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Critical decay exponent of the pair contact process with diffusion
1Department of Physics, The Catholic University of Korea, Bucheon 420-743, Republic of Korea.
This study investigates the one-dimensional pair contact process with diffusion (PCPD) using Monte Carlo simulations. The critical decay exponent was determined to be 0.173(3), regardless of diffusion rate, and compared to directed percolation.
Area of Science:
- Statistical Physics
- Complex Systems
- Nonlinear Dynamics
Background:
- The pair contact process with diffusion (PCPD) is a model system for studying spreading phenomena.
- Understanding critical exponents is crucial for classifying universality classes in statistical mechanics.
Purpose of the Study:
- To accurately determine the critical density decay exponent (δ) for the one-dimensional PCPD.
- To investigate the influence of diffusion rate on scaling corrections and critical behavior.
- To analyze crossover phenomena and their implications for the PCPD's universality class.
Main Methods:
- Extensive Monte Carlo simulations were employed to model the PCPD.
- A recently introduced method was used to find the strength of corrections to scaling.
- Effective exponents were systematically analyzed to determine the critical decay exponent.
- Crossover behaviors at different diffusion rates (d=0 and d=1) were studied.
Main Results:
- The leading corrections to scaling exhibit different behaviors for small (∼t^{-0.15}) and large (∼t^{-0.5}) diffusion rates.
- The critical decay exponent δ was found to be 0.173(3), independent of the diffusion rate.
- A discontinuous phase boundary was observed at d=0, with a crossover exponent ϕ=2.6(1).
- At d=1, the crossover exponent was found to be ϕ=2, suggesting an exact value.
Conclusions:
- The determined critical decay exponent (δ=0.173(3)) provides a key characteristic of the one-dimensional PCPD.
- The discontinuity at d=0 challenges the hypothesis that PCPD belongs to the directed percolation universality class.
- The crossover exponent at d=1 supports exact theoretical predictions for mean-field behavior.
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