Storage of multiple single-photon pulses emitted from a quantum dot in a solid-state quantum memory

Quantum repeaters are critical components for distributing entanglement over long distances in presence of unavoidable optical losses during transmission. Stimulated by Duan-Lukin-Cirac-Zoller protocol, many improved quantum-repeater protocols based on quantum memories have been proposed, which commonly focus on the entanglement-distribution rate. Among these protocols, the elimination of multi-photons (multi-photon-pairs) and the use of multimode quantum memory are demonstrated to have the ability to greatly improve the entanglement-distribution rate. Here, we demonstrate the storage of deterministic single photons emitted from a quantum dot in a polarization-maintaining solid-state quantum memory; in addition, multi-temporal-mode memory with $1$, $20$ and $100$ narrow single-photon pulses is also demonstrated. Multi-photons are eliminated, and only one photon at most is contained in each pulse. Moreover, the solid-state properties of both sub-systems make this configuration more stable and easier to be scalable. Our work will be helpful in the construction of efficient quantum repeaters based on all-solid-state devicesComment: Published version, including supplementary materia

Reservoir Permeability Prediction Based on Analogy and Machine Learning Methods: Field Cases in DLG Block of Jing’an Oilfield, China

AbstractReservoir permeability, generally determined by experimental or well testing methods, is an essential parameter in the oil and gas field development. In this paper, we present a novel analogy and machine learning method to predict reservoir permeability. Firstly, the core test and production data of other 24 blocks (analog blocks) are counted according to the DLG block (target block) of Jing’an Oilfield, and the permeability analogy parameters including porosity, shale content, reservoir thickness, oil saturation, liquid production, and production pressure difference are optimized by Pearson and principal component analysis. Then, the fuzzy matter element method is used to calculate the similarity between the target block and analog blocks. According to the similarity calculation results, reservoir permeability of DLG block is predicted by reservoir engineering method (the relationship between core permeability and porosity of QK-D7 in similar blocks) and machine learning method (random forest, gradient boosting decision tree, light gradient boosting machine, and categorical boosting). By comparing the prediction accuracy of the two methods through the evaluation index determination coefficient (R2) and root mean square error (RMSE), the CatBoost model has higher accuracy in predicting reservoir permeability, with R2 of 0.951 and RMSE of 0.139. Finally, the CatBoost model is selected to predict reservoir permeability of 121 oil wells in the DLG block. This work uses simple logging and production data to quickly and accurately predict reservoir permeability without coring and testing. At the same time, the prediction results are well applied to the formulation of DLG block development technology strategy, which provides a new idea for the application of machine learning to predict oilfield parameters

Complete remission of advanced pancreatic cancer induced by claudin18.2-targeted CAR-T cell therapy: a case report

Pancreatic cancer (PC) is one of the most malignant tumors in digestive system due to its highly invasive and metastatic properties. At present, conventional treatment strategies for PC show the limited clinical efficacy. Therefore, novel effective therapeutic strategies are urgently needed. Here, we report a case of complete remission of advanced PC induced by claudin18.2-targeted CAR-T cell therapy. The patient was a 72-year-old man who was diagnosed with pancreatic ductal adenocarcinoma 2 years ago, and he experienced tumor recurrence and multiple metastases after pancreaticoduodenectomy and multi-line chemotherapies, including liver, peritoneum, and cervical lymph node metastases. Then, the patient was referred to our department for further treatment of metastatic PC, and he was enrolled in a clinical trial of claudin18.2-targeted CAR-T cell therapy. After lymphodepleting chemotherapy, the patient received claudin18.2-targeted CAR-T cell infusion at a dose of 1.2 × 106 cells/kg on November 21, 2022. During CAR-T cell therapy, the patient experienced grade 2 cytokine release syndrome (CRS) and gastric mucosa injury, which were controlled by tocilizumab and conventional symptomatic and supportive treatment. The patient achieved a complete response (CR) 1 month after claudin18.2-targeted CAR-T cell therapy, and remained in clinical remission for 8 months. Unfortunately, the patient experienced claudin18.2-negative relapse in July, 2023. Despite antigen-negative relapse after claudin18.2-targeted CAR-T cell infusion, the patient achieved sustained remission for 8 months, which indicates that claudin18.2-targeted CAR-T cell therapy is an extremely effective therapeutic strategy for the treatment of advanced PC

Charge Measurement of Cosmic Ray Nuclei with the Plastic Scintillator Detector of DAMPE

One of the main purposes of the DArk Matter Particle Explorer (DAMPE) is to measure the cosmic ray nuclei up to several tens of TeV or beyond, whose origin and propagation remains a hot topic in astrophysics. The Plastic Scintillator Detector (PSD) on top of DAMPE is designed to measure the charges of cosmic ray nuclei from H to Fe and serves as a veto detector for discriminating gamma-rays from charged particles. We propose in this paper a charge reconstruction procedure to optimize the PSD performance in charge measurement. Essentials of our approach, including track finding, alignment of PSD, light attenuation correction, quenching and equalization correction are described detailedly in this paper after a brief description of the structure and operational principle of the PSD. Our results show that the PSD works very well and almost all the elements in cosmic rays from H to Fe are clearly identified in the charge spectrum.Comment: 20 pages, 4 figure

Differential Changes of Aorta and Carotid Vasodilation in Type 2 Diabetic GK and OLETF Rats: Paradoxical Roles of Hyperglycemia and Insulin

We investigated large vessel function in lean Goto-Kakizaki diabetic rats (GK) and Otsuka Long-Evans Tokushima Fatty diabetic rats (OLETF) with possible roles of hyperglycemia/hyperosmolarity and insulin. Both young and old GK showed marked hyperglycemia with normal insulin level and well-preserved endothelium-dependent and endothelium-independent vasodilation in aorta and carotid artery. There were significant elevations in endothelial/inducible nitric oxide synthase (eNOS/iNOS) and inducible/constitutive heme oxygenase (HO-1/HO-2) in GK. The endothelium-dependent vasodilation in GK was inhibited partly by NOS blockade and completely by simultaneous blocking of HO and NOS. In contrast, OLETF showed hyperinsulinemia and mild hyperglycemia but significant endothelium dysfunction beginning at early ages with concomitantly reduced eNOS. Insulin injection corrected hyperglycemia in GK but induced endothelium dysfunction and intima hyperplasia. Hyperglycemia/hyperosmolarity in vitro enhanced vessel eNOS/HO. We suggest that hyperinsulinemia plays a role in endothelium dysfunction in obese diabetic OLETF, while hyperglycemia/hyperosmolarity-induced eNOS/HO upregulation participates in the adaptation of endothelium function in lean diabetic GK