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On the singularity probability of random Bernoulli matrices

Author(s): Terence Tao; Van Vu
Journal: J. Amer. Math. Soc. 20 (2007), 603-628.
MSC (2000): Primary 15A52
Posted: February 6, 2007
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Abstract: Let $ n$ be a large integer and let $ M_n$ be a random $ n \times n$ matrix whose entries are i.i.d. Bernoulli random variables (each entry is $ \pm 1$ with probability $ 1/2$). We show that the probability that $ M_n$ is singular is at most $ (3/4 +o(1))^n$, improving an earlier estimate of Kahn, Komlós and Szemerédi, as well as earlier work by the authors. The key new ingredient is the applications of Freiman-type inverse theorems and other tools from additive combinatorics.


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Additional Information:

Terence Tao
Affiliation: Department of Mathematics, UCLA, Los Angeles, California 90095-1555
Email: tao@math.ucla.edu

Van Vu
Affiliation: Department of Mathematics, Rutgers University, Piscataway, New Jersey 08854-8019
Email: vanvu@ucsd.edu

DOI: 10.1090/S0894-0347-07-00555-3
PII: S 0894-0347(07)00555-3
Received by editor(s): November 5, 2004
Posted: February 6, 2007
Additional Notes: The first author is a Clay Prize Fellow and is supported by a grant from the Packard Foundation.
The second author is an A. Sloan Fellow and is supported by an NSF Career Grant.
Copyright of article: Copyright 2007, American Mathematical Society
The copyright for this article reverts to public domain after 28 years from publication.


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