Human skill knowledge guided global trajectory policy reinforcement learning method.

Traditional trajectory learning methods based on Imitation Learning (IL) only learn the existing trajectory knowledge from human demonstration. In this way, it can not adapt the trajectory knowledge to the task environment by interacting with the environment and fine-tuning the policy. To address this problem, a global trajectory learning method which combinines IL with Reinforcement Learning (RL) to adapt the knowledge policy to the environment is proposed. In this paper, IL is proposed to acquire basic trajectory skills, and then learns the agent will explore and exploit more policy which is applicable to the current environment by RL. The basic trajectory skills include the knowledge policy and the time stage information in the whole task space to help learn the time series of the trajectory, and are used to guide the subsequent RL process. Notably, neural networks are not used to model the action policy and the Q value of RL during the RL process. Instead, they are sampled and updated in the whole task space and then transferred to the networks after the RL process through Behavior Cloning (BC) to get continuous and smooth global trajectory policy. The feasibility and the effectiveness of the method was validated in a custom Gym environment of a flower drawing task. And then, we executed the learned policy in the real-world robot drawing experiment.

Minimum-Consumption Discrimination of Quantum States via Globally Optimal Adaptive Measurements.

Reducing the average resource consumption is the central quest in discriminating non-orthogonal quantum states for a fixed admissible error rate ϵ. The globally optimal fixed local projective measurement for this task is found to be different from that for previous minimum-error discrimination tasks [S. Slussarenko et al., Phys. Rev. Lett. 118, 030502 (2017)PRLTAO0031-900710.1103/PhysRevLett.118.030502]. To achieve the ultimate minimum average consumption, here we develop a general globally optimal adaptive strategy (GOA) by subtly using the updated posterior probability, which works under any error rate requirements and any one-way measurement restrictions, and can be solved by a convergent iterative relation. First, under the local measurement restrictions, our GOA is solved to serve as the local bound, which saves 16.6 copies (24%) compared with the previously best globally optimal fixed local projective measurement. When the more powerful two-copy collective measurements are allowed, our GOA is experimentally demonstrated to beat the local bound by 3.9 copies (6.0%). By exploiting both adaptivity and collective measurements, our Letter marks an important step toward minimum-consumption quantum state discrimination.

Experimental Investigation of Uncertainty Relations for Non-Hermitian Operators.

Uncertainty relations for Hermitian operators have been confirmed through many experiments. However, previous experiments have only tested the special case of non-Hermitian operators, i.e., uncertainty relations for unitary operators. In this study, we explore uncertainty relations for general non-Hermitian operators, which include Hermitian and unitary operators as special cases. We perform experiments with both real and complex non-Hermitian operators for qubit states, and confirm the validity of the uncertainty relations within the experimental error. Our results provide experimental evidence of uncertainty relations for non-Hermitian operators. Furthermore, our methods for realizing and measuring non-Hermitian operators are valuable in characterizing open-system dynamics and enhancing parameter estimation.

A von-Neumann-like photonic processor and its application in studying quantum signature of chaos.

Photonic quantum computation plays an important role and offers unique advantages. Two decades after the milestone work of Knill-Laflamme-Milburn, various architectures of photonic processors have been proposed, and quantum advantage over classical computers has also been demonstrated. It is now the opportune time to apply this technology to real-world applications. However, at current technology level, this aim is restricted by either programmability in bulk optics or loss in integrated optics for the existing architectures of processors, for which the resource cost is also a problem. Here we present a von-Neumann-like architecture based on temporal-mode encoding and looped structure on table, which is capable of multimode-universal programmability, resource-efficiency, phase-stability and software-scalability. In order to illustrate these merits, we execute two different programs with varying resource requirements on the same processor, to investigate quantum signature of chaos from two aspects: the signature behaviors exhibited in phase space (13 modes), and the Fermi golden rule which has not been experimentally studied in quantitative way before (26 modes). The maximal program contains an optical interferometer network with 1694 freely-adjustable phases. Considering current state-of-the-art, our architecture stands as the most promising candidate for real-world applications.

Experimental Demonstration of Inequivalent Mutually Unbiased Bases.

Quantum measurements based on mutually unbiased bases (MUBs) play crucial roles in foundational studies and quantum information processing. It is known that there exist inequivalent MUBs, but little is known about their operational distinctions, not to say experimental demonstration. In this Letter, by virtue of a simple estimation problem, we experimentally demonstrate the operational distinctions between inequivalent triples of MUBs in dimension 4 based on high-precision photonic systems. The experimental estimation fidelities coincide well with the theoretical predictions with only 0.16% average deviation, which is 25 times less than the difference (4.1%) between the maximum estimation fidelity and the minimum estimation fidelity. Our experiments clearly demonstrate that inequivalent MUBs have different information extraction capabilities and different merits for quantum information processing.

Efficient learning of mixed-state tomography for photonic quantum walk.

Noise-enhanced applications in open quantum walk (QW) has recently seen a surge due to their ability to improve performance. However, verifying the success of open QW is challenging, as mixed-state tomography is a resource-intensive process, and implementing all required measurements is almost impossible due to various physical constraints. To address this challenge, we present a neural-network-based method for reconstructing mixed states with a high fidelity (∼97.5%) while costing only 50% of the number of measurements typically required for open discrete-time QW in one dimension. Our method uses a neural density operator that models the system and environment, followed by a generalized natural gradient descent procedure that significantly speeds up the training process. Moreover, we introduce a compact interferometric measurement device, improving the scalability of our photonic QW setup that enables experimental learning of mixed states. Our results demonstrate that highly expressive neural networks can serve as powerful alternatives to traditional state tomography.

Arc discharge method to fabricate large concave structures for open-access fiber Fabry-Pérot cavities.

We present a novel micro-fabrication technique for creating concave surfaces on the endfacets of photonic crystal fibers. A fiber fusion splicer is used to generate arc discharges to melt and reshape the fiber endfacet. This technique can produce large spherical concave surfaces with roughness as low as 0.12 nm in various types of photonic crystal fibers. The deviation of fabricated surface and a spherical profile in the region of 70 µm in diameter is less than 50 nm. The center of the concave surface and the fiber mode field are highly coincident with a deviation less than 500 nm. Finesse measurements have shown that a Fabry-Pérot cavity composed of the fiber fabricated using this method and a plane mirror maintains finesse of 20000. This method is easy to replicate, making it a practical and efficient approach to fabricate concave surface on fibers for open-access fiber Fabry-Pérot cavities.

Reflective dielectric cavity enhanced emission from hexagonal boron nitride spin defect arrays.

Among the various kinds of spin defects in hexagonal boron nitride (hBN), the negatively charged boron vacancy (VB-) spin defect that can be site-specifically generated is undoubtedly a potential candidate for quantum sensing, but its low quantum efficiency restricts its practical applications. Here, we demonstrate a robust enhancement structure called reflective dielectric cavity (RDC) with advantages including easy on-chip integration, convenient processing, low cost and suitable broad-spectrum enhancement for VB- defects. In the experiment, we used a metal reflective layer under the hBN flakes, filled with a transition dielectric layer in the middle, and adjusted the thickness of the dielectric layer to achieve the best coupling between RDC and spin defects in hBN. A remarkable 11-fold enhancement in the fluorescence intensity of VB- spin defects in hBN flakes can be achieved. By designing the metal layer into a waveguide structure, high-contrast optically detected magnetic resonance (ODMR) signal (∼21%) can be obtained. The oxide layer of the RDC can be used as the integrated material to implement secondary processing of micro-nano photonic devices, which means that it can be combined with other enhancement structures to achieve stronger enhancement. This work has guiding significance for realizing the on-chip integration of spin defects in two-dimensional materials.

Genetic characterization of duck hepatitis B viruses from Anhui Province, China.

Duck hepatitis B virus (DHBV) infection model was frequently used as the experimental model for human hepatitis B virus (HBV) research. In order to decipher the genetic characteristics of DHBVs from Anhui province of China, 120 duck liver tissue samples were collected and subjected to PCR screening, and 28 samples were detected as DHBV positive. Subsequently, five DHBV-positive samples were selected for genome-wide amplification and a comprehensive analysis. Comparative analysis of complete genome sequences using the MegAlign program showed that five strains of DHBVs shared 94.5-96.3% with each other and 93.2-98.7% with other reference strains in GenBank. The phylogenetic analysis showed that all five DHBV strains belonged to the evolutionary branch of "Chinese DHBV" isolates or DHBV-2. Importantly, three potential intra-genotypic recombination events, between strains AAU-6 and Guilin, strains AAU-1 and GD3, and strains AAU-6 and AAU-1, were respectively found using the RDP and SimPlot softwares and considered the first report in avihepadnaviruses. These results not only improve our understanding for molecular prevalence status of DHBV among ducks, but also provide a reference for recombination mechanism of HBV.

Preparation of multiphoton high-dimensional GHZ states.

The physics associated with multipartite high-dimensional entanglement is different from that of multipartite two-dimensional entanglement. Therefore, preparing multipartite high-dimensional entanglements with linear optics is challenging. This study proposes a preparation protocol of multiphoton GHZ state with arbitrary dimensions for optical systems. Auxiliary entanglements realize a high-dimensional entanglement gate to connect the high-dimensional entangled pairs to a multipartite high-dimensional GHZ state. Specifically, we use the path degrees of freedom of photons to prepare a four-partite, three-dimensional GHZ state. Our method can be extended to other degrees of freedom to generate arbitrary GHZ entanglements in any dimension.

Observation of Non-Markovian Evolution of Einstein-Podolsky-Rosen Steering.

Einstein-Podolsky-Rosen (EPR) steering is a type of characteristic nonlocal correlation and provides an important resource in quantum information tasks, especially in view of its asymmetric property. Although plenty of works on EPR steering have been reported, the study of non-Markovian evolution of EPR steering, in which the interactions between the quantum system and surrounding environment are taken into consideration, still lacks intuitive experimental evidence. Here, we experimentally observe the non-Markovian evolution of EPR steering including its sudden death and revival processes, during which the degree of memory effect plays a key role in the recovery of steering. Additionally, a strict unsteerable feature is sufficiently verified during the non-Markovian evolution within multisetting measurements. This Letter, revealing the whole evolution of EPR steering under the non-Markovian process, provides incisive insight into the applications of EPR steering in quantum open systems.

Experimental Test of High-Dimensional Quantum Contextuality Based on Contextuality Concentration.

Contextuality is a distinctive feature of quantum theory and a fundamental resource for quantum computation. However, existing examples of contextuality in high-dimensional systems lack the necessary robustness required in experiments. Here, we address this problem by identifying a family of noncontextuality inequalities whose maximum quantum violation grows with the dimension of the system. At first glance, this contextuality is the single-system version of multipartite Bell nonlocality taken to an extreme form. What is interesting is that the single-system version achieves the same degree of contextuality but uses a Hilbert space of lower dimension. That is, contextuality "concentrates" as the degree of contextuality per dimension increases. We show the practicality of this result by presenting an experimental test of contextuality in a seven-dimensional system. By simulating sequences of quantum ideal measurements with destructive measurements and repreparation in an all-optical setup, we report a violation of 68.7 standard deviations of the simplest case of the noncontextuality inequalities identified. Our results advance the investigation of high-dimensional contextuality, its connection to the Clifford algebra, and its role in quantum computation.

Implementing quantum dimensionality reduction for non-Markovian stochastic simulation.

Complex systems are embedded in our everyday experience. Stochastic modelling enables us to understand and predict the behaviour of such systems, cementing its utility across the quantitative sciences. Accurate models of highly non-Markovian processes - where the future behaviour depends on events that happened far in the past - must track copious amounts of information about past observations, requiring high-dimensional memories. Quantum technologies can ameliorate this cost, allowing models of the same processes with lower memory dimension than corresponding classical models. Here we implement such memory-efficient quantum models for a family of non-Markovian processes using a photonic setup. We show that with a single qubit of memory our implemented quantum models can attain higher precision than possible with any classical model of the same memory dimension. This heralds a key step towards applying quantum technologies in complex systems modelling.

Plasmonic-Enhanced Bright Single Spin Defects in Silicon Carbide Membranes.

Optically addressable spin defects in silicon carbide (SiC) have emerged as attractable platforms for various quantum technologies. However, the low photon count rate significantly limits their applications. We strongly enhanced the brightness by 7 times and spin-control strength by 14 times of single divacancy defects in 4H-SiC membranes using a surface plasmon generated by gold film coplanar waveguides. The mechanism of the plasmonic-enhanced effect is further studied by tuning the distance between single defects and the surface of the gold film. A three-energy-level model is used to determine the corresponding transition rates consistent with the enhanced brightness of single defects. Lifetime measurements also verified the coupling between defects and surface plasmons. Our scheme is low-cost, without complicated microfabrication and delicate structures, which is applicable for other spin defects in different materials. This work would promote developing spin-defect-based quantum applications in mature SiC materials.

Coherent control of an ultrabright single spin in hexagonal boron nitride at room temperature.

Hexagonal boron nitride (hBN) is a remarkable two-dimensional (2D) material that hosts solid-state spins and has great potential to be used in quantum information applications, including quantum networks. However, in this application, both the optical and spin properties are crucial for single spins but have not yet been discovered simultaneously for hBN spins. Here, we realize an efficient method for arraying and isolating the single defects of hBN and use this method to discover a new spin defect with a high probability of 85%. This single defect exhibits outstanding optical properties and an optically controllable spin, as indicated by the observed significant Rabi oscillation and Hahn echo experiments at room temperature. First principles calculations indicate that complexes of carbon and oxygen dopants may be the origin of the single spin defects. This provides a possibility for further addressing spins that can be optically controlled.

Experimental Examination of Entanglement Estimates.

Recently, a proper genuine multipartite entanglement measure has been found for three-qubit pure states [see Xie and Eberly, Phys. Rev. Lett. 127, 040403 (2021)PRLTAO0031-900710.1103/PhysRevLett.127.040403], but capturing useful entanglement measures for mixed states has remained an open challenge. So far, it requires not only a full tomography in experiments, but also huge calculational labor. A leading proposal was made by Gühne, Reimpell, and Werner [Phys. Rev. Lett. 98, 110502 (2007)PRLTAO0031-900710.1103/PhysRevLett.98.110502], who used expectation values of entanglement witnesses to describe a lower bound estimation of entanglement. We provide here an extension that also gives genuine upper bounds of entanglement. This advance requires only the expectation value of any Hermitian operator. Moreover, we identify a class of operators A_{1} that not only give good estimates, but also require a remarkably small number of experimental measurements. In this Letter, we define our approach and illustrate it by estimating entanglement measures for a number of pure and mixed states prepared in our recent experiments.

Certification of non-classicality in all links of a photonic star network without assuming quantum mechanics.

Networks composed of independent sources of entangled particles that connect distant users are a rapidly developing quantum technology and an increasingly promising test-bed for fundamental physics. Here we address the certification of their post-classical properties through demonstrations of full network nonlocality. Full network nonlocality goes beyond standard nonlocality in networks by falsifying any model in which at least one source is classical, even if all the other sources are limited only by the no-signaling principle. We report on the observation of full network nonlocality in a star-shaped network featuring three independent sources of photonic qubits and joint three-qubit entanglement-swapping measurements. Our results demonstrate that experimental observation of full network nonlocality beyond the bilocal scenario is possible with current technology.

Viral Metagenomic Analysis of the Fecal Samples in Domestic Dogs (Canis lupus familiaris).

Canine diarrhea is a common intestinal illness that is usually caused by viruses, bacteria, and parasites, and canine diarrhea may induce morbidity and mortality of domestic dogs if treated improperly. Recently, viral metagenomics was applied to investigate the signatures of the enteric virome in mammals. In this research, the characteristics of the gut virome in healthy dogs and dogs with diarrhea were analyzed and compared using viral metagenomics. The alpha diversity analysis indicated that the richness and diversity of the gut virome in the dogs with diarrhea were much higher than the healthy dogs, while the beta diversity analysis revealed that the gut virome of the two groups was quite different. At the family level, the predominant viruses in the canine gut virome were certified to be Microviridae, Parvoviridae, Siphoviridae, Inoviridae, Podoviridae, Myoviridae, and others. At the genus level, the predominant viruses in the canine gut virome were certified to be Protoparvovirus, Inovirus, Chlamydiamicrovirus, Lambdavirus, Dependoparvovirus, Lightbulbvirus, Kostyavirus, Punavirus, Lederbergvirus, Fibrovirus, Peduovirus, and others. However, the viral communities between the two groups differed significantly. The unique viral taxa identified in the healthy dogs group were Chlamydiamicrovirus and Lightbulbvirus, while the unique viral taxa identified in the dogs with diarrhea group were Inovirus, Protoparvovirus, Lambdavirus, Dependoparvovirus, Kostyavirus, Punavirus, and other viruses. Phylogenetic analysis based on the near-complete genome sequences showed that the CPV strains collected in this study together with other CPV Chinese isolates clustered into a separate branch, while the identified CAV-2 strain D5-8081 and AAV-5 strain AAV-D5 were both the first near-complete genome sequences in China. Moreover, the predicted bacterial hosts of phages were certified to be Campylobacter, Escherichia, Salmonella, Pseudomonas, Acinetobacter, Moraxella, Mediterraneibacter, and other commensal microbiota. In conclusion, the enteric virome of the healthy dogs group and the dogs with diarrhea group was investigated and compared using viral metagenomics, and the viral communities might influence canine health and disease by interacting with the commensal gut microbiome.