OrthogonalPolynomial - crowlogic/arb4j GitHub Wiki

An orthogonal polynomial is a type of polynomial that belongs to a sequence of polynomials satisfying certain orthogonality conditions with respect to a specific inner product defined on a function space. In other words, any two different polynomials in the sequence are orthogonal to each other under the given inner product.

To understand this better, let's consider a weight function w(x) defined on an interval [a, b]. The inner product of two functions f(x) and g(x) is defined as:

⟨f, g⟩ = ∫[a, b] f(x) g(x) w(x) dx

A sequence of polynomials {P₀(x), P₁(x), P₂(x), ...} is said to be orthogonal with respect to the weight function w(x) if for any distinct indices i and j, the inner product of Pᵢ(x) and Pⱼ(x) is zero:

⟨Pᵢ, Pⱼ⟩ = ∫[a, b] Pᵢ(x) Pⱼ(x) w(x) dx = 0, for i ≠ j

Orthogonal polynomials are useful in many areas of mathematics and its applications, such as numerical analysis, approximation theory, and spectral theory. Some well-known families of orthogonal polynomials include:

• Legendre polynomials (w(x) = 1, on [-1, 1])
• Chebyshev polynomials (w(x) = 1/√(1-x²), on [-1, 1])
• Hermite polynomials (w(x) = e^(-x²), on (-∞, ∞))
• Laguerre polynomials (w(x) = x^α e^(-x), on [0, ∞), for some α > -1)
• Jacobi polynomials (w(x) = (1-x)^(α) * (1+x)^(β), on [-1, 1], for some α, β > -1)

These orthogonal polynomials have distinct properties and applications, and they are widely used in solving mathematical problems and in engineering applications.