Chinese Organization Name Recognition Using Chunk Analysis

PACLIC 20 / Wuhan, China / 1-3 November, 200

Employing Incremental Outlines for OpenStreetMap Data Updating

The updating of changing information plays a significant role in ensuring the quality of OpenStreetMap, which is usually completed by mapping the whole changing objects with a high degree of uncertainty. The incremental object-based approach provides opportunities to reduce the unreliability of data, while challenges of data inaccuracy and redundancy remain. This paper provides an incremental outline-based approach for OpenStreetMap data updating to solve this issue. First, incremental outlines are delineated from the changed objects and distinguished through a spatial classification. Then, attribute information corresponding to incremental outlines is proposed to assist in describing the physical changes. Finally, through a geometric calculation based on both the spatial and attribute information, updating operations are constructed with a variety of rules to activate the data updating process. The proposed approach was verified by updating an area in the OpenStreetMap datasets. The result shows that the incremental outline-based updating approach can reduce both the time and storage costs compared to incremental objects and further improve data quality in the updating process. Document type: Articl

Observation of entanglement negativity transition of pseudo-random mixed states

Multipartite entanglement is a key resource for quantum computation. It is expected theoretically that entanglement transition may happen for multipartite random quantum states, however, which is still absent experimentally. Here, we report the observation of entanglement transition quantified by negativity using a fully connected 20-qubit superconducting processor. We implement multi-layer pseudo-random circuits to generate pseudo-random pure states of 7 to 15 qubits. Then, we investigate negativity spectra of reduced density matrices obtained by quantum state tomography for 6 qubits.Three different phases can be identified by calculating logarithmic negativities based on the negativity spectra. We observe the phase transitions by changing the sizes of environment and subsystems. The randomness of our circuits can be also characterized by quantifying the distance between the distribution of output bit-string probabilities and Porter-Thomas distribution. Our simulator provides a powerful tool to generate random states and understand the entanglement structure for multipartite quantum systems

Demonstration of Maxwell Demon-assistant Einstein-Podolsky-Rosen Steering via Superconducting Quantum Processor

The concept of Maxwell demon plays an essential role in connecting thermodynamics and information theory, while entanglement and non-locality are fundamental features of quantum theory. Given the rapid advancements in the field of quantum information science, there is a growing interest and significance in investigating the connection between Maxwell demon and quantum correlation. The majority of research endeavors thus far have been directed towards the extraction of work from quantum correlation through the utilization of Maxwell demon. Recently, a novel concept called Maxwell demon-assistant Einstein-Podolsky-Rosen (EPR) steering has been proposed, which suggests that it is possible to simulate quantum correlation by doing work. This seemingly counterintuitive conclusion is attributed to the fact that Alice and Bob need classical communication during EPR steering task, a requirement that does not apply in the Bell test. In this study, we demonstrate Maxwell demon-assistant EPR steering with superconducting quantum circuits. By compiling and optimizing a quantum circuit to be implemented on a 2D superconducting chip, we were able to achieve a steering parameter of $S_{2} = 0.770 \pm 0.005$ in the case of two measurement settings, which surpasses the classical bound of $1/\sqrt{2}$ by 12.6 standard deviations. In addition, experimental observations have revealed a linear correlation between the non-locality demonstrated in EPR steering and the work done by the demon. Considering the errors in practical operation, the experimental results are highly consistent with theoretical predictions. Our findings not only suggest the presence of a Maxwell demon loophole in the EPR steering, but also contribute to a deeper comprehension of the interplay between quantum correlation, information theory, and thermodynamics.Comment: Comments are welcome

On-chip black hole: Hawking radiation and curved spacetime in a superconducting quantum circuit with tunable couplers

Hawking radiation is one of quantum features of a black hole, which can be understood as a quantum tunneling across the event horizon of the black hole, but it is quite difficult to directly observe the Hawking radiation of an astrophysical black hole. Remarkable experiments of analogue black holes on various platforms have been performed. However, Hawking radiation and its quantum nature such as entanglement have not been well tested due to the experimental challenges in accurately constructing curved spacetime and precisely measuring the thermal spectrum. Based on the recent architecture breakthrough of tunable couplers for superconducting processor, we realize experimentally an analogue black hole using our new developed chip with a chain of 10 superconducting transmon qubits with interactions mediated by 9 transmon-type tunable couplers. By developing efficient techniques to engineer the couplings between qubits via tuning couplers, we realize both the flat and curved spacetime backgrounds. The quantum walks of quasi-particle in the curved spacetime reflect the gravitational effect around the black hole, resulting in the behavior of Hawking radiation. By virtue of the state tomography measurement of all 7 qubits outside the analogue event horizon, we show that Hawking radiation can be verified. In addition, an entangled pair is prepared inside the horizon and the dynamics of entanglement in the curved spacetime is directly measured. Our results would stimulate more interests to explore information paradox, entropy and other related features of black holes using programmable superconducting processor with tunable couplers.Comment: modified manuscripts, 7 pages, 4 figures (main text) + 12 pages (supplementary information

Geographic Variation Did Not Affect the Predictive Power of Salivary Microbiota for Caries in Children With Mixed Dentition

Dental caries is one of the most prevalent chronic oral diseases, affecting approximately half of children worldwide. The microbial composition of dental caries may depend on age, oral health, diet, and geography, yet the effect of geography on these microbiomes is largely underexplored. Here, we profiled and compared saliva microbiota from 130 individuals aged 6 to 8 years old, representing both healthy children (H group) and children with caries-affected (C group) from two geographical regions of China: a northern city (Qingdao group) and a southern city (Guangzhou group). First, the saliva microbiota exhibited profound differences in diversity and composition between the C and H groups. The caries microbiota featured a lower alpha diversity and more variable community structure than the healthy microbiota. Furthermore, the relative abundance of several genera (e.g., Lactobacillus, Gemella, Cryptobacterium and Mitsuokella) was significantly higher in the C group than in the H group (p<0.05). Next, geography dominated over disease status in shaping salivary microbiota, and a wide array of salivary bacteria was highly predictive of the individuals’ city of origin. Finally, we built a universal diagnostic model based on 14 bacterial species, which can diagnose caries with 87% (AUC=86.00%) and 85% (AUC=91.02%) accuracy within each city and 83% accuracy across cities (AUC=92.17%). Although the detection rate of Streptococcus mutans in populations is not very high, it could be regarded as a single biomarker to diagnose caries with decent accuracy. These findings demonstrated that despite the large effect size of geography, a universal model based on salivary microbiota has the potential to diagnose caries across the Chinese child population