Differential neutrino condensation onto cosmic structure

Article metrics

Abstract

Astrophysical techniques have pioneered the discovery of neutrino mass properties. Currently, the known neutrino effects on the large-scale structure of the Universe are all global, and neutrino masses are constrained by attempting to disentangle the small neutrino contribution from the sum of all matter using precise theoretical models. We investigate an alternative approach: to detect the difference between the neutrinos and that of dark matter and baryons. Here, by using one of the largest N-body simulations yet, we discover the differential neutrino condensation effect: in regions of the Universe with different neutrino relative abundance (the local ratio of neutrino to cold dark matter density), halo properties are different and neutrino mass can be inferred. In ‘neutrino-rich’ regions, more neutrinos can be captured by massive halos compared with ‘neutrino-poor’ regions. This effect differentially skews the halo mass function and opens up the path to independent measurements of neutrino mass in current or future galaxy surveys.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: TianNu simulation.
Figure 2: Distribution of dark-matter halos as a function of environmental variables δ ˆ c and δ ˆ ν .
Figure 3: Relative variation in halo mass and rank caused by differential neutrino condensation.
Figure 4: Differential modulation in halo rank caused by neutrino condensation.

References

  1. 1

    Cowan, C. L. Jr, Reines, F., Harrison, F. B., Kruse, H. W. & McGuire, A. D. Detection of the free neutrino: a confirmation. Science 124, 103–104 (1956).

  2. 2

    Danby, G. et al. Observation of high-energy neutrino reactions and the existence of two kinds of neutrinos. Phys. Rev. Lett. 9, 36–44 (1962).

  3. 3

    Fukuda, Y. et al. Evidence for oscillation of atmospheric neutrinos. Phys. Rev. Lett. 81, 1562–1567 (1998).

  4. 4

    Ahmad, Q. R. et al. Direct evidence for neutrino flavor transformation from neutral-current interactions in the Sudbury Neutrino Observatory. Phys. Rev. Lett. 89, 011301 (2002).

  5. 5

    Ahmad, Q. R. et al. Measurement of the rate of v e+d → p+p+e interactions produced by 8b solar neutrinos at the Sudbury Neutrino Observatory. Phys. Rev. Lett. 87, 071301 (2001).

  6. 6

    Olive, K. A. & Particle Data Group. Review of particle physics. Chin. Phys. C 38 , 090001 ( 2014).

  7. 7

    Planck Collaboration et al. Planck 2015 results. XIII. Cosmological parameters. Astron. Astrophys. 594, A13 (2016).

  8. 8

    Laureijs, R. et al. Euclid Definition Study Report. Preprint at http://arxiv.org/abs/1110.3193 (2011).

  9. 9

    LSST Science Collaboration et al. LSST Science Book, Version 2.0. Preprint at http://arxiv.org/abs/0912.0201 (2009).

  10. 10

    Dawson, K. S. et al. The SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: overview and early data. Astron. J. 151, 44 (2016).

  11. 11

    Goullioud, R. et al. Wide field infrared survey telescope [WFIRST]: telescope design and simulated performance. Proc. SPIE 8442, 84421U (2012).

  12. 12

    Eisenstein, D. & DESI Collaboration. in American Astronomical Society Meeting Abstracts, vol. 225 of American Astronomical Society Meeting Abstracts, 336.05 (2015).

  13. 13

    Abazajian, K. N. et al. Neutrino physics from the cosmic microwave background and large scale structure. Astropart. Phys. 63, 66–80 (2015).

  14. 14

    Mead, A. J. et al. Accurate halo-model matter power spectra with dark energy, massive neutrinos and modified gravitational forces. Mon. Not. R. Astron. Soc. 459, 1468–1488 (2016).

  15. 15

    Ichiki, K. & Takada, M. Impact of massive neutrinos on the abundance of massive clusters. Phys. Rev. D 85, 063521 (2012).

  16. 16

    LoVerde, M. Spherical collapse in vΛCDM. Phys. Rev. D 90, 083518 (2014).

  17. 17

    Castorina, E., Carbone, C., Bel, J., Sefusatti, E. & Dolag, K. DEMNUni: the clustering of large-scale structures in the presence of massive neutrinos. J. Cosmol. Astropart. Phys. 7, 043 (2015).

  18. 18

    Carbone, C., Petkova, M. & Dolag, K. DEMNUni: ISW, Rees–Sciama, and weak-lensing in the presence of massive neutrinos. J. Cosmol. Astropart. Phys. 7, 034 (2016).

  19. 19

    Brandbyge, J., Hannestad, S., Haugbølle, T. & Wong, Y. Y. Y. Neutrinos in non-linear structure formation — the effect on halo properties. J. Cosmology Astropart. Phys. 9, 014 (2010).

  20. 20

    Castorina, E., Sefusatti, E., Sheth, R. K., Villaescusa-Navarro, F. & Viel, M. Cosmology with massive neutrinos II: on the universality of the halo mass function and bias. J. Cosmol. Astropart. Phys. 2, 049 (2014).

  21. 21

    Villaescusa-Navarro, F., Bird, S., Peña-Garay, C. & Viel, M. Non-linear evolution of the cosmic neutrino background. J. Cosmol. Astropart. Phys. 3, 019 (2013).

  22. 22

    Harnois-Déraps, J. et al. High-performance P3M N-body code: CUBEP3M. Mon. Not. R. Astron. Soc. 436, 540–559 (2013).

  23. 23

    Inman, D. et al. Precision reconstruction of the cold dark matter–neutrino relative velocity from N-body simulations. Phys. Rev. D 92, 023502 (2015).

  24. 24

    Blas, D., Lesgourgues, J. & Tram, T. The Cosmic Linear Anisotropy Solving System (CLASS). Part II: Approximation schemes. J. Cosmology Astropart. Phys. 7, 034 (2011).

  25. 25

    Trujillo-Gomez, S., Klypin, A., Primack, J. & Romanowsky, A. J. Galaxies in ΛCDM with halo abundance matching: luminosity-velocity relation, baryonic mass–velocity relation, velocity function, and clustering. Astrophys. J. 742, 16 (2011).

  26. 26

    Klypin, A., Prada, F., Yepes, G., Heß, S. & Gottlöber, S. Halo abundance matching: accuracy and conditions for numerical convergence. Mon. Not. R. Astron. Soc. 447, 3693–3707 (2015).

  27. 27

    Berlind, A. A. & Weinberg, D. H. The halo occupation distribution: toward an empirical determination of the relation between galaxies and mass. Astrophys. J. 575, 587–616 (2002).

  28. 28

    Zheng, Z. et al. Theoretical models of the halo occupation distribution: separating central and satellite galaxies. Astrophys. J. 633, 791–809 (2005).

  29. 29

    Battye, R. A. et al. BINGO: a single dish approach to 21 cm intensity mapping. Preprint at https://arxiv.org/abs/1209.1041 (2012).

  30. 30

    Schlegel, D. J. et al. SDSS-III: The Baryon Oscillation Spectroscopic Survey (BOSS). Bull. Am. Astron. Soc. 39, 966 (2007).

  31. 31

    Li, Y., Hu, W. & Takada, M. Super-sample covariance in simulations. Phys. Rev. D 89, 083519 (2014).

  32. 32

    Pekurovsky. D. P3DFFT: a framework for parallel computations of Fourier transforms in three dimensions. SIAM J. Sci. Comput. 2012. 34 C192–C209 (2014).

  33. 33

    Peacock, J. A. & Smith, R. E. HALOFIT: Nonlinear distribution of cosmological mass and galaxies. Astrophysics Source Code Library. record ascl:1402.032 (2014).

Download references

Acknowledgements

H.-R.Y. thanks E. Komatsu for discussions and crucial remarks. The TianNu and TianZero simulations were performed on the Tianhe-2 supercomputer at the National Super Computing Centre in Guangzhou and the analyses were performed on the GPC and BGQ supercomputer at the SciNet HPC Consortium. This work was supported by Fundamental Research Funds for the Central Universities, the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase), the National Science Foundation of China (Grant Nos 11573006, 11528306, 11135009 and 11633004), and the CAS Frontier Science Key Project No. QYZDJ-SSW-SLH017. H.-R.Y. acknowledges General Financial Grant No. 2015M570884 and Special Financial Grant No. 2016T90009 from the China Postdoctoral Science Foundation. H.R.Y., J.D.E., D.I. and J.H.-D. acknowledge the support of the NSERC. J.H.-D. also acknowledges the support from the European Commission under Marie-Skłodwoska-Curie European Fellowship (EU project 656869). We thank Y.-F. Wang of IHEP for his initial support for our project, and X.-F. Yuan for his support in the Tianhe-2 supercomputing centre.

Author information

H.-R.Y., J.D.E. and U.-L.P. performed the data analysis. D.I., J.H.-D. and T.-J.Z. also contributed to the interpretation of the results. J.H.-D., J.D.E. and U.-L.P. primarily developed the neutrino simulation code and H.-R.Y., S.Y., H.-Y.T. and T.-J.Z. performed the TianNu simulations on the Tianhe-2 supercomputer. J.D.E. contributed the graphics of the animation. H.-M.Z., X.C. and Z.-Z.X. contributed to the scientific discussions. L.Z., Y.D., Y.L. and X.L. contributed to the feasibility of application of the code on the Tianhe-2 supercomputer. T.-J.Z. and U.-L.P. proposed the idea and conceived the plan of the TianNu project.

Correspondence to Tong-Jie Zhang.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Figures 1–2. (PDF 367 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Further reading