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The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological implications of the full shape of the clustering wedges in the data release 10 and 11 galaxy samples

A. Sanchez, F. Montesano, E. Kazin, E. Aubourg, F. Beutler, J. Brinkmann, J. Brownstein, A. Cuesta, K. Dawson, D. Eisenstein, S. Ho, K. Honscheid, M. Manera, C. Maraston, C. McBride, W. Percival, A. Ross, L. Samushia, D. Schlegel, D. Schneider, R. Skibba, D. Thomas, J. Tinker, R. Tojeiro, D. Wake, B. Weaver, M. White, and I. Zehavi. (2013)cite arxiv:1312.4854Comment: 24 pages, 14 figures. Submitted to MNRAS. Measurements and covariance matrices are available at https://sdss3.org/science/boss_publications.php.

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Shirley Brückner

Shirley Atkinson

Shirley Schäfer

Shirley Williams

Shirley Knauer

Other publications of authors with the same name

Search for CII Emission on Cosmological Scales at Redshift Z~2.6A. Pullen, P. Serra, T. Chang, O. Dore, and S. Ho. (2017)cite arxiv:1707.06172Comment: 14 pages, 9 figures, to be submitted to MNRAS.Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task.S. Golkar, A. Bietti, M. Pettee, M. Eickenberg, M. Cranmer, K. Hirashima, G. Krawezik, N. Lourie, M. McCabe, R. Morel and 5 other author(s). CoRR, (2024)Multiple Physics Pretraining for Physical Surrogate Models.M. McCabe, B. Blancard, L. Parker, R. Ohana, M. Cranmer, A. Bietti, M. Eickenberg, S. Golkar, G. Krawezik, F. Lanusse and 4 other author(s). CoRR, (2023)Learning the Evolution of the Universe in N-body Simulations.C. Chen, Y. Li, F. Villaescusa-Navarro, S. Ho, and A. Pullen. CoRR, (2020)HInet: Generating neutral hydrogen from dark matter with neural networksD. Wadekar, F. Villaescusa-Navarro, S. Ho, and L. Perreault-Levasseur. (2020)cite arxiv:2007.10340Comment: 13 pages, 8 figures.Lagrangian Neural Networks.M. Cranmer, S. Greydanus, S. Hoyer, P. Battaglia, D. Spergel, and S. Ho. CoRR, (2020)Fast and Accurate Non-Linear Predictions of Universes with Deep Learning.R. de Oliveira, Y. Li, F. Villaescusa-Navarro, S. Ho, and D. Spergel. CoRR, (2020)The CAMELS project: Cosmology and Astrophysics with MachinE Learning SimulationsF. Villaescusa-Navarro, D. Anglés-Alcázar, S. Genel, D. Spergel, R. Somerville, R. Dave, A. Pillepich, L. Hernquist, D. Nelson, P. Torrey and 11 other author(s). (2020)cite arxiv:2010.00619Comment: 33 pages, 18 figures, CAMELS webpage at https://www.camel-simulations.org.Learning to Predict the Cosmological Structure Formation.S. He, Y. Li, Y. Feng, S. Ho, S. Ravanbakhsh, W. Chen, and B. Póczos. CoRR, (2018)The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological implications of the full shape of the clustering wedges in the data release 10 and 11 galaxy samplesA. Sanchez, F. Montesano, E. Kazin, E. Aubourg, F. Beutler, J. Brinkmann, J. Brownstein, A. Cuesta, K. Dawson, D. Eisenstein and 18 other author(s). (2013)cite arxiv:1312.4854Comment: 24 pages, 14 figures. Submitted to MNRAS. Measurements and covariance matrices are available at https://sdss3.org/science/boss_publications.php.

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Disambiguation of "Ho, Shirley"