Chebyshev Polynomial Interpolation Research Articles

Surrogate Modeling of the Relative Entropy for Inverse Design Using Smolyak Sparse Grids.

Relative entropy minimization, a statistical-mechanics approach for finding potential energy functions that produce target structural ensembles, has proven to be a powerful strategy for the inverse design of nanoparticle self-assembly. For a given target structure, the gradient of the relative entropy with respect to the adjustable parameters of the potential energy function is computed by performing a simulation, and then these parameters are updated using iterative gradient-based optimization. Small parameter updates per iteration and many iterations can be required for numerical stability, but this incurs considerable computational expense because a new simulation must be performed to reevaluate the gradient at each iteration. Here, we investigate the use of surrogate modeling to decouple the process of minimizing the relative entropy from the computationally demanding process of determining its gradient. We approximate the relative-entropy gradient using Chebyshev polynomial interpolation on Smolyak sparse grids. Our approach potentially increases the robustness and computational efficiency of using the relative entropy for inverse design, primarily for physically informed potential energy functions that have a small number of adjustable parameters.

A collocation method based on roots of Chebyshev polynomial for solving Volterra integral equations of the second kind

This paper mainly studies numerical solution to the Volterra integral equation of the second kind. By using the roots of Chebyshev polynomial as collocation points, a new collocation method is proposed to solve the Volterra integral equation of the second kind. The proposed method firstly interpolates the product of the kernel function and the unknown solution at the roots of Chebyshev polynomial. Then, the Volterra integral equation is transformed into a system of linear algebra equations by properties of Chebyshev polynomials. Finally, the numerical solution of the Volterra integral equation is obtained by the Chebyshev polynomial interpolation. In addition, the error estimates of the proposed method are provided in a semi-posteriori sense; and numerical examples are given to show effectiveness of the proposed method.

Localized Chebyshev and MLS collocation methods for solving 2D steady state nonlocal diffusion and peridynamic equations

The localized Chebyshev collocation method and MLS collocation method are presented to obtain the solution of two-dimensional nonlocal diffusion and peridynamic equations. The Chebyshev polynomial and MLS interpolation techniques are used to construct shape functions in the frame of the collocation method. Low computational cost and high accuracy are the main advantages of these two methods for solving nonlocal diffusion and peridynamic equations. Several numerical examples are provided to show the validity and applicability of the proposed method with the regular and irregular domains. Numerical experiments indicate that the localized Chebyshev collocation method has high accuracy for nonlocal problems with continuous solutions. The MLS collocation method is more efficient and can maintain good behavior for problems with discontinuous solutions.

Accuracy improvement of the H-drive air-levitating wafer inspection stage based on error analysis and compensation

In order to improve the inspection precision of the H-drive air-bearing stage for wafer inspection, in this paper the geometric error of the stage is analyzed and compensated. The relationship between the positioning errors and error sources are initially modeled, and seven error components are identified that are closely related to the inspection accuracy. The most effective factor that affects the geometric error is identified by error sensitivity analysis. Then, the Spearman rank correlation method is applied to find the correlation between different error components, aiming at guiding the accuracy design and error compensation of the stage. Finally, different compensation methods, including the three-error curve interpolation method, the polynomial interpolation method, the Chebyshev polynomial interpolation method, and the B-spline interpolation method, are employed within the full range of the stage, and their results are compared. Simulation and experiment show that the B-spline interpolation method based on the error model has better compensation results. In addition, the research result is valuable for promoting wafer inspection accuracy and will greatly benefit the semiconductor industry.

An Adaptive Partition of Unity Method for Chebyshev Polynomial Interpolation

For a function that is analytic on and around an interval, Chebyshev polynomial interpolation provides spectral convergence. However, if the function has a singularity close to the interval, the rate of convergence is near one. In these cases splitting the interval and using piecewise interpolation can accelerate convergence. Chebfun includes a splitting mode that finds an optimal splitting through recursive bisection, but the result has no global smoothness unless conditions are imposed explicitly at the breakpoints. An alternative is to split the domain into overlapping intervals and use an infinitely smooth partition of unity to blend the local Chebyshev interpolants. A simple divide-and-conquer algorithm similar to Chebfun's splitting mode can be used to find an overlapping splitting adapted to features of the function. The algorithm implicitly constructs the partition of unity over the subdomains. This technique is applied to explicitly given functions as well as to the solutions of singularly pertur...

Reentry Trajectory Optimization for a Hypersonic Vehicle Based on an Improved Adaptive Fireworks Algorithm

Generation of optimal reentry trajectory for a hypersonic vehicle (HV) satisfying both boundary conditions and path constraints is a challenging task. As a relatively new swarm intelligent algorithm, an adaptive fireworks algorithm (AFWA) has exhibited promising performance on some optimization problems. However, with respect to the optimal reentry trajectory generation under constraints, the AFWA may fall into local optimum, since the individuals including fireworks and sparks are not well informed by the whole swarm. In this paper, we propose an improved AFWA to generate the optimal reentry trajectory under constraints. First, via the Chebyshev polynomial interpolation, the trajectory optimization problem with infinite dimensions is transformed to a nonlinear programming problem (NLP) with finite dimension, and the scope of angle of attack (AOA) is obtained by path constraints to reduce the difficulty of the optimization. To solve the problem, an improved AFWA with a new mutation strategy is developed, where the fireworks can learn from more individuals by the new mutation operator. This strategy significantly enhances the interactions between the fireworks and sparks and thus increases the diversity of population and improves the global search capability. Besides, a constraint-handling technique based on an adaptive penalty function and distance measure is developed to deal with multiple constraints. The numerical simulations of two reentry scenarios for HV demonstrate the validity and effectiveness of the proposed improved AFWA optimization method, when compared with other optimization methods.

Using Chebyshev polynomial interpolation to improve the computational efficiency of gravity models near an irregularly-shaped asteroid

In asteroid rendezvous missions, the dynamical environment near an asteroid’s surface should be made clear prior to launch of the mission. However, most asteroids have irregular shapes, which lower the efficiency of calculating their gravitational field by adopting the traditional polyhedral method. In this work, we propose a method to partition the space near an asteroid adaptively along three spherical coordinates and use Chebyshev polynomial interpolation to represent the gravitational acceleration in each cell. Moreover, we compare four different interpolation schemes to obtain the best precision with identical initial parameters. An error-adaptive octree division is combined to improve the interpolation precision near the surface. As an example, we take the typical irregularly-shaped near-Earth asteroid 4179 Toutatis to demonstrate the advantage of this method; as a result, we show that the efficiency can be increased by hundreds to thousands of times with our method. Our results indicate that this method can be applicable to other irregularly-shaped asteroids and can greatly improve the evaluation efficiency.

High-performance American option pricing

We develop a new high-performance spectral collocation method for the computation of American put and call option prices. The proposed algorithm involves a carefully posed Jacobi-Newton iteration for the optimal exercise boundary, aided by Gauss-Legendre quadrature and Chebyshev polynomial interpolation on a certain transformation of the boundary. The resulting scheme is straightforward to implement and converges at a speed several orders of magnitude faster than existing approaches. Computational effort depends on required accuracy; at precision levels similar to, say, those computed by a finite-difference grid with several hundred steps, the computational throughput of the algorithm in the Black-Scholes model is typically close to 100 000 option prices per second per CPU. For benchmarking purposes, Black-Scholes American option prices can generally be computed to ten or eleven significant digits in less than one-tenth of a second.

A New Method for Chebyshev Polynomial Interpolation Based on Cosine Transforms

Interpolation plays an important role in the areas of signal processing and applied mathematics. Among the various interpolation methods, those related to Chebyshev polynomial interpolation have received much interest recently. In this paper, we propose a new interpolation method using a type I discrete cosine transform (type I DCT) and the nonuniform roots of the second type of Chebyshev polynomials. In this method, the interpolation coefficients are derived using the type I DCT of the Chebyshev nonuniform sampling points. Simulations show the correctness of the proposed method, and a comparison of the proposed method with existing methods is also discussed in detail.

High Performance American Option Pricing

We develop a new high-performance spectral collocation method for the computation of American put and call option prices. The proposed algorithm involves a carefully posed Jacobi-Newton iteration for the optimal exercise boundary, aided by Gauss-Legendre quadrature and Chebyshev polynomial interpolation on a certain transformation of the boundary. The resulting scheme is straightforward to implement and converges at a speed several orders of magnitude faster than existing approaches. Computational effort depends on required accuracy; at precision levels similar to, say, those computed by finite difference grids with several hundred steps, the computational throughput of the algorithm in the Black-Scholes model is typically close to 100,000 option prices per second per CPU. For benchmarking purposes, Black-Scholes American option prices can generally be computed to at 10 or 11 significant digits in less than one-tenth of a second.

Attainability Analysis for Entry Vehicles Based on Differential Evolution

Attainable region provides crucial information on mission planning of entry vehicles. In order to obtain it, a series of nonlinear optimal control problems which have similar formulations are needed to be solved. However, it is difficult to compute due to severe nonlinearity of the dynamics and various constraints. In this paper, a novel method is established to generate the attainable region at the end of the entry phase. It utilizes the parallel feature of differential evolution (DE) and the high accuracy of Chebyshev polynomial interpolation. By using the Chebyshev polynomial interpolation, the original problem is transformed to several nonlinear programming problems to facilitate employing DE. Each individual in DE’s population represents a candidate point on the boundary of the attainable region. In order to lead the population to the boundary simultaneously, a scheme is devised by exploiting the parallel feature of DE. Different from conventional methods which generate one point of the boundary in each run, our proposed method generates one side of the boundary of the attainable region. A scenario is presented to evaluate the designed method and some analyses are conducted to evaluate the influence of the vehicle’s design parameters on the attainable region.

Methods for analysis of optical fibers with arbitrary refractive index profile

Two fast and accurate algorithms based on the orthogonal polynomial approximation and the Chebyshev polynomial interpolation for obtaining the actual field solutions of a fiber with arbitrary refractive index profile are presented. These solutions in turn can be used to evaluate the dispersion parameters of the fiber. The numerical methods are compared in terms of their performances, viz., complexity and accuracy. The method based on the orthogonal polynomial approximation (OPA) is simple in principle and easy to implement on a computer, and it has several advantages compared to the method based on the Chebyshev polynomial interpolation (CPI).

Pseudospectral Solution of Near-Singular Problems using Numerical Coordinate Transformations Based on Adaptivity

The work presented here describes a method of coordinate transformation that enables spectral methods to be applied efficiently to differential problems with steep solutions. The approach makes use of the adaptive finite difference method presented by Huang and Sloan [SIAM J. Sci. Comput., 15 (1994), pp. 776--797]. This method is applied on a coarse grid to obtain a rough approximation of the solution and a suitable adapted mesh. The adaptive finite difference solution permits the construction of a smooth coordinate transformation that relates the computational space to the physical space. The map between the spaces is based on Chebyshev polynomial interpolation. Finally, the standard pseudospectral (PS) method is applied to the transformed differential problem to obtain highly accurate, nonoscillatory numerical solutions. Numerical results are presented for steady problems in one and two space dimensions.