Random polynomials having few or no real zeros
By Amir Dembo, Bjorn Poonen, Qi-Man Shao, Ofer Zeitouni. 2000
84 citations recorded by the source corpus.
Consider a polynomial of large degree n whose coefficients are independent, identically distributed, nondegenerate random variables having zero mean and finite moments of all orders. We show that such a polynomial has exactly k real zeros with probability n−b+o(1) as n → ∞ through integers of the same parity as the fixed integer k ≥ 0. In particular, the probability that a random polynomial of large even degree n has no real zeros is n−b+o(1). The finite, positive constant b is characterized via the centered, stationary Gaussian process of correlation function sech(t/2). The value of b depends neither on k nor upon the specific law of the coefficients. Under an extra smoothness assumption about the law of the coefficients, with probability n−b+o(1) one may specify also the approximate locations of the k zeros on the real line. The constant b is replaced by b/2 in case the i.i.d. coefficients have a nonzero mean.
Subfields: Geometry and Topology, Mathematical Physics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/ecc29239883ffbbb99b4bc25d7737e4bc79e39c7
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In Geometry and Topology
- Van H. Vu
- Terence Tao
- Frank Aurzada
- Steffen Dereich
- Amir Dembo
- Hoi H. Nguyen
- Nikos Frantzikinakis
- Tom Sanders
In Mathematical Physics
In Statistics and Probability
- Van H. Vu
- Terence Tao
- Nicholas A. Cook
- L. Erdős
- Hoi H. Nguyen
- Horng-Tzer Yau
- Jun Yin
- Charles Bordenave
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- No zero-crossings for random polynomials and the heat equation (2012, background): “Here bα = 0 when α ≤ −1 and otherwise bα ∈ (0,∞) is independent of the detailed regularly varying variance function and corresponds to persistence probabilities for an explicit stationary Gaussian process of smooth sample path.”
- Local Universality of Zeroes of Random Polynomials (2013, background): “39, 40] also proved that if P(ξ= 0) = 0 and E|ξ|2+ε <∞ for some constant ε>0 then the variance of NR is (4 π(1 − 2 π) + o(1))logn, and furthermore established a central limit theorem for NR. In [10], Dembo et. al. computed the probability that NR = kfor any fixed k. There are also some non-triv”