Order parameter scaling in fluctuation dominated phase ordering
Rajeev Kapri, Malay Bandyopadhyay, Mustansir Barma

TL;DR
This paper investigates the scaling behavior of multiple order parameters in fluctuation-dominated phase ordering systems, revealing distinct static and dynamic scaling laws for Fourier modes under different surface evolutions.
Contribution
It introduces a comprehensive analysis of order parameter scaling in fluctuation-dominated phase ordering, emphasizing the necessity of multiple Fourier components and characterizing their static and dynamic scaling laws.
Findings
Mean Fourier mode scales as L^{- ext{exponent}} with different exponents for EW and KPZ.
Scaling functions describe the probability distributions and correlation functions of Fourier modes.
Temporal intermittency and divergence of flatness are observed in the coarse-grained depth model.
Abstract
In systems exhibiting fluctuation-dominated phase ordering, a single order parameter does not suffice to characterize the order, and it is necessary to monitor a larger set. For hard-core sliding particles (SP) on a fluctuating surface and the related coarse-grained depth (CD) models, this set comprises the long-wavelength Fourier components of the density profile. We study both static and dynamic scaling laws obeyed by the Fourier modes and find that the mean value obeys the static scaling law with and with Edwards-Wilkinson (EW) and Kardar-Parisi-Zhang (KPZ) surface evolution respectively. The full probability distribution exhibits scaling as well. Further, time-dependent correlation functions such as the steady state auto-correlation and cross-correlations of order parameter components are…
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