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Critical Gaussian multiplicative chaos for singular measures

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  • Lacoin, Hubert

Abstract

Given d≥1, we provide a construction of the random measure – the critical Gaussian Multiplicative Chaos – formally defined as e2dXdμ where X is a log-correlated Gaussian field and μ is a locally finite measure on Rd. Our construction generalizes the one performed in the case where μ is the Lebesgue measure. It requires that the measure μ is sufficiently spread out, namely that for μ almost every x we have ∫B(x,1)μ(dy)|x−y|deρlog1|x−y|<∞, where ρ:R+→R+ can be chosen to be any lower envelope function for the 3-Bessel process (this includes ρ(x)=xα with α∈(0,1/2)). We prove that three distinct random objects converge to a common limit which defines the critical GMC: the derivative martingale, the critical martingale, and the exponential of the mollified field. We also show that the above criterion for the measure μ is in a sense optimal.

Suggested Citation

  • Lacoin, Hubert, 2024. "Critical Gaussian multiplicative chaos for singular measures," Stochastic Processes and their Applications, Elsevier, vol. 175(C).
  • Handle: RePEc:eee:spapps:v:175:y:2024:i:c:s0304414924000942
    DOI: 10.1016/j.spa.2024.104388
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