The no-cloning theorem has sparked considerable interest in achieving high-fidelity approximate quantum cloning.Most of the previous studies mainly focused on the cloning of single particle states,and cloning schemes ...The no-cloning theorem has sparked considerable interest in achieving high-fidelity approximate quantum cloning.Most of the previous studies mainly focused on the cloning of single particle states,and cloning schemes used there are incapable of cloning quantum entangled states in multipartite systems.Few schemes were proposed for cloning multiparticle states,which consume more entanglement resources with loss of qubits,and the fidelity of the cloned state is relatively low.In this paper,cloning schemes for bipartite and tripartite entangled states based on photonic quantum walk and entanglement swapping are proposed.The results show that according to the proposed schemes,two high-fidelity(up to 0.75)cloned states can be obtained with less quantum resource consumption.Because of the simple cloning steps,few quantum resources and high fidelity,these schemes are both efficient and feasible.Moreover,this cloning machine eliminates the need for tracing out cloning machine,thereby minimizing resource waste.展开更多
Soft polymer optical fiber(SPOF)has shown great potential in optical-based wearable and implantable biosensors due to its excellent mechanical properties and optical guiding characteristics.However,the multimodality c...Soft polymer optical fiber(SPOF)has shown great potential in optical-based wearable and implantable biosensors due to its excellent mechanical properties and optical guiding characteristics.However,the multimodality characteristics of SPOF limit their integration with traditional fiber optic sensors.This article introduces for the first time a flexible fiber optic vibration sensor based on laser interference technology,which can be applied to vibration measurement under high stretch conditions.This sensor utilizes elastic optical fibers made of polydimethylsiloxane(PDMS)as sensing elements,combined with phase generating carrier technology,to achieve vibration measurement at 50−260 Hz within the stretch range of 0−42%.展开更多
High-resolution flow field data has important applications in meteorology,aerospace engineering,high-energy physics and other fields.Experiments and numerical simulations are two main ways to obtain high-resolution fl...High-resolution flow field data has important applications in meteorology,aerospace engineering,high-energy physics and other fields.Experiments and numerical simulations are two main ways to obtain high-resolution flow field data,while the high experiment cost and computing resources for simulation hinder the specificanalysis of flow field evolution.With the development of deep learning technology,convolutional neural networks areused to achieve high-resolution reconstruction of the flow field.In this paper,an ordinary convolutional neuralnetwork and a multi-time-path convolutional neural network are established for the ablative Rayleigh-Taylorinstability.These two methods can reconstruct the high-resolution flow field in just a few seconds,and further greatlyenrich the application of high-resolution reconstruction technology in fluid instability.Compared with the ordinaryconvolutional neural network,the multi-time-path convolutional neural network model has smaller error and canrestore more details of the flow field.The influence of low-resolution flow field data obtained by the two poolingmethods on the convolutional neural networks model is also discussed.展开更多
文摘The no-cloning theorem has sparked considerable interest in achieving high-fidelity approximate quantum cloning.Most of the previous studies mainly focused on the cloning of single particle states,and cloning schemes used there are incapable of cloning quantum entangled states in multipartite systems.Few schemes were proposed for cloning multiparticle states,which consume more entanglement resources with loss of qubits,and the fidelity of the cloned state is relatively low.In this paper,cloning schemes for bipartite and tripartite entangled states based on photonic quantum walk and entanglement swapping are proposed.The results show that according to the proposed schemes,two high-fidelity(up to 0.75)cloned states can be obtained with less quantum resource consumption.Because of the simple cloning steps,few quantum resources and high fidelity,these schemes are both efficient and feasible.Moreover,this cloning machine eliminates the need for tracing out cloning machine,thereby minimizing resource waste.
文摘Soft polymer optical fiber(SPOF)has shown great potential in optical-based wearable and implantable biosensors due to its excellent mechanical properties and optical guiding characteristics.However,the multimodality characteristics of SPOF limit their integration with traditional fiber optic sensors.This article introduces for the first time a flexible fiber optic vibration sensor based on laser interference technology,which can be applied to vibration measurement under high stretch conditions.This sensor utilizes elastic optical fibers made of polydimethylsiloxane(PDMS)as sensing elements,combined with phase generating carrier technology,to achieve vibration measurement at 50−260 Hz within the stretch range of 0−42%.
基金National Natural Science Foundation of China(1180500311947102+4 种基金12004005)Natural Science Foundation of Anhui Province(2008085MA162008085QA26)University Synergy Innovation Program of Anhui Province(GXXT-2022-039)State Key Laboratory of Advanced Electromagnetic Technology(Grant No.AET 2024KF006)。
文摘High-resolution flow field data has important applications in meteorology,aerospace engineering,high-energy physics and other fields.Experiments and numerical simulations are two main ways to obtain high-resolution flow field data,while the high experiment cost and computing resources for simulation hinder the specificanalysis of flow field evolution.With the development of deep learning technology,convolutional neural networks areused to achieve high-resolution reconstruction of the flow field.In this paper,an ordinary convolutional neuralnetwork and a multi-time-path convolutional neural network are established for the ablative Rayleigh-Taylorinstability.These two methods can reconstruct the high-resolution flow field in just a few seconds,and further greatlyenrich the application of high-resolution reconstruction technology in fluid instability.Compared with the ordinaryconvolutional neural network,the multi-time-path convolutional neural network model has smaller error and canrestore more details of the flow field.The influence of low-resolution flow field data obtained by the two poolingmethods on the convolutional neural networks model is also discussed.
