Perspectives for a mixed two-qubit system with binomial quantum states

The problem of the relationship between entanglement and two-qubit systems in which it is embedded is central to the quantum information theory. This paper suggests that the concurrence hierarchy as an entanglement measure provides an alternative view of how to think about this problem. We consider mixed states of two qubits and obtain an exact solution of the time-dependent master equation that describes the evolution of two two-level qubits (or atoms) within a perfect cavity for the case of multiphoton transition. We consider the situation for which the field may start from a binomial state. Employing this solution, the significant features of the entanglement when a second qubit is weakly coupled to the field and becomes entangled with the first qubit, is investigated. We also describe the response of the atomic system as it varies between the Rabi oscillations and the collapse-revival mode and investigate the atomic inversion and the Q-function. We identify and numerically demonstrate the region of parameters where significantly large entanglement can be obtained. Most interestingly, it is shown that features of the entanglement is influenced significantly when the multi-photon process is involved. Finally, we obtain illustrative examples of some novel aspects of this system and show how the off-resonant case can sensitize entanglement to the role of initial state setting.Comment: 18 pages, 9 figure

Comparative Study between the Performances of Nile Tilapia Oreochromisniloticus during and Out of the Normal Spawning Season

During the production season (2010-2011), this work was carried out at a commercial tilapia hatchery in Motobas, Kafr El-Sheikh Governorate- Egypt. Two experiments were managed using the same design to make a comparison between spawning of Nile tilapia Oreochromisniloticusbroodstock off-season (the winter) and on-season (the summer). The two experiments were tested by studying the effects of using feed additive (Nuvisol hatch P® 0.1%), different broodstocksizes (350, 200, 150 and mixed up to 250 g/fish) and stocking densities (50, 55, 60 female/pond-24m2) on growth performance, feed utilization, reproductive performance and economical profitability parameters of Nile tilapia, O.niloticus spawned in the summer and in the winter. Comparing the results of the economic analysis of the two experiments showed that the total production of Nile tilapia fry per each spawning pond, 24 square meters, is 28,090 within the natural spawning season, an increase of 2.23% from that was spawning outside the normal season (27478 fry). Though total revenue and net income under hatchery conditions in the out off-season (February 2010) much higher than that in natural spawning season (April 2011) by 22.01%. This is of course due to the price of tilapia fry in the winter months is higher than the summer to supply shortages in winter and increased demand at the same time. This is due to the farmers need to start the growing season early, March/April, in order to harvest their fish before temperatures drop in the next winter, which adversely affect the life of the fish

Brain Tumors Detection using Computed Tomography Scans Based on Deep Neural Networks

Brain tumors are one of the deadliest diseases, with numerous implications on human health. A brain tumor is an abnormal cell mass or growth in or around the brain. They are not all cancerous, as they might be benign or malignant. Doctors use a variety of diagnostic techniques to assess the presence of a benign or malignant brain tumor, as well as to estimate its size, location, and growth rate. The proper diagnostic modality is used to provide a complete view of the brain to detect any abnormalities. A computed tomographic (CT) scan of the brain shall be done to check the abnormalities. The benefits of CT scans include accurate detection of calcification, hemorrhage, and bone detail, as well as low cost compared to magnetic resonance imaging (MRI). Therefore, we examine a proposed CT-based detection method to determine whether brain tumor is present or not. The proposed method works on a CT image dataset that collected from Mansoura University hospital. Different pre-trained models are used: VGG-16, ResNet-50, and MobileNet-V2. Comparing the results, that pre-train model MobileNet-V2, despite having the lowest number of parameters, yields better results. It gives an accuracy 97.6%, while its precision, recall, and F1-score values are 96%, 95%, and 96%, respectively

Quantitative aspects of entanglement in the optically driven quantum dots

We present a novel approach to look for the existence of maximum entanglement in a system of two identical quantum dots coupled by the Forster process and interacting with a classical laser field. Our approach is not only able to explain the existing treatments, but also provides further detailed insights into the coupled dynamics of quantum dots systems. The result demonstrates that there are two ways for generating maximum entangled states, one associated with far off-resonance interaction, and the other associated with the weak field limit. Moreover, it is shown that exciton decoherence results in the decay of entanglement.Comment: 13 pages, 4 figure