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PreprintCC BY 4.0arXiv

Well-Posedness for SDEs with Logarithmical Critical Distributional Drifts

Abstract

We study the stochastic differential equation d Xt=b(t,Xt)d t+√2d Wt on ℝd, where b is a time-dependent, divergence-free distributional drift of critical Hölder--Besov regularity −1, strengthened by an iterated-logarithmic correction. For every initial probability law, we construct a weak solution by smooth approximation and realize the singular drift as an additive functional. The main analytic ingredient is the Schauder estimate with a logarithmic smallness factor. Combined with uniform logarithmic Krylov estimates and a stochastic substitution formula for distributional test functions, this estimate allows us to apply a Zvonkin transformation and prove uniqueness in law among weak solutions satisfying the corresponding Krylov bounds. For solutions starting from deterministic points, we further show that their time-marginal distributions admit densities satisfying two-sided Aronson-type Gaussian estimates.

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BibTeX
@misc{chen2026wellposedness,
  title = {{Well-Posedness for SDEs with Logarithmical Critical Distributional Drifts}},
  author = {Zikai Chen and Zimo Hao and Xicheng Zhang},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.02022},
  eprint = {2609.02022},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.02022},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Well-Posedness for SDEs with Logarithmical Critical Distributional Drifts
AU  - Zikai Chen
AU  - Zimo Hao
AU  - Xicheng Zhang
PY  - 2026
DA  - 2026/09/02
PB  - arXiv
DO  - 10.48550/arxiv.2609.02022
UR  - https://arxiv.org/abs/2609.02022
AB  - We study the stochastic differential equation d X_t=b(t,X_t)d t+√2d W_t on ℝ^d, where b is a time-dependent, divergence-free distributional drift of critical Hölder--Besov regularity −1, strengthened by an iterated-logarithmic correction. For every initial probability law, we construct a weak solution by smooth approximation and realize the singular drift as an additive functional. The main analytic ingredient is the Schauder estimate with a logarithmic smallness factor. Combined with uniform logarithmic Krylov estimates and a stochastic substitution formula for distributional test functions, this estimate allows us to apply a Zvonkin transformation and prove uniqueness in law among weak solutions satisfying the corresponding Krylov bounds. For solutions starting from deterministic points, we further show that their time-marginal distributions admit densities satisfying two-sided Aronson-type Gaussian estimates.
ER  -