A robust morphological classification of high-redshift galaxies using support vector machines on seeing limited images

Astronomy and Astrophysics

Volumn 497, Issue 3, 2009, Pages 743-753

  Huertas Company, M ^a,c   Tasca, L ^b   Rouan, D ^a   Pelat, D ^a   Kneib, J P ^b   Le Fevre O ^b   Capak, P ^e,f   Kartaltepe, J ^g   Koekemoer, A ⁱ   McCracken, H J ^d   Salvato, M ^e   Sanders, D B ^g   Willott, C ^h  

^a OBSERVATOIRE DE PARIS   (France)

^b CNRS   (France)

^c INSTITUTO DE ASTROFÍSICA DE ANDALUCÍA CSIC   (Spain)

^d INSTITUT D'ASTROPHYSIQUE DE PARIS   (France)

^e CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^f CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^g UNIVERSITY OF HAWAII   (United States)

^h UNIVERSITY OF OTTAWA   (Canada)

ⁱ STScI   (United States)

Author keywords

Galaxies: fundamental parameters; Galaxies: high redshift

Indexed keywords

GALAXIES: FUNDAMENTAL PARAMETERS; GALAXIES: HIGH-REDSHIFT; GALAXY EVOLUTIONS; HIGH-ANGULAR RESOLUTIONS; HIGH-REDSHIFT; LATE TYPES; MORPHOLOGICAL PARAMETERS; NON-PARAMETRIC METHODS; PHYSICAL PARAMETERS; PHYSICAL STRUCTURES; RED SHIFTS; REDSHIFT DISTRIBUTIONS; SEEING LIMITEDS; SPACE DATUM; STELLAR POPULATIONS; YOUNG STARS;

COSMOLOGY; IMAGE RETRIEVAL; MORPHOLOGY; POPULATION STATISTICS; SPACE PROBES; SUPPORT VECTOR MACHINES;

GALAXIES;

EID: 65449153635     PISSN: 00046361     EISSN: 14320746     Source Type: Journal    
DOI: 10.1051/0004-6361/200811255     Document Type: Article

References (39)

1. Abraham, R., van den Bergh, S., Glazebrook, K., et al. 1996, ApJS, 107, 1
2. Abraham, R. G., van den Bergh, S., & Nair, P. 2003, ApJ, 588, 218
3. Abraham, R. G., Nair, P., McCarthy, P. J., et al. 2007, ApJ, 669, 184
4. Arnouts, S.,Walcher, C. J., Le Fevre, O., et al. 2007, ArXiv e-prints, 705
5. Baker, A. J., Davies, R. I., Lehnert, M. D., et al. 2003, A&A, 406, 593
6. Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393
7. Brinchmann, J., Abraham, R., Schade, D., et al. 1998, ApJ, 499, 112
8. Bundy, K., Ellis, R. S., Conselice, C. J., et al. 2006, ApJ, 651, 120
9. Cassata, P., Cimatti, A., Franceschini, A., et al. 2005, MNRAS, 357, 903
10. Chang, C.-C.,& Lin, C.-J. 2001, LIBSVM: a library for support vector machines, software available at http://www.csie.ntu.edu.tw/̃cjlin/libsvm
11. Conselice, C., & GNS Team 2007, in Amer. Astron. Soc. Meet. Abstr., 211
12. Conselice, C. J., Bershady, M. A., & Jangren, A. 2000, ApJ, 529, 886
13. Conselice, C. J., Bershady, M. A., Dickinson, M., & Papovich, C. 2003, AJ, 126, 1183
14. Cresci, G., Davies, R. I., Baker, A. J., et al. 2006, A&A, 458, 385
15. de Vaucouleurs, G. 1948, Annales dAstrophysique, 11, 247
16. Freeman, K. C. 1970, ApJ, 160, 811
17. Gardner, J. P., Cowie, L. L., & Wainscoat, R. J. 1993, ApJ, 415, L9
18. Huertas-Company, M., Rouan, D., Soucail, G., et al. 2007, A&A, 468, 937
19. Huertas-Company, M., Rouan, D., Tasca, L., Soucail, G., & Le Fèvre, O. 2008, A&A, 478, 971
20. Ilbert, O., Arnouts, S., McCracken, H. J., et al. 2006a, ArXiv Astrophysics e-prints
21. Ilbert, O., Lauger, S., Tresse, L., et al. 2006b, A&A, 453, 809
22. Ilbert, O., Capak, P., Salvato, M., et al. 2009, ApJ, 690, 1236
23. Koekemoer, A. M., Aussel, H., Calzetti, D., et al. 2007, ApJS, 172, 196
24. Lotz, J. M., Primack, J., & Madau, P. 2004, AJ, 128, 163
25. Madgwick, D. S., Lahav, O., Baldry, I. K., et al. 2002, MNRAS, 333, 133
26. Maihara, T., Iwamuro, F., Tanabe, H., et al. 2001, PASJ, 53, 25
27. McCracken, H. J., Metcalfe, N., Shanks, T. et al. 2000a, MNRAS, 311, 707
28. McCracken, H. J., Metcalfe, N., Shanks, T., et al.. 2000b, MNRAS, 311, 707
29. Menanteau, F., Ellis, R. S., Abraham, R. G., Barger, A. J., & Cowie, L. L. 1999, MNRAS, 309, 208
30. Menanteau, F., Ford, H. C., Motta, V., et al. 2006, AJ, 131, 208
31. Platt, J. 2000, Advances in Large Margin Classifiers
32. Saracco, P., Longhetti, M., Andreon, S., & Mignano, A. 2008, ArXiv e-prints, 801
33. Scoville, N. Z., & COSMOS Team. 2005, in BAAS, 1309
34. Tasca, L., & White, S. 2005, [arXiv:astro-ph/0507249]
35. Thibault, S., Cui, Q., Poirier, M., et al. 2003, in Instrument Design and Performance for Optical/Infrared Ground-based Telescopes, ed. M. Iye, & A. F. M. Moorwood, Proc. SPIE, 4841
36. Wolf, C., Meisenheimer, K., Rix, H.-W., et al. 2003, A&A, 401, 73
37. Wu, T. F., J., L. C., & C., W. R. 2004, J. Machine Learning Res., 5, 975
38. Zirm, A. W., Stanford, S. A., Postman, M., et al. 2008, ArXiv e-prints, 802
39. Zucca, E., Ilbert, O., Bardelli, S., et al. 2006, A&A, 455, 879