Large-dimensional quantum state engineering

Schematic of an automated platform for designing arbitrary qudit states in the orbital angular momentum of photons. The experimental parameters are adaptively optimized for the generation of target states. Credit: Alessia Suprano, Danilo Zia and Nicolò Spagnolo.

The adoption of large quantum states in quantum information protocols enables better performance in applications ranging from secure quantum communications to fault tolerant quantum computing. The development of universal protocols capable of designing arbitrary large-dimensional quantum states would be an important achievement. Several strategies and platforms have been proposed and developed for this purpose. Quantum Walking (QW) dynamics have been shown to enable the development of universal and platform independent state engineering protocols. However, the inevitable presence of noise, and the imperfections in the characterization of experimental devices, decrease the overall quality of state generation.

To overcome these limitations, a team of researchers from Sapienza Università di Roma, Queen’s University of Belfast and Università degli Studi di Palermo, demonstrate the use of an adaptive optimization protocol that can generate arbitrary states large, as indicated in Advanced photonics. In an all black box scenario, the protocol adjusts the relevant experimental parameters based only on the measured agreement between the produced state and the target state, without the need for a description of the generation setup.

The authors present an experimental verification of the proposed protocol using the orbital angular momentum (OAM) of classical light and single photons. OAM is a degree of freedom of the electromagnetic field related to its spatial and phase profile. Since OAM is an infinite dimensional degree of freedom, it is suitable for encoding high dimensional arbitrary quantum states. The authors experimentally implement the protocol using a state generation platform based on the dynamics of quantum walking in OAM and polarization degrees of freedom. By adjusting the parameters of the operators acting on the polarization state, an arbitrary walker state encoded in the OAM space can be designed. The proposed optimization algorithm then performs on-line tuning of the experimental parameters resulting in the dynamics to achieve the desired result.

Large-dimensional quantum state engineering

Conceptual diagram of the engineering protocol. a) The optimization algorithm adjusts the parameters to optimize the engineering performance of an arbitrary target walker state. b) Modification of the OAM mode during the iterations of the algorithm. In the first iteration, the shape of the beam is completely random, during the evolution it improves until it almost completely coincides with the target state. Credit: Suprano et al., Doi 10.1117 / 1.AP.3.6.066002.

The optimization protocol is shown to work well when subjected to noisy experimental conditions, for several four-dimensional target OAM states. Finally, the team studied the adaptability of the protocol by introducing a time varying noise as an external disturbance on the values ​​of the parameters. The protocol found the new optimal solution after the introduction of these external disturbances. The proposed protocol is applicable in a wide variety of circumstances, even in the presence of disturbances, without the need for significant fine tuning.

According to lead author Fabio Sciarrino, head of the quantum information laboratory of the physics department of the Sapienza Università di Roma, “The proposed dynamic learning protocol will be beneficial for several quantum information tasks that require finding optimal values. of experimental parameters under noisy conditions. ”

Optimized method to detect large dimension entanglement

More information:
Alessia Suprano et al, Dynamic learning of a photonic engineering process of the quantum state, Advanced photonics (2021). DOI: 10.1117 / 1.AP.3.6.066002

Quote: Large Dimensional Quantum State Engineering (2021, December 21) retrieved December 21, 2021 from

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