5,889 research outputs found
Quantum Phases and Collective Excitations in Bose-Hubbard Models with Staggered Magnetic Flux
We study the quantum phases of a Bose-Hubbard model with staggered magnetic
flux in two dimensions, as has been realized recently [Aidelsburger {\it et
al.}, PRL, {\bf 107}, 255301 (2011)]. Within mean field theory, we show how the
structure of the condensates evolves from weak to strong coupling limit,
exhibiting a tricritical point at the Mott-superfluid transition. Non-trivial
topological structures (Dirac points) in the quasi-particle (hole) excitations
in the Mott state are found within random phase approximation and we discuss
how interaction modifies their structures. Excitation gap in the Mott state
closes at different points when approaching the superfluid states,
which is consistent with the findings of mean field theory.Comment: 5 pages, 3 figure
Quantum state tomography with disentanglement algorithm
In this work, we report on a novel quantum state reconstruction process based
on the disentanglement algorithm. Using variational quantum circuits, we
disentangle the quantum state to a product of computational zero states.
Inverse evolution of the zero states reconstructs the quantum state up to an
overall phase. By sequentially disentangling the qubit one by one, we reduce
the required measurements with only single qubit measurement. Demonstrations
with our proposal for the reconstruction of the random states are presented
where variational quantum circuit is optimized by disentangling process. To
facilitate experimental implementation, we also employ reinforcement learning
for quantum circuit design with limited discrete quantum gates. Our method is
universal and imposes no specific ansatz or constrain on the quantum state.Comment: 5 pages, 6 figure
3,19-Diacetyl-12-nitroÂmethyl-14-deoxyÂandrographolide
In the crystal of the title compound, C24H33NO9, interÂmolecular C—H⋯O hydrogen bonds link the molÂecules
MONITORING DATA PRODUCT QUALITY
The importance of data quality has been considered for many years and is well recognized among practitioners and researchers. A great deal of work has been done and most of the work to date fall under two main categories. One group of scientists has focused on mathematical and statistical model to work at the database layer to introduce constrain based mechanism to prevent data quality problems. Another group has focused on the management of the process of data generation. While the body of knowledge in the area is vast, the practical application of these approaches is still limited. One particular area which is still rarely considered in improving data quality is the development cycle of information system. Recognising this limitation and aiming to provide a practical-orient approach, we take a process centric view, and focus on preventing deficiencies during the IS design. In this paper we propose a process centric framework for data quality monitoring
AN APPROACH TO APPROXIMATE DIFFUSION PROCESSES IN SOCIAL NETWORKS
Social network analysis is concerned with the analysis of influence of an individual within a social network and how the influence diffuses through the network. It has been shown useful in business analytics. In this paper, we extend a nonlinear dynamical system that accurately models virus propagation in epidemiology to model information diffusion in social networks. Our approach can numerically calculate each node’s probability to get activated given the initial active set. It provides an alternative way of estimating the number of nodes reached by the initial target set in the diffusion process. We validate our approach by comparing its predicting performance with diffusion simulations. Using the number of nodes reached in the diffusion process as an influence measure, our results show that the proposed method can provide a way of identifying nontrivial nodes as influencer
Positivity constraints on the low-energy constants of the chiral pion-nucleon Lagrangian
Positivity constraints on the pion-nucleon scattering amplitude are derived
in this article with the help of general S-matrix arguments, such as
analyticity, crossing symmetry and unitarity, in the upper part of Mandelstam
triangle, R. Scanning inside the region R, the most stringent bounds on the
chiral low energy constants of the pion-nucleon Lagrangian are determined. When
just considering the central values of the fit results from covariant baryon
chiral perturbation theory using extended-on-mass-shell scheme, it is found
that these bounds are well respected numerically both at O(p^3) and O(p^4)
level. Nevertheless, when taking the errors into account, only the O(p^4)
bounds are obeyed in the full error interval, while the bounds on O(p^3) fits
are slightly violated. If one disregards loop contributions, the bounds always
fail in certain regions of R. Thus, at a given chiral order these terms are not
numerically negligible and one needs to consider all possible contributions,
i.e., both tree-level and loop diagrams. We have provided the constraints for
special points in R where the bounds are nearly optimal in terms of just a few
chiral couplings, which can be easily implemented and employed to constrain
future analyses. Some issues about calculations with an explicit Delta(1232)
resonance are also discussed.Comment: 15 pages, 13 eps figures, 2 table
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