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14 pages, 2030 KiB

Open AccessArticle

Analysis of Dissipation Mechanisms for Cesium Rydberg Atoms in Magic-Wavelength Optical Trap

by Shaofeng Fan, Yang Liu, Wenyuan Liu, Yang Zhao, Yijun Li and Jiandong Bai

Photonics 2025, 12(2), 138; https://doi.org/10.3390/photonics12020138 - 8 Feb 2025

Viewed by 1064

A magic optical dipole trap (ODT) can confine atoms in the ground state and a highly excited state with the same light shifts, resulting in a long-range coherent lifetime between them, which plays an important role in high-fidelity quantum logic gates, multi-body physics and other quantum information. Here, we use a sum-over-states model to calculate the dynamic polarizabilities of the 6S_1/2 ground state and 46S_1/2 Rydberg state of Cs atoms and identify corresponding magic wavelengths and magic detunings for trapping the two states in the range of 900–1950 nm. Then, we analyze the robustness of the magic condition and the feasibility of the experimental operation. Furthermore, we estimate the trapping lifetime of Cs Rydberg atoms by considering different dissipation mechanisms, such as photon scattering and photoionization in the magic ODT. The photoexcitation and photoionization of Cs atoms under the action of three-step laser pulses are calculated by the rate equation. The presented results for magic-wavelength ODTs are of great significance for quantum information and quantum computing based on Rydberg atoms. Full article

(This article belongs to the Special Issue Optical Quantum System)

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44 pages, 1134 KiB

Open AccessReview

Excipients in the Paediatric Population: A Review

by Khadija Rouaz, Blanca Chiclana-Rodríguez, Anna Nardi-Ricart, Marc Suñé-Pou, Dèbora Mercadé-Frutos, Josep María Suñé-Negre, Pilar Pérez-Lozano and Encarna García-Montoya

Pharmaceutics 2021, 13(3), 387; https://doi.org/10.3390/pharmaceutics13030387 - 13 Mar 2021

Cited by 87 | Viewed by 17365

Abstract

This theoretical study seeks to critically review the use of excipients in the paediatric population. This study is based on the rules and recommendations of European and American drug regulatory agencies. On the one hand, this review describes the most frequent excipients used in paediatric medicine formulations, identifying the compounds that scientific literature has marked as potentially harmful regarding the side effects generated after exposure. On the other hand, this review also highlights the importance of carrying out safety -checks on the excipients, which, in most cases, are linked to toxicity studies. An excipient in the compilation of paediatric population databases is expected to target safety and toxicity, as in the STEP database. Finally, a promising pharmaceutical form for child population, ODT (Orally Disintegrating Tablets), will be studied. Full article

(This article belongs to the Special Issue Development and Adaptation of New and Better Pediatric Drugs)

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21 pages, 1549 KiB

Open AccessArticle

Power Quality Disturbances Feature Selection and Recognition Using Optimal Multi-Resolution Fast S-Transform and CART Algorithm

by Nantian Huang, Hua Peng, Guowei Cai and Jikai Chen

Energies 2016, 9(11), 927; https://doi.org/10.3390/en9110927 - 9 Nov 2016

Cited by 32 | Viewed by 5265

Abstract

In order to improve the recognition accuracy and efficiency of power quality disturbances (PQD) in microgrids, a novel PQD feature selection and recognition method based on optimal multi-resolution fast S-transform (OMFST) and classification and regression tree (CART) algorithm is proposed. Firstly, OMFST is carried out according to the frequency domain characteristic of disturbance signal, and 67 features are extracted by time-frequency analysis to construct the original feature set. Subsequently, the optimal feature subset is determined by Gini importance and sorted according to an embedded feature selection method based on the Gini index. Finally, one standard error rule subtree evaluation methods were applied for cost complexity pruning. After pruning, the optimal decision tree (ODT) is obtained for PQD classification. The experiments show that the new method can effectively improve the classification efficiency and accuracy with feature selection step. Simultaneously, the ODT can be constructed automatically according to the ability of feature classification. In different noise environments, the classification accuracy of the new method is higher than the method based on probabilistic neural network, extreme learning machine, and support vector machine. Full article

(This article belongs to the Special Issue Microgrids 2016)

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