Equation of motion for multiqubit entanglement in multiple independent noisy channels

We investigate the possibility and conditions to factorize the entanglement evolution of a multiqubit system passing through multi-sided noisy channels. By means of a lower bound of concurrence (LBC) as entanglement measure, we derive an explicit formula of LBC evolution of the N-qubit generalized Greenberger-Horne-Zeilinger (GGHZ) state under some typical noisy channels, based on which two kinds of factorizing conditions for the LBC evolution are presented. In this case, the time-dependent LBC can be determined by a product of initial LBC of the system and the LBC evolution of a maximally entangled GGHZ state under the same multi-sided noisy channels. We analyze the realistic situations where these two kinds of factorizing conditions can be satisfied. In addition, we also discuss the dependence of entanglement robustness on the number of the qubits and that of the noisy channels.Comment: 14 page

(Z)-N-(3-Nicotinoyl-1,3-thia­zolidin-2-yl­idene)cyanamide

In the title compound, C10H8N4OS, the dihedral angle between the pyridine and thia­zolidine rings is 52.5 (5)°. Inter­molecular C—H⋯N inter­actions help to stabilize the crystal structure

(1H-1,2,4-Triazol-1-yl)methyl 2-(2,4-dichloro­phen­oxy)acetate

In the title compound, C11H9Cl2N3O3, the triazole and benzene rings are roughly parallel to one another [dihedral angle = 4.99 (2)°] because the C—O—C—C—O chain that links the two rings is folded [O—C—C—O = 8.60 (2)°] rather than fully extended. In the crystal, weak inter­molecular C—H⋯N and C—H⋯O inter­actions are present, and π–π inter­actions are indicated by the short distances [3.749 (3) Å] between the centroids of the triazole and benzene rings

A unified theory for bubble dynamics

In this work, we established a novel theory for the dynamics of oscillating bubbles such as cavitation bubbles, underwater explosion bubbles, and air bubbles. For the first time, we proposed bubble dynamics equations that can simultaneously take into consideration the effects of boundaries, bubble interaction, ambient flow field, gravity, bubble migration, fluid compressibility, viscosity, and surface tension while maintaining a unified and elegant mathematical form. The present theory unifies different classical bubble equations such as the Rayleigh-Plesset equation, the Gilmore equation, and the Keller-Miksis equation. Furthermore, we validated the theory with experimental data of bubbles with a variety in scales, sources, boundaries, and ambient conditions and showed the advantages of our theory over the classical theoretical models, followed by a discussion on the applicability of the present theory based on a comparison to simulation results with different numerical methods. Finally, as a demonstration of the potential of our theory, we modeled the complex multi-cycle bubble interaction with wide ranges of energy and phase differences and gained new physical insights into inter-bubble energy transfer and coupling of bubble-induced pressure waves

Deep learning based real-time facial mask detection and crowd monitoring

During the Covid pandemic, the importance of wearing mask has been noted globally. Additionally, crowded human clusters facilitated the transmission of the virus, which brings up the need for new systems for monitoring such situations. To address such issues, this research proposes an object recognition visual system based on deep learning to monitor the wearing of masks in a certain space and the control of the number of people indoors as an important tool during an epidemic. This research mainly investigates two types of identification. The first is to monitor whether people entering the site wear a mask at the entrance and exit of the field, and the second is to count the number of people entering a specific area. Experimental results show that by utilising the visual sensor, it is possible to detect and identify the people who frequently enter and exit in real-time. An advanced transfer learning approach has been employed to achieve the best discrimination performance. The actual training results prove that the migration learning Mask R-CNN algorithm produced by this method and the original Mask R-CNN algorithm have increased the mAP by 3%, reaching a mAP of 96%. In addition, the accuracy of the random sampling and identification in actual scenes has reached 92.1%. The developed deep learning vision system has an enhanced identification ability for the verification and analysis of actual scenes and has great application potential

Ethyl 1-(4-meth­oxy­benz­yl)-3-p-tolyl-1H-pyrazole-5-carboxyl­ate

In the title compound, C21H22N2O3, the pyrazole ring makes dihedral angles of 12.93 (8) and 69.38 (8)°, respectively, with the tolyl and meth­oxy­benzyl rings

A new 3-D multi-fluid model with the application in bubble dynamics using the adaptive mesh refinement

Violent pulsating bubbles behave diversely in different circumstances. It is a multi-scale problem in both space and time. In 3-D problems, the numerical simulation is usually too expensive to implement in practice with a fixed grid. In this paper, a 3-D multi-fluid model is established based on the Eulerian finite element method and the adaptive mesh refinement technique to investigate the bubble evolution and its toroidal motion near a solid vertical wall. The mixture formula for compressible multi-fluid flow is adopted to ensure conservativeness. By means of the block-based adaptive mesh refinement, the accuracy and the efficiency of the simulation are well balanced. The present model is validated by comparing the results with an underwater explosion experiment and the existing numerical results. The results agree well and a fast convergence is observed. Then, several cases with different buoyancy parameters are simulated, and the toroidal bubble motion and their pressure load on the solid wall are analyzed. The bubble's motion exhibits complex physics, such as the formation of the crescent-shaped bubble, the air cushion effect during the jet penetration, and the nonlinear relationship between the jet impact pressure and the angle between the jet and the opposite bubble surface

Energy dissipation of pulsating bubbles in compressible fluids using the Eulerian finite-element method

Energy dissipation mechanisms of bubble pulsation in compressible fluids have always been a significant aspect of research into bubble dynamics. In this paper, bubble dynamics in compressible fluids are investigated numerically with the Eulerian finite-element method (EFEM), and the energy dissipation due to the wave effects of the compressible surrounding fluid is analyzed. The present model is validated by comparing with experimental results. Results from both the simulation and experiment show that bubble fragmentation also contributes to the energy dissipation, which has seldom been discussed before. It is also shown that the initial discontinuity is significant to the energy dissipation which is non-trivial to simulate in 1-dimensional bubble dynamics equations like the Gilmore equation. Then, the relationship between dissipated energy and bubble maximum radii in adjacent pulsating cycles is formulated to quantitatively evaluate the energy dissipation during a pulsating cycle. At last, based on the linearized theory of the energy conservation of the bubble system, a new non-dimensional parameter M a is modified from the Mach number to represent the energy dissipation due to wave effects. With simulation and discussion on cases with different initial pressure and sound speed, it is found that the dissipated energy is related linearly to M a, which can be used to predict the energy dissipation of a new case