Understanding Orthogonal Polynomials in Mathematical Physics

In summary, the conversation is about learning mathematical physics and specifically, orthogonal polynomials. The meaning of "orthogonal" in this context is defined as being perpendicular or at a right angle with respect to an inner product on a vector space, such as the space of polynomials. A set of polynomials is considered orthogonal if each polynomial is orthogonal to every other polynomial in the set.
  • #1
sniffer
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i am still learning mathematical physics.

i am learning orthogonal polynomials, but still confused.

what is the meaning of "orthogonal" here?
 
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  • #2
Orthogonality of two elements of a vectorspace (in this case the space of all polynomials) is only defined with respect to an inner product on the space. A possible inner product on a polynomial space could for instance be:

[tex] \left<f,g\right>= \int_0^1 f(x) g(x) dx[/tex]

Now f and g are orthogonal [tex]\iff \left<f,g\right>=0[/tex].

A set of polynomials is called orthogonal if each polynomial is orthogonal to each other polynomial in the set.
 
  • #3


Orthogonal polynomials are a fundamental concept in mathematical physics that are used to solve a wide range of problems in the field. They are a special type of polynomials that have the property of being orthogonal, meaning they are perpendicular to each other when plotted on a graph. This property allows them to be used in various mathematical equations and calculations to simplify and solve complex problems.

In the context of mathematical physics, orthogonal polynomials are particularly useful because they can be used to represent physical phenomena or systems in a simpler and more efficient manner. For example, they can be used to describe the motion of a particle in a quantum mechanical system or the behavior of a vibrating string.

Furthermore, the orthogonality property of these polynomials also allows for their use in approximation methods, where they can be used to approximate complex functions by a simpler polynomial function. This is particularly useful in numerical methods and simulations in physics.

I understand that learning about orthogonal polynomials can be confusing at first, but with practice and further study, their applications and importance in mathematical physics will become clearer. Keep studying and don't be afraid to ask questions and seek help from your peers or instructors. Good luck in your learning journey!
 

What are orthogonal polynomials?

Orthogonal polynomials are a special type of mathematical function that are used to represent and approximate other functions. They are typically defined over a specific interval and have certain properties, such as being orthogonal (perpendicular) to each other, that make them useful in various applications.

Why are orthogonal polynomials important?

Orthogonal polynomials are important because they can be used to approximate any function to a high degree of accuracy. This makes them useful in many areas of science and engineering, including statistics, physics, and signal processing. They also have special properties that allow for efficient computational methods.

What are some examples of orthogonal polynomials?

Some commonly used orthogonal polynomials include Legendre polynomials, Chebyshev polynomials, and Hermite polynomials. These are named after the mathematicians who first studied them and have different properties and areas of application. Other examples include Gegenbauer polynomials, Jacobi polynomials, and Laguerre polynomials.

How are orthogonal polynomials used in statistics?

In statistics, orthogonal polynomials are often used to fit curves to data that cannot be accurately represented by a simple linear model. They are also used in regression analysis and in the analysis of variance (ANOVA) method. They provide a way to analyze complex data sets and make predictions based on the relationships between different variables.

How are orthogonal polynomials related to other types of polynomials?

Orthogonal polynomials are a subset of the larger family of polynomials. They are related to other types of polynomials, such as monomials (x^n), binomials (ax + b), and trinomials (ax^2 + bx + c), but have different properties and applications. In particular, orthogonal polynomials have the unique property of being orthogonal to each other, which makes them useful for approximating other functions.

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