Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology
I. Sevilla-Noarbe, K. Bechtol, M. Carrasco Kind, A. Carnero Rosell, M. R. Becker, A. Drlica-Wagner, R. A. Gruendl, E. S. Rykoff, E. Sheldon, B. Yanny, A. Alarco… 展开作者
I. Sevilla-Noarbe, K. Bechtol, M. Carrasco Kind, A. Carnero Rosell, M. R. Becker, A. Drlica-Wagner, R. A. Gruendl, E. S. Rykoff, E. Sheldon, B. Yanny, A. Alarcon, S. Allam, A. Amon, A. Benoit-Lévy, G. M. Bernstein, E. Bertin, D. L. Burke, J. Carretero, A. Choi, H. T. Diehl, S. Everett, B. Flaugher, E. Gaztanaga, J. Gschwend, I. Harrison, W. G. Hartley, B. Hoyle, M. Jarvis, M. D. Johnson, R. Kessler, R. Kron, N. Kuropatkin, B. Leistedt, T. S. Li, F. Menanteau, E. Morganson, R. L. C. Ogando, A. Palmese, F. Paz-Chinchón, A. Pieres, C. Pond, M. Rodriguez-Monroy, J. Allyn-Smith, K. M. Stringer, M. A. Troxel, D. L. Tucker, J. de Vicente, W. Wester, Y. Zhang, T. M. C. Abbott, M. Aguena, J. Annis, S. Avila, S. Bhargava, S. L. Bridle, D. Brooks, D. Brout, F. J. Castander, R. Cawthon, C. Chang, C. Conselice, M. Costanzi, M. Crocce, L. N. da Costa, M. E. E. Pereira, T. M. Davis, S. Desai, J. P. Dietrich, P. Doel, K. Eckert, A. E. Evrard, I. Ferrero, P. Fosalba, J. García-Bellido, D. W. Gerdes, T. Giannantonio, D. Gruen, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, E. M. Huff, D. Huterer, D. J. James, T. Jeltema, K. Kuehn, O. Lahav, C. Lidman, M. Lima, H. Lin, M. A. G. Maia, J. L. Marshall, P. Martini, P. Melchior, R. Miquel, J. J. Mohr, R. Morgan, E. Neilsen, A. A. Plazas, A. K. Romer, A. Roodman, E. Sanchez, V. Scarpine, M. Schubnell, S. Serrano, M. Smith, E. Suchyta, G. Tarle, D. Thomas, C. To, T. N. Varga, R. H. Wechsler, J. Weller, R. D. Wilkinson
We describe the Dark Energy Survey (DES) photometric data set assembled from the first three years of science operations to support DES Year 3 cosmology analyses, and provide usage notes aimed at the broad astrophysics community. Y3 Gold improves on previous releases from DES, Y1 Gold and Data Release 1 (DES DR1), presenting an expanded and curated data set that incorporates algorithmic developments in image detrending and processing, photometric calibration, and object classification. Y3 Gold comprises nearly 5000 square degrees of grizY imaging in the south Galactic cap, including nearly 390 million objects, with depth reaching S/N ~ 10 for extended objects up to $i_{AB}\sim 23.0$, and top-of-the-atmosphere photometric uniformity $< 3$ mmag. Compared to DR1, photometric residuals with respect to Gaia are reduced by $50\%$, and per-object chromatic corrections are introduced. Y3 Gold augments DES DR1 with simultaneous fits to multi-epoch photometry for more robust galaxy color measurements and corresponding photometric redshift estimates. Y3 Gold features improved morphological star-galaxy classification with efficiency $>98\%$ and purity $>99\%$ for galaxies with $19 < i_{AB} < 22.5$. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used to select the cosmology analysis samples. This paper will be complemented by online resources.
Cosmology Requirements on Supernova Photometric Redshift Systematics for Rubin LSST and Roman Space Telescope
在即将到来的广域时域调查中，将发现和监测大约100万颗Ia型超新星（SN），如Vera C。Rubin Observatory Legacy Survey of Space and Time（鲁宾天文台时空遗产巡天）对于宇宙学的应用，除了其他特性外，还需要精确的红移;然而绝大多数SN不会有光谱红移，即使是对于它们的宿主星系，也只有光度红移。我们评估了红移系统控制必要的强大的宇宙学。基于由机器学习产生的光度与真实红移关系，应用于LSST质量观察到的50万个星系的模拟，我们量化了平均关系和异常值分数和偏差中的系统学要求，以便不偏向暗能量宇宙学推断。某些红移范围是特别敏感的，激发了SN在$z\lesssim0.2$和$z\approx0.5$-0.6附近的光谱跟踪。包括Nancy Grace Roman太空望远镜近红外波段的模拟中，我们重新分析的约束，发现在高红移的改善，但很少在低红移的系统学导致强烈的宇宙学偏见。我们确定了一个完整的光谱调查SN主机星系$z\lesssim0.2$作为一个非常有利的元素强大的SN宇宙学。
Machine Learning Closure Audits for LSST Photometric Supernova Cosmology
Center for AstroPhysical Surveys, National Center for Supercomputing Applications（国家超级计算应用中心天体物理调查中心）；Department of Astronomy, University of Illinois at Urbana Champaign（伊利诺伊大学厄巴纳-香槟分校天文系）
A Fully Photometric Approach to Type Ia Supernova Cosmology in the LSST Era: Host Galaxy Redshifts and Supernova Classification
National Center for Supercomputing Applications（国家超级计算应用中心）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of Chicago（芝加哥大学）；Stanford University（斯坦福大学）；SLAC National Accelerator Laboratory（SLAC国家加速器实验室）；Massachusetts Institute of Technology（麻省理工学院）；Center for Astrophysics | Harvard & Smithsonian（天体物理中心|哈佛与史密森尼学会）；The Inter-University Centre for Astronomy and Astrophysics (IUCAA)（大学间天文学和天体物理学中心）
Comment on "Is Dark Matter with Long-Range Interactions a Solution to All Small-Scale Problems of ΛCDM Cosmology?"
In Phys. Rev. Lett. 109（2012）231301，van den Aarssen等人试图通过引入暗物质粒子和MeV质量矢量玻色子之间的相互作用来解决冷暗物质场景中的所有小尺度结构问题。此外，后者与普通中微子耦合，为此需要中微子-矢量玻色子耦合常数10^{-5} < g_nu < 0.1。我们表明，这种暗物质的情况下，受到大爆炸核合成的限制性约束。
