. S., Bundy, K., & Treu, T. 2012, ApJ, 746, 162 Noll, S., & Pierini, D. 2005, A&A, 444, 137 Noll, S., Pierini, D., Pannella, M., & Savaglio, S. 2007, A&A, 472, 455 Noll, S., Pierini, D., Cimatti, A., et al. 2009, A&A, 499, 69 Norberg, P., Baugh, C. M., Gaztañaga, E., & Croton, D. J. 2009, MNRAS, 396, 19 Oteo, I., Cepa, J., Bongiovanni, Á., et al. 2013, A&A, 554, L3 Ouchi, M., Hamana, T., Shimasaku, K., et al. 2005, ApJL, 635, L117 Overzier, R. A., Heckman, T. M., Wang, J., et al. 2011, ApJL, 726, L7 Peacock, J. A. 1983, MNRAS, 202, 615 —. 1991, MNRAS, 253, 1P Pearson, K. 1900, Phil. Mag. Series 5, 50, 157 Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, Journal of Machine Learning Research, 12, 2825 Peebles, P. J. E. 1980, Princeton, NJ: Princeton Univ. Press Pei, Y. C. 1992, ApJ, 395, 130 Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2010, AJ, 139, 2097 Pforr, J., Maraston, C., & Tonini, C. 2012, MNRAS, 422, 3285 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2014, A&A, 571, A16 Poglitsch, A., Waelkens, C., Geis, N., et al. 2010, A&A, 518, L2 Polletta, M., Tajer, M., Maraschi, L., et al. 2007, ApJ, 663, 81 Pope, A., Scott, D., Dickinson, M., et al. 2006, MNRAS, 370, 1185 Popping, G., Puglisi, A., & Norman, C. A. 2017, MNRAS, 472, 2315 Porciani, C., & Norberg, P. 2006, MNRAS, 371, 1824 Pozzetti, L., Bolzonella, M., Zucca, E., et al. 2010, A&A, 523, A13 Provost, F., Fawcett, T., & Kohavi, R. 1997, In Proceedings of the Fifteenth International Conference on Machine Learning, 445 Puget, J. L., Abergel, A., Bernard, J. P., et al. 1996, A&A, 308, L5 Ranalli, P., Comastri, A., & Setti, G. 2003, A&A, 399, 39 Reddy, N. A., Erb, D. K., Pettini, M., Steidel, C. C., & Shapley, A. E. 2010, ApJ, 712, 1070 Reddy, N. A., Oesch, P. A., Bouwens, R. J., et al. 2018, ApJ, 853, 56 Rennehan, D., Babul, A., Hayward, C. C., et al. 2019, arXiv e-prints, arXiv:1907.00977. https://arxiv.org/abs/1907.00977 Riechers, D. A., Bradford, C. M., Clements, D. L., et al. 2013, Nature, 496, 329 Rieke, G. H., Alonso-Herrero, A., Weiner, B. J., et al. 2009, ApJ, 692, 556 Rieke, G. H., Young, E. T., Engelbracht, C. W., et al. 2004, ApJS, 154, 25 Rijsbergen, C. J. V. 1979, Information Retrieval, 2nd edn. (Newton, MA, USA: Butterworth-Heinemann) Robitaille, T. P., & Whitney, B. A. 2010, ApJL, 710, L11 Roche, N., & Eales, S. A. 1999, MNRAS, 307, 703 Rodighiero, G., Daddi, E., Baronchelli, I., et al. 2011, ApJL, 739, L40 Romano, D., Matteucci, F., Zhang, Z. Y., Papadopoulos, P. P., & Ivison, R. J. 2017, MNRAS, 470, 401 Roseboom, I. G., Oliver, S. J., Kunz, M., et al. 2010, MNRAS, 409, 48 Roseboom, I. G., Ivison, R. J., Greve, T. R., et al. 2012, MNRAS, 419, 2758 Roseboom, I. G., Dunlop, J. S., Cirasuolo, M., et al. 2013, MNRAS, 436, 430 Rowan-Robinson, M., Oliver, S., Wang, L., et al. 2016, MNRAS, 461, 1100 Safarzadeh, M., Hayward, C. C., & Ferguson, H. C. 2017, ApJ, 840, 15 Salmon, B., Papovich, C., Long, J., et al. 2016, ApJ, 827, 20 Salpeter, E. E. 1955, ApJ, 121, 161 Sandage, A., Tammann, G. A., & Yahil, A. 1979, ApJ, 232, 352 Sanders, D. B., & Mirabel, I. F. 1996, ARA&A, 34, 749 Sanders, D. B., Soifer, B. T., Elias, J. H., et al. 1988a, ApJ, 325, 74 Sanders, D. B., Soifer, B. T., Elias, J. H., Neugebauer, G., & Matthews, K. 1988b, ApJL, 328, L35 Sanders, D. B., Salvato, M., Aussel, H., et al. 2007, ApJS, 172, 86 Sato, T., Sawicki, M., & Arcila-Osejo, L. 2014, MNRAS, 443, 2661 Saunders, W., Rowan-Robinson, M., Lawrence, A., et al. 1990, MNRAS, 242, 318 Schechter, P. 1976, ApJ, 203, 297 Schmidt, M. 1968, ApJ, 151, 393 Schmidt, M., Schneider, D. P., & Gunn, J. E. 1995, AJ, 110, 68 Schreiber, C., Elbaz, D., Pannella, M., et al. 2018, A&A, 609, A30 Scott, K. S., Austermann, J. E., Perera, T. A., et al. 2008, MNRAS, 385, 2225 Scott, S. E., Fox, M. J., Dunlop, J. S., et al. 2002, Monthly Notices of the Royal Astronomical Society, 331, 817 Scoville, N., Aussel, H., Brusa, M., et al. 2007, ApJS, 172, 1 Scranton, R., Johnston, D., Dodelson, S., et al. 2002, ApJ, 579, 48 Sérsic, J. L. 1963, Boletin de la Asociacion Argentina de Astronomia La Plata Argentina, 6, 41 —. 1968, Atlas de Galaxias Australes Shen, S., Mo, H. J., White, S. D. M., et al. 2003, MNRAS, 343, 978 Shen, Y., Strauss, M. A., Oguri, M., et al. 2007, AJ, 133, 2222 Sheth, R. K., Mo, H. J., & Tormen, G. 2001, MNRAS, 323, 1 Silk, J., & Rees, M. J. 1998, A&A, 331, L1 Simpson, J. M., Swinbank, A. M., Smail, I., et al. 2014, The Astrophysical Journal, 788, 125 Simpson, J. M., Smail, I., Swinbank, A. M., et al. 2015, ApJ, 807, 128 —. 2017, ApJ, 839, 58 —. 2019, ApJ, 880, 43 Smail, I., Chapman, S. C., Blain, A. W., & Ivison, R. J. 2004, ApJ, 616, 71 Smail, I., Ivison, R. J., & Blain, A. W. 1997, The Astrophysical Journal Letters, 490, L5 Smail, I., Ivison, R. J., Blain, A. W., & Kneib, J.-P. 2002, MNRAS, 331, 495 Smith, R. E., Peacock, J. A., Jenkins, A., et al. 2003, MNRAS, 341, 1311 Smolčić, V., Delvecchio, I., Zamorani, G., et al. 2017, A&A, 602, A2 Sobral, D., Best, P. N., Smail, I., et al. 2011, MNRAS, 411, 675 Solarz, A., Pollo, A., Takeuchi, T. T., et al. 2015, A&A, 582, A58 Sorba, R., & Sawicki, M. 2015, MNRAS, 452, 235 —. 2018, MNRAS, 476, 1532 Speagle, J. S., Steinhardt, C. L., Capak, P. L., & Silverman, J. D. 2014, ApJS, 214, 15 Springel, V. 2005, MNRAS, 364, 1105 Stach, S. M., Dudzevičiūtė, U., Smail, I., et al. 2019, MNRAS, 487, 4648 Staguhn, J. G., Kovács, A., Arendt, R. G., et al. 2014, ApJ, 790, 77 Starikova, S., Berta, S., Franceschini, A., et al. 2012, ApJ, 751, 126 Stecher, T. P. 1965, ApJ, 142, 1683 Swinbank, A. M., Smail, I., Chapman, S. C., et al. 2004, ApJ, 617, 64 —. 2010, MNRAS, 405, 234 Swinbank, A. M., Simpson, J. M., Smail, I., et al. 2014, MNRAS, 438, 1267 Swinbank, M., Smail, I., Lindner, C., et al. 2006, arXiv Astrophysics e-prints Symeonidis, M., Vaccari, M., Berta, S., et al. 2013, MNRAS, 431, 2317 Szokoly, G. P., Bergeron, J., Hasinger, G., et al. 2004, ApJS, 155, 271 Tacconi, L. J., Neri, R., Chapman, S. C., et al. 2006, ApJ, 640, 228 Tacconi, L. J., Genzel, R., Smail, I., et al. 2008, ApJ, 680, 246 Takahashi, R., Sato, M., Nishimichi, T., Taruya, A., & Oguri, M. 2012, ApJ, 761, 152 Targett, T. A., Dunlop, J. S., McLure, R. J., et al. 2011, MNRAS, 412, 295 Targett, T. A., Dunlop, J. S., Cirasuolo, M., et al. 2013, MNRAS, 432, 2012 Teyssier, R., Chapon, D., & Bournaud, F. 2010, ApJL, 720, L149 Thomson, A. P., Ivison, R. J., Simpson, J. M., et al. 2014, MNRAS, 442, 577 Thomson, A. P., Smail, I., Swinbank, A. M., et al. 2019, ApJ, 883, 204 To, C.-H., Wang, W.-H., & Owen, F. N. 2014, ApJ, 792, 139 Toba, Y., Nagao, T., Kajisawa, M., et al. 2017, ApJ, 835, 36 Toft, S., Smolčić, V., Magnelli, B., et al. 2014, ApJ, 782, 68 Trayford, J. W., Theuns, T., Bower, R. G., et al. 2016, MNRAS, 460, 3925 Trump, J. R., Impey, C. D., Elvis, M., et al. 2009, ApJ, 696, 1195 U, V., Sanders, D. B., Mazzarella, J. M., et al. 2012, ApJS, 203, 9 van der Wel, A., Bell, E. F., Häussler, B., et al. 2012, ApJS, 203, 24 van der Wel, A., Franx, M., van Dokkum, P. G., et al. 2014, ApJ, 788, 28 van Kampen, E., Smith, D. J. B., Maddox, S., et al. 2012, MNRAS, 426, 3455 Vieira, J. D., Crawford, T. M., Switzer, E. R., et al. 2010, ApJ, 719, 763 Wall, J. V., Pope, A., & Scott, D. 2008, MNRAS, 383, 435 Wang, R., Carilli, C. L., Beelen, A., et al. 2007, AJ, 134, 617 Wang, S. X., Brandt, W. N., Luo, B., et al. 2013, ApJ, 778, 179 Wang, T., Schreiber, C., Elbaz, D., et al. 2019, Nature, 572, 211 Wang, W.-H., Cowie, L. L., & Barger, A. J. 2004, ApJ, 613, 655 Wang, W.-H., Lin, W.-C., Lim, C.-F., et al. 2017, ApJ, 850, 37 Wardlow, J. L., Smail, I., Coppin, K. E. K., et al. 2011, MNRAS, 415, 1479 Watson, D., Christensen, L., Knudsen, K. K., et al. 2015, Nature, 519, 327 Webb, T. M., Eales, S., Foucaud, S., et al. 2003a, ApJ, 582, 6 —. 2003b, ApJ, 582, 6 Weiß, A., Kovács, A., Coppin, K., et al. 2009a, ApJ, 707, 1201 —. 2009b, ApJ, 707, 1201 Wild, V., Charlot, S., Brinchmann, J., et al. 2011, MNRAS, 417, 1760 Wilkinson, A., Almaini, O., Chen, C.-C., et al. 2017, MNRAS, 464, 1380 Williams, C. C., Giavalisco, M., Porciani, C., et al. 2011, ApJ, 733, 92 Wuyts, S., Förster Schreiber, N. M., Genzel, R., et al. 2012, ApJ, 753, 114 Younger, J. D., Hayward, C. C., Narayanan, D., et al. 2009, MNRAS, 396, L66 Yun, M. S., Scott, K. S., Guo, Y., et al. 2012, MNRAS, 420, 957 Zahid, H. J., Kashino, D., Silverman, J. D., et al. 2014, ApJ, 792, 75 Zavala, J. A., Aretxaga, I., Geach, J. E., et al. 2017, MNRAS, 464, 3369 Zavala, J. A., Aretxaga, I., Dunlop, J. S., et al. 2018, MNRAS, 475, 5585 Zehavi, I., Blanton, M. R., Frieman, J. A., et al. 2002, ApJ, 571, 172 Zehavi, I., Zheng, Z., Weinberg, D. H., et al. 2005, ApJ, 630, 1 Zezas, A. L., Georgantopoulos, I., & Ward, M. J. 1998, MNRAS, 301, 915 Zhang, Z.-Y., Romano, D., Ivison, R. J., Papadopoulos, P. P., & Matteucci, F. 2018, Nature, 558, 260 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63949 | - |
| dc.description.abstract | 本論文的研究對象主要是在次毫米波觀測到的星系，探討它們的
物理性質，從而進一步瞭解它們的生成以及演化。這些星系是經由15 米的詹姆士克拉克麥斯威爾望遠鏡中鑲嵌的SCUBA-2 儀器觀測得到。 本論文結合了SCUBA-2 最新的大型觀測計畫（STUDIES）以及所有 SCUBA-2 在COSMOS 巡天場裡的公開資料，建構了有史以來最深的 450 微米影像，其觀測靈敏度在最深的區域大約是0.6 斯基。本論文 的第一部分探討了這些星系的物理性質，例如：紅移、恆星生成率、 恆星質量、紅外光度以及塵埃輻射溫度。對於紅移小於3 以及紅外光 度大於太陽光度十的十二次方倍的450 微米星系，其塵埃輻射溫度並沒有隨著 紅移而有所演化。但是它們的塵埃輻射溫度與其於恆星生成主星序的 距離成正向關係。此外，塵埃輻射溫度也與其可見光形態有關聯，符 合了次毫米星系中的星暴成因是藉由星系間碰撞及併吞引發的。本論 文也計算了450 微米星系的光度函數以及它們的恆星生成率密度。在 紅移0 到2 之間，大於太陽光度十的十二次方倍的450 微米星系貢獻於恆星生 成率密度逐漸提升，並主導了紅移大於2 的區間。本論文的第二部分 利用了450 微米觀測到的次毫米波星系以及K-譜帶觀測到的非次毫米 波星系做為研究的基底，並透過機器學習的分類方法發展了一個分類 器。這個機器學習的分類器可以被利用於大範圍的COSMOS 巡天場 （1.6 平方度），從而在整個COSMOS 巡天場內判斷出哪些星系是次毫 米波星系的候選星系。針對這些次毫米波候選星系在紅移0.5 到3 的 區間，本論文進行了星系的兩點相關函數的分析，從而發現它們的暈 質量大約是太陽質量的二乘十的十三次方倍。此外，它們的暈質量並沒有顯示 出強烈的紅移演化關係。本研究旨在擴大我們對次毫米波星系生成與 演化的瞭解。 | zh_TW |
| dc.description.abstract | In my thesis, I studied a sample of sub-millimeter galaxies (SMGs), aiming
at unveiling their physical properties and providing insight in the physical processes shaping galaxy formation and evolution. I based the analysis on the 450-μm data obtained from the SCUBA-2 camera on the 15-m James Clerk Maxwell Telescope (JCMT). By combining a new SCUBA-2 imaging survey from the ongoing JCMT Large Program - SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES) and all the archival data in the CANDELS/ COSMOS field, I constructed an extremely deep single-dish image across an area of 300 arcmin^2 at 450μm (S450μm ≃ 0.6 mJy beam^-1). This image is the deepest ever observed at 450μm. In the first part of my thesis, I probed the physical properties of the 450-μm-selected galaxies, such as redshift, star-formation rate (SFR), stellar mass (M *), infrared luminosity (LIR), and dust temperature (Td). I did not find a redshift evolution in dust temperature for sources with LIR > 10^12 L⊙ at z < 3. I found a moderate correlation between the dust temperature and the deviation from the SFR–M * relation. The increase in dust temperature also correlates with optical morphology, which is consistent with merger-triggered starbursts in submillimeter galaxies. I constructed the infrared luminosity functions of the 450-μm sources and measure their comoving SFR densities (SFRDs). I discovered that the contribution of the LIR > 10^12 L⊙ population to the SFRD rises dramatically from z = 0 to 2 and dominates the total SFRD at z ≳ 2. In the second part of my thesis, I developed a machine-learning classifier using optical-to-near-infrared colors from the 450-μm-selected SMGs and a sample of K-band-selected non-SMGs. I employed the trained machine-learning classifier to the general COSMOS field (1.6 deg^2) and identified a sample of SMG candidates with similar colors to the training SMG sample. I measured the two-point autocorrelation functions and found that the SMG candidates reside in massive halos of ≃ (2+-0.5) 10^13 h^-1M⊙ across the redshift range of z = 0.5–3.0. I did not find evidence of downsizing that is suggested by recent observational studies. The work presented in this dissertation contributes to widening our understanding of the evolution of SMGs. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T17:24:05Z (GMT). No. of bitstreams: 1 ntu-109-D04244001-1.pdf: 12100736 bytes, checksum: 5a688a53fbba55c5f16edec0f550af4a (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 誌謝ii
摘要iii Abstract v 1 Introduction 1 1.1 A typical galactic spectral energy distribution . . . . . . . . . . . . . . . 1 1.2 Infrared/Sub-millimeter Observations . . . . . . . . . . . . . . . . . . . 1 1.3 Local Infrared-luminous Galaxies . . . . . . . . . . . . . . . . . . . . . 3 1.4 Sub-millimeter Galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.5 The 450-mm observations . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.6 Thesis Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 Multi-wavelength Properties and Luminosity Functions 10 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Multi-wavelength Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.1 SCUBA-2 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.2 Ancillary Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.3 Source Extraction and Counterpart Identification . . . . . . . . . . . . . 22 2.3.1 Source Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.3.2 Counterpart Identification . . . . . . . . . . . . . . . . . . . . . 24 2.3.3 Unidentified Sources . . . . . . . . . . . . . . . . . . . . . . . . 25 2.4 Deriving Physical Parameters . . . . . . . . . . . . . . . . . . . . . . . . 28 2.4.1 AGN Contamination . . . . . . . . . . . . . . . . . . . . . . . . 28 2.4.2 Redshift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.4.3 Stellar Mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2.4.4 Infrared Luminosity . . . . . . . . . . . . . . . . . . . . . . . . 36 2.4.5 Dust Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.4.6 Ultraviolet-continuum Slope and Ultraviolet Luminosity . . . . . 40 2.4.7 SFRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.4.8 Radio Power at 1.4 GHz . . . . . . . . . . . . . . . . . . . . . . 42 2.5 The Nature of SCUBA-2 450-mm-selected Sources . . . . . . . . . . . . 43 2.5.1 The Star-formation Main Sequence . . . . . . . . . . . . . . . . 44 2.5.2 Td–LIR Correlation . . . . . . . . . . . . . . . . . . . . . . . . . 50 2.5.3 IRX–bUV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 2.6 Infrared Luminosity Function . . . . . . . . . . . . . . . . . . . . . . . . 59 2.6.1 1/Vmax Method . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 2.6.2 Likelihood Method . . . . . . . . . . . . . . . . . . . . . . . . . 62 2.6.3 Comparison with Other Observations . . . . . . . . . . . . . . . 65 2.6.4 Comparison with Models . . . . . . . . . . . . . . . . . . . . . . 66 2.7 The Obscured Star-formation History . . . . . . . . . . . . . . . . . . . 68 2.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3 Spatial Clustering and Halo Masses 75 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 3.2 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.2.1 Main Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.2.2 Ancillary Data . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 3.2.3 Training Sample . . . . . . . . . . . . . . . . . . . . . . . . . . 82 3.3 Machine-Learning Methodology . . . . . . . . . . . . . . . . . . . . . . 84 3.3.1 Performance Measures of Classification . . . . . . . . . . . . . . 84 3.3.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 3.3.3 Feature Selection . . . . . . . . . . . . . . . . . . . . . . . . . . 86 3.3.4 Tuning Hyper-parameters . . . . . . . . . . . . . . . . . . . . . 87 3.3.5 Algorithms Comparison . . . . . . . . . . . . . . . . . . . . . . 88 3.4 Verifications of the SMG Candidates . . . . . . . . . . . . . . . . . . . . 89 3.5 Comparison Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 3.5.1 Rest-frame NUV-r-J Color . . . . . . . . . . . . . . . . . . . . . 93 3.5.2 Physical Properties of SMG Candidates and Comparison Samples 96 3.6 Clustering and Halo Mass . . . . . . . . . . . . . . . . . . . . . . . . . . 99 3.6.1 Two Point Auto-correlation Function . . . . . . . . . . . . . . . 101 3.6.2 Dark-matter Halo Mass . . . . . . . . . . . . . . . . . . . . . . . 103 3.6.3 Clustering Signals . . . . . . . . . . . . . . . . . . . . . . . . . 104 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 4 Conclusions 109 5 Future Works 111 5.1 A More Complete Picture of SMGs . . . . . . . . . . . . . . . . . . . . 111 5.2 Machine-learning De-blending Procedure for Far-infrared Photometry . . 111 5.3 Star-formation History of Dusty Population . . . . . . . . . . . . . . . . 112 A Monte Carlo Simulation 113 B Confusion Noises 116 C Long Tables 118 D Clustering Results of SMG Candidates Identified by Other Algorithms 129 Bibliography 131 | |
| dc.language.iso | en | |
| dc.title | 多波段性質、星系光度函數以及大尺度結構群聚於450微米星系的研究 | zh_TW |
| dc.title | Multi-wavelength properties, luminosity functions, and clustering measurements of 450-μm-selected galaxies | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.coadvisor | 王為豪(Wei-Hao Wang) | |
| dc.contributor.oralexamcommittee | 平下博之(Hiroyuki Hirashita),林彥廷(Yen-Ting Lin),陳建州(Chian-Chou Chen) | |
| dc.subject.keyword | 次毫米波星系,高紅移星系,星系形成,星系演化,星系光度函數,宇宙大尺度結構,機器學習, | zh_TW |
| dc.subject.keyword | sub-millimeter galaxy,high-redshift galaxy,galaxy formation,galaxy evolution,galaxy luminosity function,large-scale structure of universe,machine learning, | en |
| dc.relation.page | 149 | |
| dc.identifier.doi | 10.6342/NTU202000685 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-03-16 | |
| dc.contributor.author-college | 理學院 | zh_TW |
| dc.contributor.author-dept | 天文物理研究所 | zh_TW |
| 顯示於系所單位： | 天文物理研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-109-1.pdf 目前未授權公開取用 | 11.82 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。