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arXiv 2601.07784astro-ph.CO
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欧几里得准备。在欧几里得旗舰模拟中测试星系固有对齐的分析模型

Euclid preparation. Testing analytic models of galaxy intrinsic alignments in the Euclid Flagship simulation

Université Paris-Saclay, Université Paris Cité(巴黎萨克雷大学、巴黎西岱大学);CEA(法国原子能和替代能源委员会);CNRS(法国国家科学研究中心);Centre National d’Etudes Spatiales – Centre spatial de Toulouse(法国国家空间研究中心图卢兹航天中心);University College London(伦敦大学学院);Institute of Space Sciences (ICE, CSIC)(空间科学研究所(CSIC));Institut d’Estudis Espacials de Catalunya (IEEC)(加泰罗尼亚空间研究学院);Institut de Recherche en Astrophysique et Planétologie (IRAP)(天体物理学与行星学研究所在);Leiden Observatory, Leiden University(莱顿大学莱顿天文台);Northeastern University(东北大学);University of Zurich(苏黎世大学);ESAC/ESA(欧洲空间应用中心/欧洲空间局)
Euclid Collaboration, R. Paviot, B. Joachimi, K. Hoffmann, S. Codis, I. Tutusaus, D. Navarro-Gironés, J. Blazek, F. Hervas-Peters, B. Altieri, S. Andreon, N. Au… 展开作者

Euclid Collaboration, R. Paviot, B. Joachimi, K. Hoffmann, S. Codis, I. Tutusaus, D. Navarro-Gironés, J. Blazek, F. Hervas-Peters, B. Altieri, S. Andreon, N. Auricchio, C. Baccigalupi, M. Baldi, S. Bardelli, A. Biviano, E. Branchini, M. Brescia, S. Camera, G. Cañas-Herrera, V. Capobianco, C. Carbone, V. F. Cardone, J. Carretero, S. Casas, F. J. Castander, M. Castellano, G. Castignani, S. Cavuoti, K. C. Chambers, A. Cimatti, C. Colodro-Conde, G. Congedo, L. Conversi, Y. Copin, F. Courbin, H. M. Courtois, A. Da Silva, H. Degaudenzi, S. de la Torre, G. De Lucia, H. Dole, F. Dubath, C. A. J. Duncan, X. Dupac, S. Dusini, S. Escoffier, M. Farina, R. Farinelli, S. Farrens, S. Ferriol, F. Finelli, P. Fosalba, M. Frailis, E. Franceschi, S. Galeotta, K. George, B. Gillis, C. Giocoli, J. Gracia-Carpio, A. Grazian, F. Grupp, S. V. H. Haugan, H. Hoekstra, W. Holmes, F. Hormuth, A. Hornstrup, K. Jahnke, M. Jhabvala, E. Keihänen, S. Kermiche, A. Kiessling, M. Kilbinger, B. Kubik, M. Kümmel, M. Kunz, H. Kurki-Suonio, A. M. C. Le Brun, S. Ligori, P. B. Lilje, V. Lindholm, I. Lloro, G. Mainetti, D. Maino, E. Maiorano, O. Mansutti, S. Marcin, O. Marggraf, M. Martinelli, N. Martinet, F. Marulli, R. J. Massey, S. Maurogordato, E. Medinaceli, S. Mei, Y. Mellier, M. Meneghetti, E. Merlin, G. Meylan, A. Mora, M. Moresco, L. Moscardini, C. Neissner, S. -M. Niemi, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, V. Pettorino, S. Pires, G. Polenta, M. Poncet, L. A. Popa, L. Pozzetti, F. Raison, R. Rebolo, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, R. Saglia, Z. Sakr, A. G. Sánchez, D. Sapone, B. Sartoris, P. Schneider, T. Schrabback, A. Secroun, E. Sefusatti, G. Seidel, S. Serrano, P. Simon, C. Sirignano, G. Sirri, A. Spurio Mancini, L. Stanco, J. Steinwagner, P. Tallada-Crespí, A. N. Taylor, I. Tereno, N. Tessore, S. Toft, R. Toledo-Moreo, F. Torradeflot, L. Valenziano, J. Valiviita, T. Vassallo, G. Verdoes Kleijn, A. Veropalumbo, Y. Wang, J. Weller, A. Zacchei, G. Zamorani, F. M. Zerbi, E. Zucca, E. Bozzo, C. Burigana, R. Cabanac, M. Calabrese, J. A. Escartin Vigo, L. Gabarra, W. G. Hartley, S. Matthew, M. Maturi, N. Mauri, R. B. Metcalf, A. Pezzotta, M. Pöntinen, C. Porciani, I. Risso, V. Scottez, M. Sereno, M. Tenti, M. Viel, M. Wiesmann, Y. Akrami, I. T. Andika, S. Anselmi, M. Archidiacono, F. Atrio-Barandela, D. Bertacca, M. Bethermin, A. Blanchard, L. Blot, H. Böhringer, M. Bonici, S. Borgani, M. L. Brown, S. Bruton, A. Calabro, B. Camacho Quevedo, F. Caro, C. S. Carvalho, T. Castro, F. Cogato, S. Conseil, A. R. Cooray, O. Cucciati, S. Davini, F. De Paolis, G. Desprez, A. Díaz-Sánchez, J. J. Diaz, S. Di Domizio, J. M. Diego, P. Dimauro, M. Y. Elkhashab, A. Enia, Y. Fang, A. G. Ferrari, A. Finoguenov, A. Fontana, A. Franco, K. Ganga, J. García-Bellido, T. Gasparetto, V. Gautard, R. Gavazzi, E. Gaztanaga, F. Giacomini, F. Gianotti, G. Gozaliasl, M. Guidi, C. M. Gutierrez, A. Hall, S. Hemmati, H. Hildebrandt, J. Hjorth, S. Joudaki, J. J. E. Kajava, Y. Kang, V. Kansal, D. Karagiannis, K. Kiiveri, J. Kim, C. C. Kirkpatrick, S. Kruk, J. Le Graet, L. Legrand, M. Lembo, F. Lepori, G. Leroy, G. F. Lesci, J. Lesgourgues, T. I. Liaudat, A. Loureiro, J. Macias-Perez, G. Maggio, M. Magliocchetti, F. Mannucci, R. Maoli, C. J. A. P. Martins, L. Maurin, M. Miluzio, P. Monaco, C. Moretti, G. Morgante, S. Nadathur, K. Naidoo, P. Natoli, A. Navarro-Alsina, S. Nesseris, L. Pagano, D. Paoletti, F. Passalacqua, K. Paterson, L. Patrizii, A. Pisani, D. Potter, S. Quai, M. Radovich, S. Sacquegna, M. Sahlén, D. B. Sanders, E. Sarpa, A. Schneider, M. Schultheis, D. Sciotti, E. Sellentin, L. C. Smith, J. G. Sorce, K. Tanidis, C. Tao, G. Testera, R. Teyssier, S. Tosi, A. Troja, M. Tucci, C. Valieri, A. Venhola, D. Vergani, F. Vernizzi, G. Verza, P. Vielzeuf, N. A. Walton

AI总结:

本文通过欧几里得旗舰模拟测试星系固有对齐模型,发现NLA和TATT模型在低尺度下表现良好,但红移幂律无法准确描述高红移下的对齐信号,引入光度依赖性可显著提高一致性。

摘要:

我们对欧几里得旗舰模拟中的固有对齐(IA)进行建模,以研究其对欧几里得弱透镜信号的影响。我们的旗舰模拟中的IA实现考虑了星系的光度特性以及它们的暗物质宿主晕。我们将模拟与理论预测进行比较,确定了两种最广泛使用的IA模型的参数:非线性对齐(NLA)模型和潮汐对齐和潮汐扭力(TATT)模型。我们测量了模拟IA信号的振幅,作为红移范围0.1 < z < 2.1内星系亮度和颜色的函数。我们发现,NLA和TATT模型在6-7 h⁻¹ Mpc的尺度下能够准确描述模拟中的IA信号。我们测量了红星系的对齐振幅,与观测结果相当,这些样本未用于校准过程。对于蓝星系,我们的约束与我们在第一个红移区间0.1 < z < 0.3中的零对齐一致,但我们在更高的红移处检测到一个非可忽略的信号,但与观测限制设定的上限一致。此外,几种流体动力学模拟预测螺旋星系的对齐,与我们的发现一致。最后,对齐随红移的变化是真实的,并与观测确定的对齐一致。然而,我们发现通常采用的IA红移幂律无法在z>1.1时重现模拟的对齐。当加入光度依赖性时,得到显著更好的一致,捕捉到在亮度限制调查中红移的固有光度变化。我们得出结论,旗舰IA模拟是将当前IA约束转化为IA污染预测的有用工具。

英文摘要:

We model intrinsic alignments (IA) in Euclid's Flagship simulation to investigate its impact on Euclid's weak lensing signal. Our IA implementation in the Flagship simulation takes into account photometric properties of galaxies as well as their dark matter host halos. We compare simulations against theory predictions, determining the parameters of two of the most widely used IA models: the Non Linear Alignment (NLA) and the Tidal Alignment and Tidal Torquing (TATT) models. We measure the amplitude of the simulated IA signal as a function of galaxy magnitude and colour in the redshift range $0.1<z<2.1$. We find that both NLA and TATT can accurately describe the IA signal in the simulation down to scales of $6$-$7 \,h^{-1}\,$Mpc. We measure alignment amplitudes for red galaxies comparable to those of the observations, with samples not used in the calibration procedure. For blue galaxies, our constraints are consistent with zero alignments in our first redshift bin $0.1 < z < 0.3$, but we detect a non-negligible signal at higher redshift, which is, however, consistent with the upper limits set by observational constraints. Additionally, several hydrodynamical simulations predict alignment for spiral galaxies, in agreement with our findings. Finally, the evolution of alignment with redshift is realistic and comparable to that determined in the observations. However, we find that the commonly adopted redshift power-law for IA fails to reproduce the simulation alignments above $z=1.1$. A significantly better agreement is obtained when a luminosity dependence is included, capturing the intrinsic luminosity evolution with redshift in magnitude-limited surveys. We conclude that the Flagship IA simulation is a useful tool for translating current IA constraints into predictions for IA contamination of Euclid-like samples.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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