@article{14775,
  abstract     = {We establish a quantitative version of the Tracy–Widom law for the largest eigenvalue of high-dimensional sample covariance matrices. To be precise, we show that the fluctuations of the largest eigenvalue of a sample covariance matrix X∗X converge to its Tracy–Widom limit at a rate nearly N−1/3, where X is an M×N random matrix whose entries are independent real or complex random variables, assuming that both M and N tend to infinity at a constant rate. This result improves the previous estimate N−2/9 obtained by Wang (2019). Our proof relies on a Green function comparison method (Adv. Math. 229 (2012) 1435–1515) using iterative cumulant expansions, the local laws for the Green function and asymptotic properties of the correlation kernel of the white Wishart ensemble.},
  author       = {Schnelli, Kevin and Xu, Yuanyuan},
  issn         = {1050-5164},
  journal      = {The Annals of Applied Probability},
  keywords     = {Statistics, Probability and Uncertainty, Statistics and Probability},
  number       = {1},
  pages        = {677--725},
  publisher    = {Institute of Mathematical Statistics},
  title        = {{Convergence rate to the Tracy–Widom laws for the largest eigenvalue of sample covariance matrices}},
  doi          = {10.1214/22-aap1826},
  volume       = {33},
  year         = {2023},
}

@article{12707,
  abstract     = {We establish precise right-tail small deviation estimates for the largest eigenvalue of real symmetric and complex Hermitian matrices whose entries are independent random variables with uniformly bounded moments. The proof relies on a Green function comparison along a continuous interpolating matrix flow for a long time. Less precise estimates are also obtained in the left tail.},
  author       = {Erdös, László and Xu, Yuanyuan},
  issn         = {1350-7265},
  journal      = {Bernoulli},
  number       = {2},
  pages        = {1063--1079},
  publisher    = {Bernoulli Society for Mathematical Statistics and Probability},
  title        = {{Small deviation estimates for the largest eigenvalue of Wigner matrices}},
  doi          = {10.3150/22-BEJ1490},
  volume       = {29},
  year         = {2023},
}

@article{11332,
  abstract     = {We show that the fluctuations of the largest eigenvalue of a real symmetric or complex Hermitian Wigner matrix of size N converge to the Tracy–Widom laws at a rate O(N^{-1/3+\omega }), as N tends to infinity. For Wigner matrices this improves the previous rate O(N^{-2/9+\omega }) obtained by Bourgade (J Eur Math Soc, 2021) for generalized Wigner matrices. Our result follows from a Green function comparison theorem, originally introduced by Erdős et al. (Adv Math 229(3):1435–1515, 2012) to prove edge universality, on a finer spectral parameter scale with improved error estimates. The proof relies on the continuous Green function flow induced by a matrix-valued Ornstein–Uhlenbeck process. Precise estimates on leading contributions from the third and fourth order moments of the matrix entries are obtained using iterative cumulant expansions and recursive comparisons for correlation functions, along with uniform convergence estimates for correlation kernels of the Gaussian invariant ensembles.},
  author       = {Schnelli, Kevin and Xu, Yuanyuan},
  issn         = {1432-0916},
  journal      = {Communications in Mathematical Physics},
  pages        = {839--907},
  publisher    = {Springer Nature},
  title        = {{Convergence rate to the Tracy–Widom laws for the largest Eigenvalue of Wigner matrices}},
  doi          = {10.1007/s00220-022-04377-y},
  volume       = {393},
  year         = {2022},
}

@article{12243,
  abstract     = {We consider the eigenvalues of a large dimensional real or complex Ginibre matrix in the region of the complex plane where their real parts reach their maximum value. This maximum follows the Gumbel distribution and that these extreme eigenvalues form a Poisson point process as the dimension asymptotically tends to infinity. In the complex case, these facts have already been established by Bender [Probab. Theory Relat. Fields 147, 241 (2010)] and in the real case by Akemann and Phillips [J. Stat. Phys. 155, 421 (2014)] even for the more general elliptic ensemble with a sophisticated saddle point analysis. The purpose of this article is to give a very short direct proof in the Ginibre case with an effective error term. Moreover, our estimates on the correlation kernel in this regime serve as a key input for accurately locating [Formula: see text] for any large matrix X with i.i.d. entries in the companion paper [G. Cipolloni et al., arXiv:2206.04448 (2022)]. },
  author       = {Cipolloni, Giorgio and Erdös, László and Schröder, Dominik J and Xu, Yuanyuan},
  issn         = {1089-7658},
  journal      = {Journal of Mathematical Physics},
  keywords     = {Mathematical Physics, Statistical and Nonlinear Physics},
  number       = {10},
  publisher    = {AIP Publishing},
  title        = {{Directional extremal statistics for Ginibre eigenvalues}},
  doi          = {10.1063/5.0104290},
  volume       = {63},
  year         = {2022},
}