TY - JOUR
T1 - Large deviations of the interface height in the Golubović-Bruinsma model of stochastic growth
AU - Meerson, Baruch
AU - Vilenkin, Arkady
N1 - Publisher Copyright:
©2023 American Physical Society.
PY - 2023/7
Y1 - 2023/7
N2 - We study large deviations of the one-point height H of a stochastic interface, governed by the Golubović-Bruinsma equation, ∂_{t}h=-ν∂_{x}^{4}h+(λ/2)(∂_{x}h)^{2}+sqrt[D]ξ(x,t), where h(x,t) is the interface height at point x and time t and ξ(x,t) is the Gaussian white noise. The interface is initially flat, and H is defined by the relation h(x=0,t=T)=H. We focus on the short-time limit, T≪T_{NL}, where T_{NL}=ν^{5/7}(Dλ^{2})^{-4/7} is the characteristic nonlinear time of the system. In this limit typical, small fluctuations of H are unaffected by the nonlinear term, and they are Gaussian. However, the large-deviation tails of the probability distribution P(H,T) "feel" the nonlinearity already at short times, and they are non-Gaussian and asymmetric. We evaluate these tails using the optimal fluctuation method (OFM). The lower tail scales as -lnP(H,T)∼H^{5/2}/T^{1/2}. It coincides with its analog for the Kardar-Parisi-Zhang (KPZ) equation, and we point out to the mechanism of this universality. The upper tail scales as -lnP(H,T)∼H^{11/6}/T^{5/6}, it is different from the upper tail of the KPZ equation. We also compute the large deviation function of H numerically and verify our asymptotic results for the tails.
AB - We study large deviations of the one-point height H of a stochastic interface, governed by the Golubović-Bruinsma equation, ∂_{t}h=-ν∂_{x}^{4}h+(λ/2)(∂_{x}h)^{2}+sqrt[D]ξ(x,t), where h(x,t) is the interface height at point x and time t and ξ(x,t) is the Gaussian white noise. The interface is initially flat, and H is defined by the relation h(x=0,t=T)=H. We focus on the short-time limit, T≪T_{NL}, where T_{NL}=ν^{5/7}(Dλ^{2})^{-4/7} is the characteristic nonlinear time of the system. In this limit typical, small fluctuations of H are unaffected by the nonlinear term, and they are Gaussian. However, the large-deviation tails of the probability distribution P(H,T) "feel" the nonlinearity already at short times, and they are non-Gaussian and asymmetric. We evaluate these tails using the optimal fluctuation method (OFM). The lower tail scales as -lnP(H,T)∼H^{5/2}/T^{1/2}. It coincides with its analog for the Kardar-Parisi-Zhang (KPZ) equation, and we point out to the mechanism of this universality. The upper tail scales as -lnP(H,T)∼H^{11/6}/T^{5/6}, it is different from the upper tail of the KPZ equation. We also compute the large deviation function of H numerically and verify our asymptotic results for the tails.
UR - http://www.scopus.com/inward/record.url?scp=85165632432&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.108.014117
DO - 10.1103/PhysRevE.108.014117
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C2 - 37583177
AN - SCOPUS:85165632432
SN - 2470-0045
VL - 108
JO - Physical Review E
JF - Physical Review E
IS - 1
M1 - 014117
ER -