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Long-Range Phase Order in Two Dimensions under Shear Flow.

Hiroyoshi Nakano1, Yuki Minami2, Shin-Ichi Sasa1

  • 1Department of Physics, Kyoto University, Kyoto 606-8502, Japan.

Physical Review Letters
|May 7, 2021
PubMed
Summary
This summary is machine-generated.

Shear flow in a two-dimensional O(2) model unexpectedly creates long-range order by suppressing phase fluctuations. This non-equilibrium system exhibits a second-order phase transition with critical exponents resembling equilibrium mean-field values.

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Area of Science:

  • Condensed matter physics
  • Statistical mechanics
  • Non-equilibrium systems

Background:

  • Understanding phase transitions and order in systems driven far from equilibrium is crucial.
  • Shear flow effects on phase ordering are complex and not fully understood.
  • The two-dimensional O(2) model serves as a fundamental framework for studying phase transitions.

Purpose of the Study:

  • To investigate the emergence of long-range order in a 2D O(2) model under shear flow.
  • To analyze the role of shear flow in suppressing phase fluctuations.
  • To characterize the nature of the phase transition and its critical exponents.

Main Methods:

  • Theoretical analysis of the two-dimensional O(2) model.
  • Numerical simulations to observe emergent phenomena.
  • Application of finite-size scaling theory to determine transition order.
  • Calculation of critical exponents at the non-equilibrium transition point.

Main Results:

  • Demonstration of anomalous suppression of phase fluctuations by shear flow.
  • Observation of emergent long-range phase order in two dimensions.
  • Confirmation of a second-order phase transition from a disordered to an ordered state.
  • Critical exponents at the non-equilibrium transition are found to be near mean-field values.

Conclusions:

  • Shear flow can induce long-range order in 2D systems by altering fluctuation dynamics.
  • The non-equilibrium phase transition shares characteristics with equilibrium mean-field transitions.
  • This study provides insights into ordering phenomena in driven soft matter systems.