PIRSA:13050054

Axiverse Cosmology and the Energy Scale of Inflation

APA

Marsh, D. (2013). Axiverse Cosmology and the Energy Scale of Inflation. Perimeter Institute. https://pirsa.org/13050054

MLA

Marsh, David. Axiverse Cosmology and the Energy Scale of Inflation. Perimeter Institute, May. 07, 2013, https://pirsa.org/13050054

BibTex

          @misc{ pirsa_PIRSA:13050054,
            doi = {10.48660/13050054},
            url = {https://pirsa.org/13050054},
            author = {Marsh, David},
            keywords = {Cosmology},
            language = {en},
            title = {Axiverse Cosmology and the Energy Scale of Inflation},
            publisher = {Perimeter Institute},
            year = {2013},
            month = {may},
            note = {PIRSA:13050054 see, \url{https://pirsa.org}}
          }
          

David Marsh

King's College London

Talk number
PIRSA:13050054
Talk Type
Subject
Abstract
Ultra-light axions (m_a<10^{-18} eV), motivated by string theory, can be a powerful probe of the energy scale of inflation if they exist as a sub-dominant component of the Dark Matter. In contrast to heavier axions the isocurvature modes in the ultra-light axions can coexist with observable gravitational waves. Here it is shown that existing (2005) large scale structure constraints severely limit the parameter space for axion mass, density fraction and isocurvature amplitude. It is also shown that radically different CMB observables for the ultra-light axion isocurvature mode additionally reduce this space. The results of a new, accurate and efficient method to calculate this isocurvature power spectrum are presented, and can be used to constrain ultra-light axions and inflation.
I will also present preliminary results of constraints to this model using up-to-date cosmological observations, which verify the above picture. The parameter space is interesting to explore due to a strongly mass dependent covariance matrix, motivating comparisons between Metropolis-Hastings and nested sampling. Finally I discuss fine-tuning and naturalness in these models.