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The feature graph (Q-H graph) is the best way to intuitively and quantitatively reflect all features of the ventilation network. In this paper, an optimized adaptive genetic algorithm is proposed to solve the problem that rectangular blocks are cut in the process of drawing a Q-H diagram of a three-dimensional ventilation network. The algorithm adopts binary coding based on node sorting and mixed genetic coding based on integer coding. The formulas for calculating the adaptive crossover rate and mutation rate are designed, which can effectively generate new individuals and get rid of the search for local optimal values, ensuring the global optimal solution. Matlab was used to test the optimization effect of the Q-H graph; the results show that, for a complex ventilation network, the improved adaptive genetic algorithm can make the Q-H graph significantly reduce the number of rectangular pieces, which is divided, and make the Q-H graph have better effect to draw clearly and intuitively. [ABSTRACT FROM AUTHOR]

The moth-flame algorithm shows some shortcomings in solving the complex problem of optimization, such as insufficient population diversity and unbalanced search ability. In this paper, an IMFO (Improved Moth-Flame Optimization) algorithm is proposed to be applied in solving the optimization problem of function. First, cat chaotic mapping is used to generate the initial position of moth to improve the population diversity. Second, cosine inertia weight is introduced to balance the global and local search abilities of the algorithm. Third, the memory information in the particle swarm algorithm is introduced into the iterative process of the algorithm to speed up the convergence of the population. Finally, Gaussian mutation strategy is used in the current optimal solution to avoid the algorithm from falling into the local optimum. Simulation experiments are conducted on 11 benchmark test functions, compared with other improved MFO (Moth-Flame Optimization) algorithms and classical optimization algorithms. The results show that the IMFO has higher accuracy and stability in solving the above-mentioned test functions. The proposed algorithm is experimented and verified by optimizing the KELM (Kernel Extreme Learning Machine) in an engineering example and exhibits a better optimization performance. [ABSTRACT FROM AUTHOR]

Three-dimensional magnetic null points (3D nulls) are sites of dynamic activity in a wide range of naturally-occurring and laboratory plasma environments. The topology of a 3D null is defined by a two-dimensional fan plane of radial field lines and a one-dimensional, collimated spine axis. Here, we build on previous work that was able to form an extended 3D null topology using an assembly of circular conducting coils, with each coil carrying a constant current. While that magnetic field design decayed from the mathematically pure form away from the central null, this paper introduces an algorithm for modulating the current through each coil to form a more mathematically pure spine axis along the entirety of the coil assembly. By the method of solving an inverse problem, we demonstrate that unique currents exist for any arbitrary distribution of axially-aligned circular coils for creating an accurate spine axis in a 3D null topology. Tests of this algorithm are performed on spherical, cylindrical, and cone-shaped coil assemblies. Vector magnetic field mapping of these small-scale demonstrators verifies that an accurate spine axis is maintained along the entire central axis of the coil assemblies. The magnetic field accuracy is roughly maintained along the fan plane but decays strongly toward the outer extents of the coils. The inverse method presented here is not limited to 3D null topologies but can be adapted to match any theoretical form of the magnetic field along a single axis. [ABSTRACT FROM AUTHOR]

The improved particle filter (PF) based on the geometric center and likelihood estimation is proposed in order to solve the problem of particle dilution and degradation. In the resampling stage, the geometric center is used to resample the particles. The particles are filtered according to the distance between the particles and the geometric center, and then the particles are resampled. The resampled particles are composed of newborn particles and non-resampled particles. The former can help alleviate the degradation problem, while the latter can keep the diversity of the particle set. In order to ensure effectiveness of the PF, the positioning error threshold of the particle filter is introduced. In the phase of particle weighting calculation, in view of the problem of low accuracy and divergence of PF state estimation caused by non-stationary and non-Gaussian noise, it adopts non-Gaussian noise parameter estimation based on likelihood to approximately estimate the measurement noise instead of the Gaussian density function. The proposed model is applied to particle weight calculation to avoid particle degradation caused by Gaussian density function approximation. The simulation results show that, after the improved algorithm, the root-mean-square error is reduced to 0.085, the variance is reduced to 0.014, and the running time is shortened by 14.8% compared with the polynomial resampling algorithm, which can effectively alleviate particle degradation and dilution in the traditional PF algorithm, and the positioning accuracy is also improved. [ABSTRACT FROM AUTHOR]

In this paper we propose a new quadrature scheme for computing vibrational spectra and apply it, using a Lanczos algorithm, to CH3CN. All 12 coordinates are treated explicitly. We need only 157'419'523 quadrature points. It would not be possible to use a product Gauss grid because 33 853 318 889 472 product Gauss points would be required. The nonproduct quadrature we use is based on ideas of Smolyak, but they are extended so that they can be applied when one retains basis functions θn1(r1)...θnD(rD) that satisfy the condition α1n1 + ··· + αDnD <= b, where the αk are integers. We demonstrate that it is possible to exploit the structure of the grid to efficiently evaluate the matrix-vector products required to use the Lanczos algorithm. [ABSTRACT FROM AUTHOR]

Active noise control algorithms aimed at reducing Gaussian noise have been studied. However, the performance of these algorithms can deteriorate if impulsive noise or other non-Gaussian noise such as piling noise exists. To solve this problem, an algorithm named the filtered-x affine projection sign algorithm with a post-adaptive filter is proposed to reduce impulsive noise. The proposed algorithm is based on the filtered-x affine projection sign algorithm and the post-adaptive filter structure. In addition, an algorithm with a variable step size is proposed to improve the performance of the filtered-x affine projection sign algorithm with a post-adaptive filter by using a convex combination strategy. The fixed step size in the convex combination is replaced with a linear function of the ratio between the estimated error signal and the estimated desired signal. The detailed derivation processes of the proposed algorithms are given. The computational complexities are analyzed. Numerical simulations are carried out to demonstrate the performance of the proposed algorithms. The results illustrate that the proposed algorithms can effectively reduce impulsive noise. At the same time, the algorithm with a variable step size has better convergence performance than the filtered-x affine projection sign algorithm with a post-adaptive filter. [ABSTRACT FROM AUTHOR]

Quantum algorithms offer efficient solutions to computational problems that are expensive to solve classically. Publicly available quantum computers, such as those provided by IBM, can now be used to run small quantum circuits that execute quantum algorithms. However, these quantum computers are highly prone to noise. Here, we introduce important concepts of quantum circuit noise and connectivity that must be addressed to obtain reliable results on quantum computers. We utilize several examples to show how noise scales with circuit depth. We present Simon's algorithm, a quantum algorithm for solving a computational problem of the same name, explain how to implement it in IBM's Qiskit platform, and compare the results of running it both on a noiseless simulator and on physical hardware subject to noise. We discuss the impact of Qiskit's transpiler, which adapts ideal quantum circuits for physical hardware with limited connectivity between qubits. We show that even circuits of only a few qubits can have their success rate significantly reduced by quantum noise unless specific measures are taken to minimize its impact. [ABSTRACT FROM AUTHOR]

The multiple pulse train interference (MPTI) ranging system takes advantage of the high accuracy and absolute length measurement capability, but traditional scheme has a large measurement dead zone. In this Letter, we propose a MPTI ranging scheme based on chip-based soliton microcomb to achieve high-precision but no dead-zone measurement. The measurement optical path is improved to solve the problem of cross correlation interference fringe overlap, and a peak fitting algorithm is employed to further improve the measurement accuracy of the system. Using a commercial He–Ne interferometer, a 384 nm precision is obtained in 1.5 m distance measurements. Advantages of the simple optical path, high precision, and no measurement dead zone are expected to realize on-chip integration and provide a solution for precision measurement. [ABSTRACT FROM AUTHOR]

Properties of ferrofluid bilayer (modeled as a system of two planar layers separated by a h and each layer carrying a soft sphere dipolar liquid) are calculated in the framework of inhomogeneous Ornstein-Zernike equations with reference hypernetted chain closure (RHNC). The bridge functions are taken from a soft sphere (1/r12) reference system in the pressure-consistent closure approximation. In order to make the RHNC problem tractable, the angular dependence of the correlation functions is expanded into special orthogonal polynomials according to Lado. The resulting equations are solved using the Newton-GRMES algorithm as implemented in the publicdomain solver NITSOL. Orientational densities and pair distribution functions of dipoles are compared with Monte Carlo simulation results. A numerical algorithm for the Fourier-Hankel transform of any positive integer order on a uniform grid is presented. [ABSTRACT FROM AUTHOR]

Robot grasping has become a very hot research field so that the requirements for robot operation are getting higher and higher. In previous research studies, the use of traditional target detection algorithms for grasping is often very inefficient, and this article is dedicated to improving the deep reinforcement learning algorithm to improve the grasping efficiency and solve the problem of robots dealing with the impact of unknown disturbances on grasping. Using the characteristic that deep reinforcement learning actively explores the unknown environment, a Gaussian parameter Deep Deterministic Policy Gradient (Gaussian-DDPG) algorithm based on the Importance-Weighted Autoencoder (IWAE) is proposed to realize the robot's autonomous learning of the grasping task. Traditional coordinate positioning methods and deep learning methods have poor grasping effects for disturbed situations (such as the movement of the target object). The IWAE algorithm is used to compress the high-dimensional information of the original visual input to the hidden space and pass it to the deep reinforcement learning network as part of the state value. Based on the classic DDPG algorithm, it smoothly adds Gaussian parameters to improve the exploratory nature of the algorithm, dynamically sets the robot grasping space parameters to adapt to the workspace of multiple scales, and finally, realizes the accurate grasping of the robot. Relying on the possible position information deviation of the visual information, the control of the grasping position by the manipulator torque information is further optimized to improve the grasping efficiency of disturbed objects. [ABSTRACT FROM AUTHOR]

A recent problem [B. Gardas, J. Math. Phys. 52, 042104 (2011)] concerning an antilinear solution of the Riccati equation is solved. We also exemplify that a simplification of the Riccati equation, even under reasonable assumptions, can lead to a not equivalent equation. [ABSTRACT FROM AUTHOR]