Exact dynamics of single-qubit-gate fidelities under the measurement-based quantum computation scheme

Measurement-based quantum computation is an efficient model to perform universal computation. Nevertheless, theoretical questions have been raised, mainly with respect to realistic noise conditions. In order to shed some light on this issue, we evaluate the exact dynamics of some single-qubit-gate fidelities using the measurement-based quantum computation scheme when the qubits which are used as a resource interact with a common dephasing environment. We report a necessary condition for the fidelity dynamics of a general pure N-qubit state, interacting with this type of error channel, to present an oscillatory behavior, and we show that for the initial canonical cluster state, the fidelity oscillates as a function of time. This state fidelity oscillatory behavior brings significant variations to the values of the computational results of a generic gate acting on that state depending on the instants we choose to apply our set of projective measurements. As we shall see, considering some specific gates that are frequently found in the literature, the fast application of the set of projective measurements does not necessarily imply high gate fidelity, and likewise the slow application thereof does not necessarily imply low gate fidelity. Our condition for the occurrence of the fidelity oscillatory behavior shows that the oscillation presented by the cluster state is due exclusively to its initial geometry. Other states that can be used as resources for measurement-based quantum computation can present the same initial geometrical condition. Therefore, it is very important for the present scheme to know when the fidelity of a particular resource state will oscillate in time and, if this is the case, what are the best times to perform the measurements.

A novel self consistent calculation approach for the capacitance-voltage characteristics of semiconductor quantum wire transistors based on a split-gate configuration

Purpose - The purpose of this paper is to develop an efficient numerical algorithm for the self-consistent solution of Schrodinger and Poisson equations in one-dimensional systems. The goal is to compute the charge-control and capacitance-voltage characteristics of quantum wire transistors. Design/methodology/approach - The paper presents a numerical formulation employing a non-uniform finite difference discretization scheme, in which the wavefunctions and electronic energy levels are obtained by solving the Schrodinger equation through the split-operator method while a relaxation method in the FTCS scheme ("Forward Time Centered Space") is used to solve the two-dimensional Poisson equation. Findings - The numerical model is validated by taking previously published results as a benchmark and then applying them to yield the charge-control characteristics and the capacitance-voltage relationship for a split-gate quantum wire device. Originality/value - The paper helps to fulfill the need for C-V models of quantum wire device. To do so, the authors implemented a straightforward calculation method for the two-dimensional electronic carrier density n(x,y). The formulation reduces the computational procedure to a much simpler problem, similar to the one-dimensional quantization case, significantly diminishing running time.

Reproductive biology and species geographical distribution in the Melastomataceae: a survey based on New World taxa

Apomictic plants are less dependent on pollinator services and able to occupy more diverse habitats than sexual species. However, such assumptions are based on temperate species, and comparable evaluation for species-rich Neotropical taxa is lacking. In this context, the Melastomataceae is a predominantly Neotropical angiosperm family with many apomictic species, which is common in the Campos Rupestres, endemism-rich vegetation on rocky outcrops in central Brazil. In this study, the breeding system of some Campo Rupestre Melastomataceae was evaluated, and breeding system studies for New World species were surveyed to test the hypothesis that apomixis is associated with wide distributions, whilst sexual species have more restricted areas. The breeding systems of 20 Campo Rupestre Melastomataceae were studied using hand pollinations and pollen-tube growth analysis. In addition, breeding system information was compiled for 124 New World species of Melastomataceae with either wide (1000 km) or restricted distributions. Most (80 ) of the Campo Rupestre species studied were self-compatible. Self-incompatibility in Microlicia viminalis was associated with pollen-tube arrest in the style, as described for other Melastomataceae, but most self-incompatible species analysed showed pollen-tube growth to the ovary irrespective of pollination treatment. Apomictic species showed lower pollen viability and were less frequent among the Campo Rupestre plants. Among the New World species compiled, 43 were apomictic and 77 sexual (24 self-incompatible and 53 self-compatible). Most apomictic (86 ) and self-incompatible species (71 ) presented wide distributions, whilst restricted distributions predominate only among the self-compatible ones (53 ). Self-compatibility and dependence on biotic pollination were characteristic of Campo Rupestre and narrowly distributed New World Melastomataceae species, whilst apomictics are widely distributed. This is, to a certain extent, similar to the geographical parthenogenesis pattern of temperate apomictics.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Multiobjective Biogeography-Based Optimization Based on Predator-Prey Approach

Biogeography is the science that studies the geographical distribution and the migration of species in an ecosystem. Biogeography-based optimization (BBO) is a recently developed global optimization algorithm as a generalization of biogeography to evolutionary algorithm and has shown its ability to solve complex optimization problems. BBO employs a migration operator to share information between the problem solutions. The problem solutions are identified as habitat, and the sharing of features is called migration. In this paper, a multiobjective BBO, combined with a predator-prey (PPBBO) approach, is proposed and validated in the constrained design of a brushless dc wheel motor. The results demonstrated that the proposed PPBBO approach converged to promising solutions in terms of quality and dominance when compared with the classical BBO in a multiobjective version.