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Modeling cosmic void statistics

  • Nico Hamaus (a1) (a2), P. M. Sutter (a1) (a2) (a3) and Benjamin D. Wandelt (a1) (a2) (a4)

Abstract

Understanding the internal structure and spatial distribution of cosmic voids is crucial when considering them as probes of cosmology. We present recent advances in modeling void density- and velocity-profiles in real space, as well as void two-point statistics in redshift space, by examining voids identified via the watershed transform in state-of-the-art ΛCDM n-body simulations and mock galaxy catalogs. The simple and universal characteristics that emerge from these statistics indicate the self-similarity of large-scale structure and suggest cosmic voids to be among the most pristine objects to consider for future studies on the nature of dark energy, dark matter and modified gravity.

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References

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Colberg, J. M., Sheth, R. K., Diaferio, A., Gao, L., & Yoshida, N. 2005, MNRAS, 360, 216
Hamaus, N., Wandelt, B. D., Sutter, et al. 2014, Phys. Rev. Lett., 112, 041304
Hamaus, N., Sutter, P. M., & Wandelt, B. D. 2014, Phys. Rev. Lett., 112, 251302
Hamaus, N., Sutter, P. M., Lavaux, G., & Wandelt, B. D. 2014, arXiv:1409.3580
Nadathur, S., Hotchkiss, S., Diego, J. M., et al. 2014, arXiv:1407.1295
Neyrinck, M. C. 2008, MNRAS, 386, 2101
Padilla, N. D., Ceccarelli, L., & Lambas, D. G. 2005, MNRAS, 363, 977
Paz, D., Lares, M., Ceccarelli, L., Padilla, N., & Lambas, D. G. 2013, MNRAS, 436, 3480
Ricciardelli, E., Quilis, V., & Varela, J. 2014, MNRAS, 440, 601
Sheth, R. K. & van de Weygaert, R. 2004, MNRAS, 350, 517
Sutter, P. M., Lavaux, G., Wandelt, B. D., & Weinberg, D. H. 2012 ApJ, 761, 187
Sutter, P. M., Lavaux, G., Hamaus, N., et al. 2014, MNRAS, 442, 462
Sutter, P. M., Lavaux, G., Hamaus, N., et al. 2014, arXiv:1406.1191
Warren, M. S. 2013, in Proceedings of SC '13 (ACM, New York, USA), 2HOT: An Improved Parallel Hashed Oct-tree N-body Algorithm for Cosmological Simulation, pp. 72:1–72:12
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Keywords

Modeling cosmic void statistics

  • Nico Hamaus (a1) (a2), P. M. Sutter (a1) (a2) (a3) and Benjamin D. Wandelt (a1) (a2) (a4)

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