There are two optic fibre properties in particular that obstruct the transfer over long distances in quantum communications. One of them is dispersion, which reduces the maximum bit rate. In classical communication wi...
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There are two optic fibre properties in particular that obstruct the transfer over long distances in quantum communications. One of them is dispersion, which reduces the maximum bit rate. In classical communication with modern highly purified fibres, dispersion is the major limiting factor. The other property is the material loss that causes fluctuations in addition to a general annihilation with distance of photons. It is believed that losses are the major limiting factor in quantum communication over long distances if the bit rate is not an issue. Of major interest in quantum communication is the photon source. It is therefore a high priority to develop methods for the determination of properties like initial temporal modes, repeatability, independence of sequentially emitted photons, etc., for a source emitting single photons in a given spatial mode. In the current paper we suggest that the source properties can be estimated using statistics of the run times of the photons. This requires that the fibre is modelled with sufficient accuracy. To simplify the analysis, it is assumed that the fibre losses can be neglected and that the photons are independent and identically generated. Energy detection in one spin state is employed, making the modelling scalar. The one photon initial temporal mode is found by maximizing a maximum-likelihood function based on running time statistics. Unfortunately, this optimization problem is, in general, not convex. However, for photon detection in the so-called asymptotic radiation zone, where the probability density can be determined to a sufficient degree with asymptotic methods, the optimization problem is convex. In the current paper, quantum tomography in fibres based on this convex optimization method is presented, and its generalization to more complicated situations like the introduction of losses in the modelling is discussed.
The goal of thiswork is to study the properties of the likelihood ratio ( LR) tests comparing base substitution models. These are the most widely used hypothesis tests. With mild regularity conditions, we show that th...
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The goal of thiswork is to study the properties of the likelihood ratio ( LR) tests comparing base substitution models. These are the most widely used hypothesis tests. With mild regularity conditions, we show that the asymptotic distribution of the LR statistic test, under the alternative hypothesis, is a non-central chi-square chi(2)(k) D) distribution. The asymptotic normal distribution of the LR test is proved when the sequence length S goes to infinity. We also propose a consistent estimator for the non-centrality parameter D. Through asymptotic theory and based on this consistent estimator for D, we propose a low computational cost estimator for the power of the LR test. The methodology is applied to 17 different gene sequences of the ECP-EDN family in primates.
This paper presents an image segmentation method that outlines fractured bones in an X-ray image of a patient's arm within cast materials, and displays the alignment between the fractured bones. The cast material ...
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ISBN:
(纸本)9781424407071
This paper presents an image segmentation method that outlines fractured bones in an X-ray image of a patient's arm within cast materials, and displays the alignment between the fractured bones. The cast material overlaying on the fractured bones creates extra noises to the X-ray image and provides challenges to the segmentation method. Our segmentation method aims on outlining the objects from a low contrast and high noise ratio of the X-ray images. A geodesic active contour model with global constraints is applied to this segmentation task. A prior shape is collected and embedded into the active contour model as a global constraint. A maximum-likelihood function is derived and used as a feedback system for each evolving process to a decision making procedure. Mutual Information is employed to measure the difference or the likelihood between the prior shape and the evolving curve. Experimental results show that the method produces the outlines of the fractured bones on the low contrast X-ray images robustly and accurately. The computation of our segmentation method is fast and efficient.
We propose a class of complex population dynamic models that combines new time-varying parameters and second-order time lags for describing univariate ecological time series data. The Kalman filter and likelihood func...
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We propose a class of complex population dynamic models that combines new time-varying parameters and second-order time lags for describing univariate ecological time series data. The Kalman filter and likelihoodfunction were used to estimate parameters of all models in the class for 31 data sets, and Schwarz's information criterion (SIC) was used to select the best model for each data set. Using the SIC method, models containing density-dependent processes were selected for 23 of the 31 cases examined, while models containing complex density-dependent processes were selected in 19 of these 23 density dependence cases. The density-dependent models identified by SIC had various linear or nonlinear forms, suggesting Variable patterns of population regulation in nature. Population dynamics may combine density-dependent, inversely density-dependent, and density-independent processes, which may operate at different times and under different density ranges. These results suggest that our approach offers an advance for modeling complex population dynamics, discovering complex regulation processes, and estimating the distribution of extinction times in changing environments.
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