Letter

Differential neutrino condensation onto cosmic structure

  • Nature Astronomy 1, Article number: 0143 (2017)
  • doi:10.1038/s41550-017-0143
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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.

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References

  1. 1.

    , , , & Detection of the free neutrino: a confirmation. Science 124, 103–104 (1956).

  2. 2.

    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.

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

  4. 4.

    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.

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

  6. 6.

    & 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.

    et al. Euclid Definition Study Report. Preprint at (2011).

  9. 9.

    LSST Science Collaboration et al. LSST Science Book, Version 2.0. Preprint at (2009).

  10. 10.

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

  11. 11.

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

  12. 12.

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

  13. 13.

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

  14. 14.

    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.

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

  16. 16.

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

  17. 17.

    , , , & DEMNUni: the clustering of large-scale structures in the presence of massive neutrinos. J. Cosmol. Astropart. Phys. 7, 043 (2015).

  18. 18.

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

  19. 19.

    , , & Neutrinos in non-linear structure formation — the effect on halo properties. J. Cosmology Astropart. Phys. 9, 014 (2010).

  20. 20.

    , , , & Cosmology with massive neutrinos II: on the universality of the halo mass function and bias. J. Cosmol. Astropart. Phys. 2, 049 (2014).

  21. 21.

    , , & Non-linear evolution of the cosmic neutrino background. J. Cosmol. Astropart. Phys. 3, 019 (2013).

  22. 22.

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

  23. 23.

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

  24. 24.

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

  25. 25.

    , , & 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.

    , , , & Halo abundance matching: accuracy and conditions for numerical convergence. Mon. Not. R. Astron. Soc. 447, 3693–3707 (2015).

  27. 27.

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

  28. 28.

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

  29. 29.

    et al. BINGO: a single dish approach to 21 cm intensity mapping. Preprint at (2012).

  30. 30.

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

  31. 31.

    , & Super-sample covariance in simulations. Phys. Rev. D 89, 083519 (2014).

  32. 32.

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

  33. 33.

    & 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

Affiliations

  1. Department of Astronomy, Beijing Normal University, Beijing 100875, China.

    • Hao-Ran Yu
    • , Tong-Jie Zhang
    •  & Huan-Yu Teng
  2. Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, China.

    • Hao-Ran Yu
  3. Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, M5S 3H8 Ontario, Canada.

    • Hao-Ran Yu
    • , J.D. Emberson
    • , Derek Inman
    •  & Ue-Li Pen
  4. Department of Astronomy and Astrophysics, University of Toronto, Toronto, Ontario M5S 3H4, Canada.

    • J.D. Emberson
  5. Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada.

    • Derek Inman
  6. Shandong Provincial Key Laboratory of Biophysics, School of Physics and Electric Information, Dezhou University, Dezhou 253023, China.

    • Tong-Jie Zhang
  7. Dunlap Institute for Astronomy and Astrophysics, University of Toronto, Toronto, Ontario M5S 3H4, Canada.

    • Ue-Li Pen
  8. Canadian Institute for Advanced Research, Program in Cosmology and Gravitation, Ontario, M5G 1Z8, Canada.

    • Ue-Li Pen
  9. Perimeter Institute for Theoretical Physics, Waterloo, Ontario, N2L 2Y5, Canada.

    • Ue-Li Pen
  10. Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada.

    • Joachim Harnois-Déraps
  11. Scottish University Physics Alliance, Institute for Astronomy, University of Edinburgh, EH9 3HJ, UK.

    • Joachim Harnois-Déraps
  12. Department of Astronomy, Peking University, Beijing 100871, China.

    • Shuo Yuan
  13. Key Laboratory for Computational Astrophysics, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China.

    • Hong-Ming Zhu
    •  & Xuelei Chen
  14. School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.

    • Zhi-Zhong Xing
  15. Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China.

    • Zhi-Zhong Xing
  16. School of Computer, National University of Defense Technology, Changsha 410073, China.

    • Yunfei Du
    • , Yutong Lu
    •  & XiangKe Liao
  17. National Supercomputer Center in Guangzhou, Sun Yat-Sen University, Guangzhou 510006, China.

    • Yunfei Du
    •  & Yutong Lu
  18. Institute of Ocean Science and Technology, National University of Defense Technology, Changsha 410073, China.

    • Lilun Zhang

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Contributions

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.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Tong-Jie Zhang.

Supplementary information

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  1. 1.

    Supplementary Information

    Supplementary Figures 1–2.