The DOI matches its Crossref record.
Wegner Estimate and Level Repulsion for Wigner Random Matrices
Open accessAbstract
We consider N × N Hermitian random matrices with independent identically distributed entries (Wigner matrices). The matrices are normalized so that the average spacing between consecutive eigenvalues is of order 1/ N. Under suitable assumptions on the distribution of the single matrix element, we first prove that, away from the spectral edges, the empirical density of eigenvalues concentrates around the Wigner semicircle law on energy scales η ≫ N−1. This result establishes the semicircle law on the optimal scale and it removes a logarithmic factor from our previous result [6]. We then show a Wegner estimate, i.e., that the averaged density of states is bounded. Finally, we prove that the eigenvalues of a Wigner matrix repel each other, in agreement with the universality conjecture.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Rigidity of eigenvalues of generalized Wigner matrices
Erdős, L., Yau, H.-T., & Yin, J. (2012) · Advances in Mathematics · doi:10.1016/j.aim.2011.12.010 · Cited by 345
Self-citationBulk universality for generalized Wigner matrices
Erdős, L., Yau, H.-T., & Yin, J. (2012) · Probability Theory and Related Fields · doi:10.1007/s00440-011-0390-3 · Cited by 254
Self-citationLocal law and Tracy–Widom limit for sparse random matrices
Lee, J. O., & Schnelli, K. (2018) · Probability Theory and Related Fields · doi:10.1007/s00440-017-0787-8 · Cited by 87
Metadata
- Authors
- Erdős, L., Schlein, B., & Yau, H.-T.
- Venue
- International Mathematics Research Notices
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-08-29
- Volume
- 2010
- Issue
- 3
- Pages
- 436-479
- ISSN
- 1073-7928 (ISSN-L)
- 1687-0247
- OpenAlex
- W2963432094
- Cited by
- 169
- References
- 0
- FWCI
- 14.48
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Wegner Estimate and Level Repulsion for Wigner Random Matrices. https://app.cochat.ai/papers/10.1093/imrn/rnp136
- The paper
- Erdős, L., Schlein, B., & Yau, H.-T. (2010). Wegner Estimate and Level Repulsion for Wigner Random Matrices. International Mathematics Research Notices. https://doi.org/10.1093/imrn/rnp136
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.