Search arXivSearch

arXiv · 1807.02833

Singular Value Statistics for the Spiked Elliptic Ginibre Ensemble

Abstract

The complex elliptic Ginibre ensemble with coupling $\tau$ is a complex Gaussian matrix interpolating between the Gaussian Unitary Ensemble (GUE) and the Ginibre ensemble. It has been known for some time that its eigenvalues form a determinantal point process in the complex plane. A recent result of Kanazawa and Kieburg (arXiv:1804.03985) shows that the singular values form a Pfaffian point process. In this paper we turn to consider an extended elliptic Ginibre ensemble, which connects the GUE and the spiked Wishart matrix, and prove that the singular values still build a Pfaffian point process with correlation kernels expressed by contour integral representations. As $\tau$ tends to 1 at a certain critical rate, we prove that the limiting distribution of the largest singular value is described as a new Fredholm Pfaffian series, which connects two distributions $F_{\mathrm{GUE}}$ and $F^{2}_{\mathrm{GUE}}$ where $F_{\mathrm{GUE}}$ is the GUE Tracy-Widom distribution. For fixed $\tau$, we prove the Baik-Ben Arous-P\'ech\'e transition of the largest singular value and the sine kernel in the bulk. We also observe a crossover phenomenon at the origin when $\tau$ tends to 1 at another critical rate.

Explore related subjects

Keep this discovery

BibTeXRIS

Dang-Zheng Liu, Yanhui Wang. 2018-07-08. Singular Value Statistics for the Spiked Elliptic Ginibre Ensemble. https://arxiv.org/abs/1807.02833

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection

In this paper, we study averaging principles for nonautonomous multiscale stochastic Burgers equations with reflection. First, we derive a general averaging principle applicable to such equations under minimal assumptions. Subsequently, since the coefficients of the obtained averaged equation still depend on the small scaling parameter $\e$, we impose either periodic or asymptotic conditions on the coefficients, thereby obtain two distinct averaged equations whose coefficients are independent of $\e$ and establish two averaging principles. Stopping times and Khasminskii's time discretization schemes play an important role. Finally, a concrete example is provided to illustrate the applicability and validity of the theoretical results.

math.PR

Spectral properties of Random Matrices

We give the theoretical foundations of random matrix theory through the definitions of a random matrix, a random probability measure and the corresponding empirical spectral distribution. The technical tool we use is the Stieltjes transform method through which we prove optimal convergence of the empirical spectral distribution of random sample covariance matrices to the deterministic Marchenko-Pastur distribution. We also give new results about the rigidity of the eigenvalues of this random sample covariance matrix and the rate of their convergence. We then define the Dyson equation method to prove new local laws about a random matrix model that interpolates between the Marchenko-Pastur distribution, the elliptical law and the circular law. Through our work these local laws can be considered universal.

math.PR

Moments approach for the elephant random walk

We discuss the method of moments for the one-dimensional elephant random walk (ERW). We first derive a differential recurrence relation for the characteristic function of the ERW, which yields a corresponding system of recurrence relations for its moments. We then obtain asymptotic approximations for the moments in each of the three parameter regimes of the ERW. Finally, by establishing the convergence of the moments and verifying the corresponding moment-determinacy conditions, we identify the limiting distributions of the ERW in each regime.

math.PR