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Implementing MaVaNs Cosmology

Implementing MaVaNs Cosmology. Akshay ghalsasi , ann nelson PHENO 2014 University of Washington. Ma ss Va rying N eutrinos – Introduction and Motivation. The MaVaNs model was originally proposed as a candidate for dark energy.

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Implementing MaVaNs Cosmology

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  1. Implementing MaVaNs Cosmology Akshay ghalsasi, ann nelson PHENO 2014 University of Washington

  2. Mass Varying Neutrinos – Introduction and Motivation • The MaVaNs model was originally proposed as a candidate for dark energy. • In this model the SM neutrinos couple to a scalar field the ‘acceleron’ via a sterile neutrino, the result being that this neutrino-acceleron fluid acts with negative pressure giving rise to dark energy. • Another result of this coupling is that the mass of the neutrinos now depends on their number density, and the neutrinos get heavier as the universe expands. When non-relativistic the mass of the neutrino goes as mν ~ a-3ω and mν ~ a-(3ω+1)/2 when relativistic.

  3. Mass Varying Neutrinos – Introduction and Motivation • MaVaNs allow for a much higher Σmν at late times. • This results in late forming warm dark matter which can erase structure on small scales. • Planck has a discrepancy in their measurements of σ8. • Simple fixes like increasing the mass of neutrinos don’t work. • This motivated us to study MaVaNs as a possible candidate to resolve this discrepancy. • In this study we will explore the effects of mass varying neutrinos on the CMB spectrum and compare it to the spectrum obtained from the standard ΛCDM model.

  4. Implementation - CMBEASY • Standard ΛCDM cosmology has 6 parameters other than neutrino mass, Ωmh2, Ωbh2, h, As, ns,τ. • We characterize MaVaNs with two additional parameters Σmν (the mass of the neutrinos today) and ω. • If ω < -1 then we have quintessence, which also can be implemented in CMBEASY, (although there is a caveat). • CMBEASY takes these parameters as input and spits out a CMB spectrum. We can then use Planck Likelihood calculator to find the best fit values and error bars on the cosmological parameters.

  5. Implementation

  6. Analysis

  7. Analysis • The late time ISW effect results into a rise in the CMB spectrum for low multipoles and is caused due to decaying gravitational potentials in presence of dark energy. • In MaVaNs case we have dark energy along with massive neutrinos that act as warm dark matter at late times, leading to further decaying of the gravitational potentials enhancing the ISW effect. • However we cannot use the ISW effect to constrain neutrino masses we used in the study since the cosmic variance is also correspondingly larger. • If we include the low l modes in our Likelihood calculations then we will be able to constrain very heavy neutrinos but that has been left for future studies. ISW effect

  8. Analysis – Planck σ8 discrepancy • σ8 can be thought of as a measure of rms fluctuation of matter density in the universe and gives us a measure of the amount of structure in the universe. • Assuming ΛCDM cosmology Planck obtained the best fit value of σ8to be σ8= 0.834 ± 0.027 however using SZ cluster counts they get σ8 = 0.77 ± 0.02 which is a discrepancy • Using MaVaNs we can reduce this tension without increasing the tension in the H0.

  9. Results

  10. Conclusions • MaVaNs cosmology is consistent with Planck data. • Including lower multipoles in our likelihood will allow us to constrain the very heavy neutrino masses in MaVaNs. • MaVaNs help reduce the Planck σ8 discrepancy without increasing the tension in H0. • The calculation for σ8 has been done in the linear regime and one would need to do structure formation simulations to find the true effect of MaVaNs on structure. • QUESTIONS?

  11. Implementation- Quintessence

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