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A note on loop resummation in de Sitter spacetime with the wavefunction of the universe approach

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arxiv 2412.01891 v2 pith:64TXSTGY submitted 2024-12-02 hep-th astro-ph.COhep-ph

classification hep-thastro-ph.COhep-ph
keywords firstfunctionsloopwavefunctioncorrelationpointpotentialstage
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We analyze the computation of $n$-point correlation functions in de Sitter spacetime, including loop corrections, using the wavefunction of the universe approach. This method consists of two stages employing distinct Feynman rules. First, one must compute the wavefunction coefficients using interactions as vertices. Then, in the second stage, one computes correlation functions using wavefunction coefficients as vertices. For massless fields, loop corrections in the first stage are free of infrared (IR) divergences, which leads to the question of how this matches the well-known IR behavior of correlators obtained via other methods. By considering a scalar field with an arbitrary potential, we compute $n$-point correlation functions to first order in the potential but to all orders in loops. We find that, although loop integrals in the first stage are indeed IR convergent, the second procedure reintroduces the IR divergence. We discuss how this induces renormalization of the interaction potential such that the final result combining both steps exactly matches the form of $n$-point functions previously calculated with other methods.

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Cited by 2 Pith papers

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

  1. Confronting infrared divergences in de Sitter: loops, logarithms and the stochastic formalism

    hep-th 2025-07 conditional novelty 7.0 of 10

    The authors show that loop corrections do not alter tree-level time dependence in de Sitter correlators, so secular growth is a regularization artifact, not a physical effect.

  2. 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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