Multi-Objective Optimization Algorithm for Grouping Decision Variables Based on Extreme Point Pareto Frontier

The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently.

Average fidelity estimation of twirled noisy quantum channel using unitary 2t-design

We propose a method to estimate the average fidelity using the unitary 2t-design of a twirled noisy channel, which is suitable for large-scale quantum circuits. Compared with the unitary 2-design in randomized benchmarking, the unitary2t-design for the twirling of noisy channels is more flexible in construction and can provide more information. In addition,we prove that the proposed method provides an efficient and reliable estimation of the average fidelity in benchmarking multistage quantum gates and estimating the weakly gate-and time-dependent noise. For time-dependent noise, we provide a scheme of moment superoperator to analyze the noise in different experiments. In particular, we give a lower bound on the average fidelity of a channel with imperfect implementation of benchmarking and state preparation and measurement errors(SPAM).

Ordered quasi-two-dimensional structure of nanoparticles in semiflexible ring polymer brushes under compression

在压缩下面的戒指聚合物刷子的一个纹理粗糙的祷告春天模型的分子的动力学模拟被介绍。灵活聚合物刷子在压缩期间总是是混乱的，而 semiflexible 聚合物刷子趋于在足够地强壮的压缩下面被订。进一步， semiflexible 聚合物刷子的聚合物单体密度在刷子表面附近很高，导致表面附近的免费精力的山峰价值。因此，当 nanoparticles 在 semiflexible 戒指聚合物刷子被压缩时，他们趋于展出在刷子表面之间的仔细包装的单个层的结构，刺不进的墙，和伪二维的订的结构接近刷子表面在强壮的压缩下面被形成。这些调查结果提供一条新途径给设计应答的应用。