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Correlations in twisted double-layer graphene with virtual photons in a microcavity
Facundo Arreyes1, Federico Escudero1,2, Juan Sebastián Ardenghi1,2
1Departamento de Física, Universidad Nacional del Sur, Avenida Alem 1253, B8000CPB, Bahía Blanca, Argentina.
Journal of Physics. Condensed Matter : an Institute of Physics Journal
|December 16, 2021
Summary
Researchers explored entanglement generation in rotated graphene layers within a microcavity. They found that quantum correlations can be achieved and manipulated by adjusting geometric parameters and exploiting non-causal effects via virtual photon exchange.
Area of Science:
- Quantum Physics
- Materials Science
- Condensed Matter Physics
Background:
- Graphene's unique electronic properties make it a candidate for quantum information applications.
- Microcavities can confine electromagnetic fields, influencing quantum interactions.
- Entanglement generation is crucial for quantum technologies.
Purpose of the Study:
- To analyze entanglement generation between two rotated graphene layers in a microcavity.
- To determine geometric parameters for achieving electron entanglement.
- To investigate non-causal effects in entanglement generation.
Main Methods:
- Utilized time-dependent perturbation theory.
- Considered the electromagnetic field in the vacuum state.
- Employed the negativity measure to quantify correlations.
- Analyzed an experimental protocol involving back-voltage switching.
Main Results:
- Identified geometric parameter ranges for electron entanglement.
- Demonstrated correlations on timescales shorter than light-crossing time.
- Showed that rotation angle modulates entanglement (negativity measure).
- Confirmed that non-causal propagation via virtual photons can create entangled states.
Conclusions:
- Entanglement generation in rotated graphene layers is feasible within a microcavity.
- Geometric parameters and rotation angles offer control over entanglement.
- Non-causal effects mediated by virtual photons can establish quantum correlations between layers.
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