44 citations · 47 across the 8 of their papers we have counts for
8 papers
Gibbs measures for the repulsive Bose gas
Tianyi Bai, Quirin Vogel
We prove the existence of Gibbs measures for the Feynman representation of the Bose gas with non-negative interaction in the grand-canonical ensemble. Our results are valid for all…
Compressible Velocity Transformations for Various Noncanonical Wall-Bounded Turbulent Flows
Tianyi Bai, Kevin P. Griffin, Lin Fu
This work assesses several popular transformations for the velocity profile through their application to several types of non-canonical compressible wall-bounded turbulent flows. S…
Convergence in law for the capacity of the range of a critical branching random walk
Tianyi Bai, Yueyun Hu
Let be the range of a critical branching random walk with particles on , which is the set of sites visited by a random walk indexed by a critical Galton--Wat…
On the crossing estimates for simple conformal loop ensembles
Tianyi Bai, Yijun Wan
We prove the super-exponential decay of probabilities that there exist crossings of a given quadrilateral in a simple , , as goes to in…
Capacity of the range of branching random walks in low dimensions
Tianyi Bai, Yueyun Hu
Consider a branching random walk in with the genealogy tree formed by a sequence of i.i.d. critical Galton-Watson t…
Branching random walks conditioned on rarely survival
Tianyi Bai, Pierre Rousselin
In this paper, we show that a Galton-Watson tree conditioned to have a fixed number of particles in generation converges in distribution as , and with this…
Capacity of the range of tree-indexed random walk
Tianyi Bai, Yijun Wan
By introducing a new measure for the infinite Galton-Watson process and providing estimates for (discrete) Green's functions on trees, we establish the asymptotic behavior of the c…
On the cover time of λ-biased walk on supercritical Galton-Watson trees
Tianyi Bai
In this paper, we study the time required for a λ-biased (λ>1) walk to visit all the vertices of a supercritical Galton-Watson tree up to generation n. Inspired by the extremal lan…