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researcher

Dejun Luo

54 papers hereh-index 191.2k citations94 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author12
  • first author7
  • middle author8
  • last author27

Across the 54 of 54 papers where every author was matched, so the position is known.

fields
  • math.PR47
  • math.AP2
  • math.DG2
  • math-ph2
  • math.CA1
same name
  • Dejun Luo — 4 papers, h 2
  • Dejun Luo — 3 papers, h 1
  • Dejun Luo — 3 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20102025
most citedHigh mode transport noise improves vorticity blow-up control in 3D Navier-Stokes equations

78 citations · 372 across the 53 of their papers we have counts for

collaborators
Showing 2022 · math.PRShow all

4 papers · 2 filters

math.PR2022

Stochastic inviscid Leray-α model with transport noise: convergence rates and CLT

Dejun Luo, Bin Tang

We consider the stochastic inviscid Leray-α model on the torus driven by transport noise. Under a suitable scaling of the noise, we prove that the weak solutions converge, in som…

math.PR2022★ 7 cited

Well posedness and limit theorems for a class of stochastic dyadic models

Dejun Luo, Danli Wang

We consider stochastic inviscid dyadic models with energy-preserving noise. It is shown that the models admit weak solutions which are unique in law. Under a certain scaling limit…

math.PR2022★ 3 cited

Dissipation enhancement by transport noise for stochastic p-Laplace equations

Zhao Dong, Dejun Luo, Bin Tang

The stochastic p-Laplace equation with multiplicative transport noise is studied on the torus Td(d≥2). It is shown that the dissipation is enhanced by transport…

math.PR2022★ 14 cited

LDP and CLT for SPDEs with Transport Noise

Lucio Galeati, Dejun Luo

In this work we consider solutions to stochastic partial differential equations with transport noise, which are known to converge, in a suitable scaling limit, to solution of the c…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.