Necessary condition for information transfer under simulated parity-time-symmetric evolution
- URL: http://arxiv.org/abs/2102.13630v2
- Date: Thu, 16 May 2024 23:01:24 GMT
- Title: Necessary condition for information transfer under simulated parity-time-symmetric evolution
- Authors: Leela Ganesh Chandra Lakkaraju, Shiladitya Mal, Aditi Sen De,
- Abstract summary: Parity-time (PT) symmetric quantum theory can broaden the scope of quantum dynamics beyond unitary evolution.
A non-trivial information transfer can happen if one side of a composite system is evolved according to a PT-symmetric way.
We prove that the information transfer can only happen when the density matrix and the corresponding measurements contain complex numbers.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Parity-time (PT) symmetric quantum theory can broaden the scope of quantum dynamics beyond unitary evolution which may lead to numerous counter-intuitive phenomena, including single-shot discrimination of non-orthogonal states, faster evolution of state than the standard quantum speed limit, and violation of no-signaling principle. On the other hand, PT-symmetric evolution can be realized as reduced dynamics of a subsystem in real experiments within the scope of standard quantum theory. In this experimental setup, if one side of a composite system is evolved according to a PT-symmetric way, a non-trivial information transfer can happen, i.e., the operation performed at one side can be gathered by the other side. By considering an arbitrary shared state between two parties situated in two distant locations and arbitrary measurements, we show that the PT-symmetric evolution of the reduced subsystem at one side is not sufficient for this information transfer to occur. Specifically, we prove that the information transfer can only happen when the density matrix and the corresponding measurements contain complex numbers. Moreover, we connect the entanglement content of the shared state with the efficacy of information transfer. We find evidence that the task becomes more efficient with the increase of dimension.
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