Several teleportation schemes of an arbitrary unknown multi-particle state via different quantum channels

We first provide four new schemes for two-party quantum teleportation of an arbitrary unknown multi-particle state by using three-, four-, and five-particle states as the quantum channel, respectively. The successful probability and fidelity of the four schemes reach 1. In the first two schemes, the receiver can only apply one of the unitary transformations to reconstruct the original state, making it easier for these two schemes to be directly realized. In the third and fourth schemes, the sender can preform Bell-state measurements instead of multipartite entanglement measurements of the existing similar schemes, which makes real experiments more suitable. It is found that the last three schemes may become tripartite controlled teleportation schemes of teleporting an arbitrary multi-particle state after a simple modification. Finally, we present a new scheme for three-party sharing an arbitrary unknown multi-particle state. In this scheme, the sender first shares three three-particle GHZ states with two agents. After setting up the secure quantum channel, an arbitrary unknown multi-particle state can be perfectly teleported if the sender performs three Bell-state measurements, and either of two receivers operates an appropriate unitary transformation to obtain the original state with the help of other receiver＇s three single-particle measurements. The successful probability and fidelity of this scheme also reach 1. It is demonstrated that this scheme can be generalized easily to the case of sharing an arbitrary unknown multi-particle state among several agents.

A Theoretical Scheme for Multiparty Multi-particle State Sharing

A theoretical scheme for multiparty multi-particle state sharing is proposed. After she introduces auxiliary particles and Einstein-Podolsky-Rosen （EPIC） pairs, the sender （Alice） performs Hadamard （14） gate operations and Controlled-NOT （CNOT） gate operations on them. Subsequently, the sender leaves one particle sequence and distributes the rest particles to the other participants. And then, the sender makes Bell-state measurements on her particles and publishes the measurement outcomes via the classical channel to realize the quantum state sharing among the others. Only the simple operations are used to realize quantum state sharing. The sender may increase or decrease the number of the participants by changing the number of the auxiliary particles.

An Efficient Scheme for Multiparty Multi-particle State Sharing

We present an efficient scheme for sharing an arbitrary m-qubit state with n agents.In our scheme,the sender Alice first shares m Bell states with the agent Bob,who is designated to recover the original m-qubit state.Furthermore,Alice introduces n-1 auxiliary particles in the initial state |0>,applies Hadamard (H) gate and Controlled-Not(CNOT) gate operations on the particles,which make them entangled with one of m particle pairs in Bell states,and then sends them to the controllers (i.e.,other n-1 agents),where each controller only holds one particle in hand.After Alice performing m Bell-basis measurements and each controller a single-particle measurement,the recover Bobcan obtain the original unknown quantum state by applying the corresponding local unitary operations on his particles.Its intrinsic efficiency for qubits approaches 100%,and the total efficiency really approaches the maximal value.

Probabilistic Teleportation of Multi-particle d-Level Quantum State

The general scheme for teleportation of a multi-particle d-level quantumstate is presented when m pairs of partially entangled particles are utilized as quantum channels.The probabilistic teleportation can be achieved with a successful probability of Π from N=0 to d-1of (C_0~N)~2/d~M, which is determined by the smallest coefficients of each entangled channels.

Hierarchical simultaneous entanglement swapping for multi-hop quantum communication based on multi-particle entangled states

Entanglement swapping is a key technology for multi-hop communication based on entanglement in quantum networks. However, the end-to-end delay of the traditional sequential entanglement swapping (SEQES) grows rapidly withthe increase of network scale. To solve this problem, we first propose a low-delay multi-particle simultaneous entanglementswapping (SES) scheme to establish the remote four-particle Greenberger–Horne–Zeilinger (GHZ) channel states for thebidirectional teleportation of three-particle GHZ states, in which the intermediate nodes perform Bell state measurements,send the measurement results and the Bell state type to the user node Bob (or Alice) through classical channel simultaneously. Bob (or Alice) only needs to carry out a proper unitary operation according to the information he (or she) hasreceived. Further, we put forward a hierarchical simultaneous entanglement swapping (HSES) scheme to reduce the classical information transmission cost, which is composed of level-1 SES and level-2 SES (schemes). The former is an innersegment SES, and the latter is an inter segments SES. Theoretical analysis and simulation results show the HSES can obtainthe optimal performance tradeoff between end-to-end delay and classical cost.

Scheme for probabilistic remotely preparing a multi-particle entangled GHZ state

This paper presents a scheme for probabilistic remote preparation of a three-particle entangled Greenberger-Horne-Zeilinger （GHZ） state via three-particle orthonormal basis projective measurement, and then directly generalize the scheme to multi-particle case. It is shown that by using N pairs of bipartite non-maximally entangled states as the quantum channel and N-particle orthonormal basis projective measurement, the multi-particle remote preparation can be successfully realized with a certain probability.

Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

Prediction of microstructure evolution of ZK61 alloy during hot spinning by internal state variable model

An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.

Multi-hop quantum teleportation based on HSES via GHZ-like states

Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum communication, and utilize the logical relationship between the measurements of each node to derive the unitary operation performed by the end node. The hierarchical simultaneous entanglement switching(HSES) method is adopted, resulting in a significant reduction in the consumption of classical information compared to multi-hop quantum teleportation(QT)based on general simultaneous entanglement switching(SES). In addition, the proposed protocol is simulated on the IBM Quantum Experiment platform(IBM QE). Then, the data obtained from the experiment are analyzed using quantum state tomography, which verifies the protocol's good fidelity and accuracy. Finally, by calculating fidelity, we analyze the impact of four different types of noise(phase-damping, amplitude-damping, phase-flip and bit-flip) in this protocol.

Precision bounds for quantum phase estimation using two-mode squeezed Gaussian states

Quantum phase estimation based on Gaussian states plays a crucial role in many application fields.In this paper,we study the precision bound for the scheme using two-mode squeezed Gaussian states.The quantum Fisher information is calculated and its maximization is used to determine the optimal parameters.We find that two single-mode squeezed vacuum states are the optimal Gaussian inputs for a fixed two-mode squeezing process.The corresponding precision bound is sub-Heisenberg-limited and scales as N^(-1)/2.For practical purposes,we consider the effects originating from photon loss.The precision bound can still outperform the shot-noise limit when the lossy rate is below 0.4.Our work may demonstrate a significant and promising step towards practical quantum metrology.

Alterations of interhemispheric functional connectivity in patients with hypertensive retinopathy using voxelmirrored homotopic connectivity:a resting state fMRI study

AIM:To analyze whether alterations of voxel mirror homology connectivity(VMHC)values,as determined by resting-state functional magnetic resonance imaging(rsfMRI),occur in cerebral regions of patients with hypertensive retinopathy(HR)and to determine the relationship between VMHC values and clinical characteristics in patients with HR.METHODS:Twenty-one patients with HR and 21 agematched healthy controls(HCs)were assessed by rsfMRI scanning.The functional connectivity between the hemispheres of the cerebrum was assessed by measuring VMHC,with the ability of VMHC to distinguish between the HR and HC groups assessed using receiver operating characteristic(ROC)curve analysis.Differences in the demographic and clinical characteristics of the HR and HC groups were analyzed by independent sample t-tests.The relationship between average VMHC in several brain areas of HR patients and clinical features was determined using Pearson correlation analysis.RESULTS:Mean VMHC values of the bilateral cuneus gyrus(BA19),bilateral middle orbitofrontal gyrus(BA47),bilateral middle temporal gyrus(BA39)and bilateral superior medial frontal gyrus(BA9)were lower in the HR than in the HC group.CONCLUSION:VMHC values can predict the development of early HR,prevent the transformation of hypertensive microangiopathy,and provide useful information explaining the changes in neural mechanism associated with HR.

Machine learning based damage state identification:A novel perspective on fragility analysis for nuclear power plants considering structural uncertainties

Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.

Scheme for Robust Storage of Multi-particle Entanglement with a Cavity QED System

We propose a scheme for robustly storing multi-atom entangled states involving Bell states, three-particle W-state, n-particle W-like-states, generalized multi-particle W-states, n-particle GHZ-states, and partially entangled states in cavity QED. Our scheme can preserve the internal structure of the entangled states above, with only generation of a global phase corresponding to each of entangled states during the storage of them. One single-mode cavity and n identical two-level atoms are required. Our scheme may be realized in the present technology. The idea may be also utilized to store multi-trapped-ion entangled states in linear ion trap.

Morphology and valence state evolution of Cu:Unraveling the impact on nitric oxide electroreduction

Ammonia(NH3)serves as a critical component in the fertilizer industry and fume gas denitrification.However,the conventional NH3production process,namely the Haber-Bosch process,leads to considerable energy consumption and waste gas emissions.To address this,electrocatalytic nitric oxide reduction reaction(NORR)has emerged as a promising strategy to bridge NH3consumption to NH3production,harnessing renewable electricity for a sustainable future.Copper(Cu)stands out as a prominent electrocatalyst for NO reduction,given its exceptional NH3yield and selectivity.However,a crucial aspect that remains insufficiently explored is the effects of morphology and valence states of Cu on the NORR performance.In this investigation,we synthesized CuO nanowires(CuO-NF)and Cu nanocubes(Cu-NF)as cathodes through an in situ growth method.Remarkably,CuO-NF exhibited an impressive NH3yield of 0.50±0.02 mg cm^(-2)h^(-1)at-0.6 V vs.reversible hydrogen electrode(RHE)with faradaic efficiency of29,68%±1,35%,surpassing that of Cu-NF(0.17±0.01 mg cm^(-2)h^(-1),16.18%±1.40%).Throughout the electroreduction process,secondary cubes were generated on the CuO-NF surface,preserving their nanosheet cluster morphology,sustained by an abundant supply of subsurface oxygen(s-O)even after an extended duration of 10 h,until s-O depletion ensued.Conversely,Cu-NF exhibited inadequate s-O content,leading to rapid crystal collapse within the same timeframe.The distinctive current-potential relationship,akin to a volcano-type curve,was attributed to distinct NO hydrogenation mechanisms.Further Tafel analysis revealed the exchange current density(i0)and standard heterogeneous rate constant(k0)for CuO-NF,yielding 3.44×10^(-6)A cm^(-2)and 3.77×10^(-6)cm^(-2)s^(-1)when NORR was driven by overpotentials.These findings revealed the potential of CuO-NF for NO reduction and provided insights into the intricate interplay between crystal morphology,valence states,and electrochemical performance.

Association of DNA methylation/demethylation with the functional outcome of stroke in a hyperinflammatory state

Inflammation is closely related to stroke prognosis, and high inflammation status leads to poor functional outcome in stroke. DNA methylation is involved in the pathogenesis and prognosis of stroke. However, the effect of DNA methylation on stroke at high levels of inflammation is unclear. In this study, we constructed a hyperinflammatory cerebral ischemia mouse model and investigated the effect of hypomethylation and hypermethylation on the functional outcome. We constructed a mouse model of transient middle cerebral artery occlusion and treated the mice with lipopolysaccharide to induce a hyperinflammatory state. To investigate the effect of DNA methylation on stroke, we used small molecule inhibitors to restrain the function of key DNA methylation and demethylation enzymes. 2,3,5-Triphenyltetrazolium chloride staining, neurological function scores, neurobehavioral tests, enzyme-linked immunosorbent assay, quantitative reverse transcription PCR and western blot assay were used to evaluate the effects after stroke in mice. We assessed changes in the global methylation status by measuring DNA 5-mc and DNA 5-hmc levels in peripheral blood after the use of the inhibitor. In the group treated with the DNA methylation inhibitor, brain tissue 2,3,5-triphenyltetrazolium chloride staining showed an increase in infarct volume, which was accompanied by a decrease in neurological scores and worsening of neurobehavioral performance. The levels of inflammatory factors interleukin 6 and interleukin-1 beta in ischemic brain tissue and plasma were elevated, indicating increased inflammation. Related inflammatory pathway exploration showed significant overactivation of nuclear factor kappa B. These results suggested that inhibiting DNA methylation led to poor functional outcome in mice with high inflammation following stroke. Further, the effects were reversed by inhibition of DNA demethylation. Our findings suggest that DNA methylation regulates the inflammatory response in stroke and has an important role in the functional outcome of hyperinflammatory stroke.

1-35 Multi-particle Field Operators in Quantum Field Theory

Using bi-spinor fields we write the pseudo-scalar and bi-spinor fields that are characterized by the field functions of coordinates of several particles, namely multi-particle fields. By applying the quantization procedure to these multi-particle fields, hadronic creation and annihilation operators have been obtained.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Thermal safety boundary of lithium-ion battery at different state of charge

Thermal runaway(TR)is a critical issue hindering the large-scale application of lithium-ion batteries(LIBs).Understanding the thermal safety behavior of LIBs at the cell and module level under different state of charges(SOCs)has significant implications for reinforcing the thermal safety design of the lithium-ion battery module.This study first investigates the thermal safety boundary(TSB)correspondence at the cells and modules level under the guidance of a newly proposed concept,safe electric quantity boundary(SEQB).A reasonable thermal runaway propagation(TRP)judgment indicator,peak heat transfer power(PHTP),is proposed to predict whether TRP occurs.Moreover,a validated 3D model is used to quantitatively clarify the TSB at different SOCs from the perspective of PHTP,TR trigger temperature,SOC,and the full cycle life.Besides,three different TRP transfer modes are discovered.The interconversion relationship of three different TRP modes is investigated from the perspective of PHTP.This paper explores the TSB of LIBs under different SOCs at both cell and module levels for the first time,which has great significance in guiding the thermal safety design of battery systems.

Whole-process case management effects on mental state and selfcare ability in patients with liver cancer

BACKGROUND Regarding the incidence of malignant tumors in China,the incidence of liver cancer ranks fourth,second only to lung,gastric,and esophageal cancers.The case fatality rate ranks third after lung and cervical cancer.In a previous study,the whole-process management model was applied to patients with breast cancer,which effectively reduced their negative emotions and improved treatment adherence and nursing satisfaction.METHODS In this single-center,randomized,controlled study,60 randomly selected patients with liver cancer who had been admitted to our hospital from January 2021 to January 2022 were randomly divided into an observation group(n=30),who received whole-process case management on the basis of routine nursing mea-sures,and a control group(n=30),who were given routine nursing measures.We compared differences between the two groups in terms of anxiety,depression,the level of hope,self-care ability,symptom distress,sleep quality,and quality of life.RESULTS Post-intervention,Hamilton anxiety scale,Hamilton depression scale,memory symptom assessment scale,and Pittsburgh sleep quality index scores in both groups were lower than those pre-intervention,and the observation group had lower scores than the control group(P<0.05).Herth hope index,self-care ability assessment scale-revision in Chinese,and quality of life measurement scale for patients with liver cancer scores in both groups were higher than those pre-intervention,with higher scores in the observation group compared with the control group(P<0.05).CONCLUSION Whole-process case management can effectively reduce anxiety and depression in patients with liver cancer,alleviate symptoms and problems,and improve the level of hope,self-care ability,sleep quality,and quality of life,as well as provide feasible nursing alternatives for patients with liver cancer.

Pixelated non-volatile programmable photonic integrated circuits with 20-level intermediate states

Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum information.In this paper,we propose pixelated programmable Si_(3)N_(4)PICs with record-high 20-level intermediate states at 785 nm wavelength.Such flexibility in phase or amplitude modulation is achieved by a programmable Sb_(2)S_(3)matrix,the footprint of whose elements can be as small as 1.2μm,limited only by the optical diffraction limit of anin-house developed pulsed laser writing system.We believe our work lays the foundation for laser-writing ultra-high-level(20 levels and even more)programmable photonic systems and metasurfaces based on phase change materials,which could catalyze diverse applications such as programmable neuromorphic photonics,biosensing,optical computing,photonic quantum computing,and reconfigurable metasurfaces.