Product Spaces: Showing R 2 = R × R \mathscr{R}^{2}=\mathscr{R}\times \mathscr{R} R 2 = R × R

Introduction

In measure theory, the concept of product spaces plays a crucial role in understanding the structure of higher-dimensional spaces. One of the fundamental results in this area is the demonstration that the 2-dimensional Euclidean space, denoted by $\mathscr{R}^{2}$, is equivalent to the product of two 1-dimensional Euclidean spaces, denoted by $\mathscr{R}\times \mathscr{R}$. This result is often referred to as the product space representation of $\mathscr{R}^{2}$. In this article, we will delve into the details of this representation and explore the underlying mathematical concepts.

The Class of Bounded Intervals

To begin with, let's consider the class of bounded intervals, denoted by $\mathcal{R}_{1}$. This class consists of all sets of the form $\{x\in\mathbb{R}:a<x\leq b\}$, where $a$ and $b$ are real numbers. The class $\mathcal{R}_{1}$ is a fundamental concept in measure theory, and it serves as the building block for more complex sets.

The Class of Bounded Rectangles

Next, let's consider the class of bounded rectangles, denoted by $\mathcal{R}_{2}$. This class consists of all sets of the form $\{x\in\mathbb{R}^{2}:a_{i}<x_{i}\leq b_{i},i=1,2\}$, where $a_{i}$ and $b_{i}$ are real numbers. The class $\mathcal{R}_{2}$ is a natural extension of the class $\mathcal{R}_{1}$, and it plays a crucial role in the product space representation of $\mathscr{R}^{2}$.

The Product Space Representation

Now, let's consider the product space representation of $\mathscr{R}^{2}$. This representation is based on the idea of forming a new space by taking the Cartesian product of two existing spaces. In this case, we take the Cartesian product of the 1-dimensional Euclidean space $\mathscr{R}$ with itself, resulting in the 2-dimensional Euclidean space $\mathscr{R}\times \mathscr{R}$.

The Equivalence of $\mathscr{R}^{2}$ and $\mathscr{R}\times \mathscr{R}$

To demonstrate the equivalence of $\mathscr{R}^{2}$ and $\mathscr{R}\times \mathscr{R}$, we need to show that every set in $\mathscr{R}^{2}$ can be represented as a set in $\mathscr{R}\times \mathscr{R}$. This can be done by considering the class of bounded rectangles $\mathcal{R}_{2}$, which is a subset of $\mathscr{R}\times \mathscr{R}$.

The Sigma-Algebra Generated by $\mathcal{R}_{2}$

The class $\mathcal{R}_{2}$ is a sigma-algebra, meaning that it is closed under countable unions and intersections. This property is essential in the product space representation of $\mathscr{R}^{2}$, as it allows us to generate a new sigma-algebra by taking the Cartesian product of two existing sigma-algebras.

The Product Sigma-Algebra

The product sigma-algebra, denoted by $\mathcal{A}\times \mathcal{B}$, is the smallest sigma-algebra that contains both $\mathcal{A}$ and $\mathcal{B}$. In the context of the product space representation of $\mathscr{R}^{2}$, the product sigma-algebra is generated by the class of bounded rectangles $\mathcal{R}_{2}$.

The Measure on the Product Sigma-Algebra

To complete the product space representation of $\mathscr{R}^{2}$, we need to define a measure on the product sigma-algebra. This measure is typically denoted by $\mu\times \nu$, where $\mu$ and $\nu$ are measures on the individual sigma-algebras $\mathcal{A}$ and $\mathcal{B}$, respectively.

The Fubini's Theorem

Fubini's theorem is a fundamental result in measure theory that relates the measure of a set in the product space to the measures of its projections onto the individual spaces. This theorem plays a crucial role in the product space representation of $\mathscr{R}^{2}$, as it allows us to compute the measure of a set in the product space by integrating the measures of its projections onto the individual spaces.

Conclusion

In conclusion, the product space representation of $\mathscr{R}^{2}$ is a fundamental concept in measure theory that demonstrates the equivalence of the 2-dimensional Euclidean space and the product of two 1-dimensional Euclidean spaces. This representation is based on the idea of forming a new space by taking the Cartesian product of two existing spaces, and it relies on the properties of sigma-algebras and measures. The product space representation of $\mathscr{R}^{2}$ has far-reaching implications in various areas of mathematics, including real analysis, functional analysis, and probability theory.

References

• [1] Halmos, P. R. (1950). Measure theory. Van Nostrand.
• [2] Royden, H. L. (1988). Real analysis. Prentice Hall.
• [3] Rudin, W. (1976). Principles of mathematical analysis. McGraw-Hill.

Further Reading

For further reading on the product space representation of $\mathscr{R}^{2}$, we recommend the following resources:

• [1] "Measure Theory" by Paul R. Halmos
• [2] "Real Analysis" by H. L. Royden
• [3] "Principles of Mathematical Analysis" by Walter Rudin

Q: What is a product space?

A: A product space is a mathematical concept that represents the Cartesian product of two or more spaces. In the context of measure theory, a product space is used to represent the 2-dimensional Euclidean space as the product of two 1-dimensional Euclidean spaces.

Q: What is the significance of the product space representation of $\mathscr{R}^{2}$?

A: The product space representation of $\mathscr{R}^{2}$ is significant because it demonstrates the equivalence of the 2-dimensional Euclidean space and the product of two 1-dimensional Euclidean spaces. This representation has far-reaching implications in various areas of mathematics, including real analysis, functional analysis, and probability theory.

Q: What is the class of bounded intervals $\mathcal{R}_{1}$?

A: The class of bounded intervals $\mathcal{R}_{1}$ consists of all sets of the form $\{x\in\mathbb{R}:a<x\leq b\}$, where $a$ and $b$ are real numbers. This class is a fundamental concept in measure theory and serves as the building block for more complex sets.

Q: What is the class of bounded rectangles $\mathcal{R}_{2}$?

A: The class of bounded rectangles $\mathcal{R}_{2}$ consists of all sets of the form $\{x\in\mathbb{R}^{2}:a_{i}<x_{i}\leq b_{i},i=1,2\}$, where $a_{i}$ and $b_{i}$ are real numbers. This class is a natural extension of the class $\mathcal{R}_{1}$ and plays a crucial role in the product space representation of $\mathscr{R}^{2}$.

Q: What is the product sigma-algebra $\mathcal{A}\times \mathcal{B}$?

A: The product sigma-algebra $\mathcal{A}\times \mathcal{B}$ is the smallest sigma-algebra that contains both $\mathcal{A}$ and $\mathcal{B}$. In the context of the product space representation of $\mathscr{R}^{2}$, the product sigma-algebra is generated by the class of bounded rectangles $\mathcal{R}_{2}$.

Q: What is the measure on the product sigma-algebra $\mu\times \nu$?

A: The measure on the product sigma-algebra $\mu\times \nu$ is typically denoted by $\mu\times \nu$, where $\mu$ and $\nu$ are measures on the individual sigma-algebras $\mathcal{A}$ and $\mathcal{B}$, respectively. This measure is used to compute the measure of a set in the product space by integrating the measures of its projections onto the individual spaces.

Q: What is Fubini's theorem?

A: Fubini's theorem is a fundamental result in measure theory that relates the measure of a set in the product space to the measures of its projections onto the individual spaces. This theorem plays a crucial role in the product space representation of $\mathscr{R}^{2}$, as it allows us to compute the measure of a set in the product space by integrating the measures of its projections onto the individual spaces.

Q: What are some applications of the product space representation of $\mathscr{R}^{2}$?

A: The product space representation of $\mathscr{R}^{2}$ has far-reaching implications in various areas of mathematics, including real analysis, functional analysis, and probability theory. Some applications of this representation include:

• Real analysis: The product space representation of $\mathscr{R}^{2}$ is used to study the properties of functions on the 2-dimensional Euclidean space.
• Functional analysis: The product space representation of $\mathscr{R}^{2}$ is used to study the properties of linear operators on the 2-dimensional Euclidean space.
• Probability theory: The product space representation of $\mathscr{R}^{2}$ is used to study the properties of random variables on the 2-dimensional Euclidean space.

Q: What are some resources for further reading on the product space representation of $\mathscr{R}^{2}$?

A: Some resources for further reading on the product space representation of $\mathscr{R}^{2}$ include:

• "Measure Theory" by Paul R. Halmos
• "Real Analysis" by H. L. Royden
• "Principles of Mathematical Analysis" by Walter Rudin

Note: The Q&A section is not exhaustive, and there are many other questions and answers related to the product space representation of $\mathscr{R}^{2}$.