4.7 Article

Classical description of the parameter space geometry in the Dicke and Lipkin-Meshkov-Glick models

Journal

PHYSICAL REVIEW E
Volume 104, Issue 1, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.104.014113

Keywords

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Funding

  1. CONACyT [332577]
  2. DGAPA-UNAM postdoctoral fellowship
  3. Consejo Nacional de Ciencia y Tecnologia (CONACyT), Mexico [A1S7701]
  4. DGAPA-PAPIIT [IN103919]

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In this study, the researchers investigated the classical analog of the quantum metric tensor and its scalar curvature for two well-known quantum physics models. They found that in the thermodynamic limit, the classical and quantum metrics have similar behaviors near the quantum phase transition, but the scalar curvatures show divergence only under certain conditions. Additionally, numerical analysis for finite sizes revealed precursors of the quantum phase transition in metric and scalar curvature, providing insight into their characterization as functions of parameters and system size.
We study the classical analog of the quantum metric tensor and its scalar curvature for two well-known quantum physics models. First, we analyze the geometry of the parameter space for the Dicke model with the aid of the classical and quantum metrics and find that, in the thermodynamic limit, they have the same divergent behavior near the quantum phase transition, as opposed to their corresponding scalar curvatures which are not divergent there. On the contrary, under resonance conditions, both scalar curvatures exhibit a divergence at the critical point. Second, we present the classical and quantum metrics for the Lipkin-Meshkov-Glick model in the thermodynamic limit and find a perfect agreement between them. We also show that the scalar curvature is only defined on one of the system's phases and that it approaches a negative constant value. Finally, we carry out a numerical analysis for the system's finite sizes, which clearly shows the precursors of the quantum phase transition in the metric and its scalar curvature and allows their characterization as functions of the parameters and of the system's size.

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