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Non-Gaussianity from $X, Y$ gauge bosons in Cosmological Collider Physics

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arxiv 2101.10634 v1 pith:5M4GMTC6 submitted 2021-01-26 hep-ph astro-ph.COgr-qchep-th

Nobuhito Maru , Akira Okawa This is my paper · ORCID
classification hep-phastro-ph.COgr-qchep-th
keywords gaugescalebosonscolliderhubblebosoncosmologicaldetactability
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abstract

Heavy fields of Hubble scale order present during inflation contribute to the non-Gaussian signature for the three-point function of the inflaton. Taking into account that Hubble scale is around the scale of grand unified theory (GUT), this opens a possibility that the GUT scale signatures, which are very hard to be discovered at collider, might be detectable by using information from the precise observations of cosmic microwave background. We discuss a detactability of the $X, Y$ gauge boson present in any GUT in a framework of cosmological collider physics. Calculating one-loop contributions of $X, Y$ gauge bosons to the inflaton three-point functions, we find a remarkable result that one-loop diagram with interactions originated from the mass terms of $X, Y$ gauge bosons provides an enhancement factor expressed by the ratio between the $X, Y$ gauge boson mass and Hubble scale as $(m_X/H)^4$. In an estimation of the non-Gaussianity, this factor is crucial and its impact on the detactability of $X, Y$ gauge bosons is discussed.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Massive Inflationary Amplitudes: Differential Equations and Complete Solutions for General Trees

    hep-th 2024-12 conditional novelty 7.0 of 10

    Every tree-level massive inflation correlator in the signal region can be written as one massive family tree series plus its cuts, with 2I summation variables.

  2. Cosmological Correlators at the Loop Level

    hep-th 2024-11 conditional novelty 6.0 of 10

    Using the partial Mellin-Barnes method, the author derives analytic signals from one-loop bubble diagrams in inflation correlators, including the first analytic results for a de Sitter boost-breaking bubble.

  3. Efficient training of photonic quantum generative models

    quant-ph 2026-03 unverdicted novelty 5.0 of 10

    Photonic quantum generative models can be trained classically via maximum mean discrepancy, with deployment corresponding to boson sampling.

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