We investigate the behavior of geometric global quantum discord （GGQD） and concurrence （C） between half- spins of a mixed-three-spin （1/2, 1, 1/2） system with the Ising-XY model for which spins （1, 1/2） have t...We investigate the behavior of geometric global quantum discord （GGQD） and concurrence （C） between half- spins of a mixed-three-spin （1/2, 1, 1/2） system with the Ising-XY model for which spins （1, 1/2） have the Ising interaction and half-spins （1/2, 1/2） have both XY and the Dzyaloshinskii Moriya interactions together, under the decoherence action. A single-ion anisotropy property with coefficient ζ is assumed for the spin-integer. This system which includes an analytical Hamiltonian is considered at the front of an external homogeneous magnetic field B in thermal equilibrium. Finally, we compare GGQD and C and express some interesting phase flip reactions of the total quantum correlation and pairwise entanglement between spins （1/2, 1/2）. Generally, we conclude that the concurrence and GGQD have different behaviors under the phase flip channel.展开更多
Nonpharmaceutical interventions(NPIs),particularly contact tracing isolation and household quarantine,play a vital role in effectively bringing the Coronavirus Disease 2019(COVID-19)under control in China.The pairwise...Nonpharmaceutical interventions(NPIs),particularly contact tracing isolation and household quarantine,play a vital role in effectively bringing the Coronavirus Disease 2019(COVID-19)under control in China.The pairwise model,has an inherent advantage in characterizing those two NPIs than the classical well-mixed models.Therefore,in this paper,we devised a pairwise epidemic model with NPIs to analyze COVID-19 outbreak in China by using confirmed cases during February 3rde22nd,2020.By explicitly incorporating contact tracing isolation and family clusters caused by household quarantine,our model provided a good fit to the trajectory of COVID-19 infections.We calculated the reproduction number R=1.345(95%CI:1.230-1.460)for Hubei province and R=1.217(95%CI:1.207-1.227)for China(except Hubei).We also estimated the peak time of infections,the epidemic duration and the final size,which are basically consistent with real observation.We indicated by simulation that the traced high-risk contacts from incubated to susceptible decrease under NPIs,regardless of infected cases.The sensitivity analysis showed that reducing the exposure of the susceptible and increasing the clustering coefficient bolster COVID-19 control.With the enforcement of household quarantine,the reproduction number R and the epidemic prevalence declined effectively.Furthermore,we obtained the resumption time of work and production in China(except Hubei)on 10th March and in Hubei at the end of April 2020,respectively,which is broadly in line with the actual time.Our results may provide some potential lessons from China on the control of COVID-19 for other parts of the world.展开更多
Latent factor models have become a workhorse for a large number of recommender systems. While these sys- tems are built using ratings data, which is typically assumed static, the ability to incorporate different kinds...Latent factor models have become a workhorse for a large number of recommender systems. While these sys- tems are built using ratings data, which is typically assumed static, the ability to incorporate different kinds of subsequent user feedback is an important asset. For instance, the user might want to provide additional information to the system in order to improve his personal recommendations. To this end, we examine a novel scheme for efficiently learning （or refining） user parameters from such feedback. We propose a scheme where users are presented with a sequence of pair- wise preference questions： ＂Do you prefer item A over B？＂ User parameters are updated based on their response, and subsequent questions are chosen adaptively after incorporat- ing the feedback. We operate in a Bayesian framework and the choice of questions is based on an information gain cri- terion. We validate the scheme on the Netflix movie ratings data set and a proprietary television viewership data set. A user study and automated experiments validate our findings.展开更多
文摘We investigate the behavior of geometric global quantum discord （GGQD） and concurrence （C） between half- spins of a mixed-three-spin （1/2, 1, 1/2） system with the Ising-XY model for which spins （1, 1/2） have the Ising interaction and half-spins （1/2, 1/2） have both XY and the Dzyaloshinskii Moriya interactions together, under the decoherence action. A single-ion anisotropy property with coefficient ζ is assumed for the spin-integer. This system which includes an analytical Hamiltonian is considered at the front of an external homogeneous magnetic field B in thermal equilibrium. Finally, we compare GGQD and C and express some interesting phase flip reactions of the total quantum correlation and pairwise entanglement between spins （1/2, 1/2）. Generally, we conclude that the concurrence and GGQD have different behaviors under the phase flip channel.
基金This research was funded by the National Natural Science Foundation of China(grant numbers:61873154,12022113)the Shanxi Research Project on COVID-19 epidemic control and prevention(grant number:202003D31011/GZ).
文摘Nonpharmaceutical interventions(NPIs),particularly contact tracing isolation and household quarantine,play a vital role in effectively bringing the Coronavirus Disease 2019(COVID-19)under control in China.The pairwise model,has an inherent advantage in characterizing those two NPIs than the classical well-mixed models.Therefore,in this paper,we devised a pairwise epidemic model with NPIs to analyze COVID-19 outbreak in China by using confirmed cases during February 3rde22nd,2020.By explicitly incorporating contact tracing isolation and family clusters caused by household quarantine,our model provided a good fit to the trajectory of COVID-19 infections.We calculated the reproduction number R=1.345(95%CI:1.230-1.460)for Hubei province and R=1.217(95%CI:1.207-1.227)for China(except Hubei).We also estimated the peak time of infections,the epidemic duration and the final size,which are basically consistent with real observation.We indicated by simulation that the traced high-risk contacts from incubated to susceptible decrease under NPIs,regardless of infected cases.The sensitivity analysis showed that reducing the exposure of the susceptible and increasing the clustering coefficient bolster COVID-19 control.With the enforcement of household quarantine,the reproduction number R and the epidemic prevalence declined effectively.Furthermore,we obtained the resumption time of work and production in China(except Hubei)on 10th March and in Hubei at the end of April 2020,respectively,which is broadly in line with the actual time.Our results may provide some potential lessons from China on the control of COVID-19 for other parts of the world.
文摘Latent factor models have become a workhorse for a large number of recommender systems. While these sys- tems are built using ratings data, which is typically assumed static, the ability to incorporate different kinds of subsequent user feedback is an important asset. For instance, the user might want to provide additional information to the system in order to improve his personal recommendations. To this end, we examine a novel scheme for efficiently learning （or refining） user parameters from such feedback. We propose a scheme where users are presented with a sequence of pair- wise preference questions： ＂Do you prefer item A over B？＂ User parameters are updated based on their response, and subsequent questions are chosen adaptively after incorporat- ing the feedback. We operate in a Bayesian framework and the choice of questions is based on an information gain cri- terion. We validate the scheme on the Netflix movie ratings data set and a proprietary television viewership data set. A user study and automated experiments validate our findings.
