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We investigated nonequilibrium aging in the random-field Ising model, observing how its behavior shifts across the ferromagnetic-paramagnetic phase transition. This study reveals insights into critical dynamics and emergent properties in disordered magnetic systems.

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Area of Science:

  • Condensed Matter Physics
  • Statistical Mechanics
  • Computational Physics

Background:

  • The random-field Ising model describes magnetic systems with quenched disorder.
  • Nonequilibrium aging phenomena are crucial for understanding systems below their critical temperature.
  • Phase transitions in disordered systems exhibit complex dynamics.

Purpose of the Study:

  • To investigate the nonequilibrium aging behavior of the 3D random-field Ising model.
  • To analyze how aging dynamics change across the ferromagnetic-paramagnetic phase transition.
  • To extract critical exponents and a growing length scale.

Main Methods:

  • Simulations of the random-field Ising model with system sizes up to N=256^3 spins.
  • Utilized long Monte Carlo simulations (up to 10^8 sweeps).
  • Employed high-performance computing on Intel Xeon Phi coprocessors for efficient simulations (6 ps single-spin-flip times).

Main Results:

  • Measured typical correlation functions in space and time.
  • Identified a growing length scale characteristic of aging.
  • Extracted relevant exponents describing the aging dynamics.

Conclusions:

  • The study provides insights into the nonequilibrium aging dynamics of disordered magnetic systems.
  • Aging behavior is sensitive to the disorder strength and proximity to the phase transition.
  • The findings contribute to the understanding of critical phenomena in disordered systems.