💡 Problem Formulation: In mathematical and computational fields, it’s common to work with orthogonal polynomials such as Legendre polynomials. Evaluating a two-dimensional (2D) Legendre series on the Cartesian product of two domains, x and y, involves computing values over a grid defined by these two variables. This article aims to illustrate Python methods to perform … Read more
💡 Problem Formulation: We aim to generate a pseudo-Vandermonde matrix using Legendre polynomials given a complex array of points with coordinates (x, y, z). The Vandermonde matrix is a key component in various numerical and approximate calculations, and its construction for complex points via Legendre polynomials extends its applications. The typical input is a list … Read more
💡 Problem Formulation: In computational mathematics, evaluating a Legendre series at specific points involves calculating the sum of Legendre polynomials weighted by a set of coefficients for each point. When dealing with 3D space and a 2D coefficient array, this task can become complex. The input consists of a 2D array representing the coefficients of … Read more
💡 Problem Formulation: This article focuses on constructing a pseudo Vandermonde matrix utilizing Legendre polynomials evaluated at a grid of floating-point numbers representing 3D coordinates (x, y, z). The generating process involves mathematical operations that efficiently compute this matrix. As an example, given a set of points such as [(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], … Read more
💡 Problem Formulation: When working with Hermite E series in three dimensions, particularly for applications in computational physics or computer graphics, it is often necessary to evaluate the series at specific points (x, y, z) using a given set of coefficients. This problem typically involves traversing the coefficients in a 2D array to calculate the … Read more
💡 Problem Formulation: We seek efficient methods to evaluate the 2D Hermite E polynomial series at specified points (x, y), using only a 1D array of coefficients. As input, we accept values of x, y, and a 1D array of coefficients representing the Hermite E series. The desired output is the evaluated result at the … Read more
💡 Problem Formulation: Given two Hermite E polynomial series, the task is to divide one series by the other and obtain a quotient series. Hermite E polynomials, commonly used in probability theory and physics, can be represented in Python using arrays or specific libraries. For instance, if you have two series e1 and e2, the … Read more
💡 Problem Formulation: Creating a Vandermonde-like matrix using Hermite E polynomials and a given 3D array of floating points (x, y, z) is essential for various numerical and scientific computations. The challenge lies in transforming a set of points into a matrix form where rows correspond to the points and columns correspond to the Hermite … Read more
💡 Problem Formulation: When working with Hermite E polynomials in numerical computing, one often needs to evaluate these polynomials at a set of points ‘x’, while simultaneously determining the shape of the coefficient array for each dimension of ‘x’. This is essential in scientific computations where such polynomials are used for interpolation, approximation, and as … Read more
💡 Problem Formulation: Calculating the nuclear norm (or trace norm) of a matrix is a common task in linear algebra with applications in machine learning, signal processing, and statistics. The nuclear norm is the sum of the singular values of a matrix. For example, given a matrix A, we seek to compute its nuclear norm … Read more
💡 Problem Formulation: Hermite E polynomials can be an essential tool in computational mathematics and physics for function approximation and quantum mechanics. The challenge arises when the coefficients of the Hermite E series are multidimensional, which complicates the evaluation at given points x. In this article, we will discuss how to compute the value of … Read more
💡 Problem Formulation: In linear algebra, the Frobenius norm is a measure of a matrix’s size. It is the square root of the sum of the absolute squares of its elements. For instance, given a matrix A, we want to calculate its Frobenius norm. If A = [[4, 5], [3, 2]], the desired output is … Read more