ArXiv TLDR

Sampling the Graviton Pole and Deprojecting the Swampland

🐦 Tweet
2604.15235

Guangzhuo Peng, Laurentiu Rodina, Anna Tokareva, Yongjun Xu

hep-th

TLDR

A new primal bootstrap framework for EFTs with a graviton pole yields stronger bounds and shows EFT cutoff cannot exceed Planck scale.

Key contributions

  • Introduces a primal bootstrap framework for EFTs with a graviton pole using finite-resolution sampling.
  • Reproduces known projective bounds and yields slightly stronger bounds in D=5.
  • Derives new non-projective bounds, fixing the overall scale of EFT couplings.
  • Shows EFT cutoff cannot be parametrically larger than the Planck scale (e.g., M/Mp ≤ 7.8 in D=5).

Why it matters

This paper introduces a powerful new method for analyzing effective field theories, particularly those involving gravity. It establishes crucial non-projective bounds, demonstrating that the EFT cutoff cannot significantly exceed the Planck scale. This has important implications for understanding the validity and scope of EFTs in high-energy physics.

Original Abstract

We develop a primal bootstrap framework for effective field theories in the presence of a graviton pole, based on finite-resolution sampling rather than smearing, while also allowing direct control over the number of subtractions. We show that this approach reproduces the known projective bounds obtained from smearing in $D{\ge}6$, while yielding slightly stronger bounds in $D{=}5$. This method also makes it straightforward to impose linearized unitarity directly and provides an access to the extremal spectra. Applying the method to crossing-symmetric dispersion relations, we derive new non-projective bounds that fix the overall scale of the EFT couplings. In $D{=}5$, for example, we find that $\frac{M}{M_{\rm P}}{\lesssim}7.8$, showing that the EFT cutoff cannot be taken parametrically larger than the Planck scale. At the extremal values of the couplings, the spectra exhibit a surprising structure: for projective bounds, they exhibit peaks around quadratic Regge-like trajectories, while for the non-projective bounds they form sharp quadratic bands. In the latter case, the leading coefficients further display an inverse-quadratic dependence on the band number.

📬 Weekly AI Paper Digest

Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.