Jamming, relaxation, and memory in a minimally structured glass former

Area of Science:

• Condensed matter physics
• Statistical mechanics
• Computational physics

Background:

• Structural glasses form via non-equilibrium processes like temperature quenches, compression, and shear.
• Dynamical mean-field theory (DMFT) offers a framework for understanding these processes.
• Existing numerical tools are insufficient to solve DMFT equations in relevant physical regimes.

Purpose of the Study:

• To investigate glass formation in minimally structured models under out-of-equilibrium conditions.
• To compare the Mari-Kurchan model with the random Lorentz gas within the context of DMFT.
• To gain insights into the behavior of structural glasses and advance DMFT solutions.

Main Methods:

• Numerical simulations of the infinite-range Mari-Kurchan model.
• Comparison of simulation results with the random Lorentz gas model.
• Analysis of out-of-equilibrium processes including temperature and density changes.

Main Results:

• Both models, being mean-field-like, exhibit comparable behaviors relevant to DMFT.
• Insights were gained into temperature and density onsets, memory effects, and anomalous relaxation.
• The study contributes to understanding jamming density in these models.

Conclusions:

• Minimally structured models provide valuable insights for developing DMFT solutions for structural glasses.
• The comparison highlights robust features expected in DMFT, aiding theoretical development.
• This research advances the algorithmic understanding of jamming density and glass transition phenomena.