Linearly dependent numbers over the rationals

In summary, the conversation discusses the concept of linear dependence and the possibility of finding an algorithm to calculate the coefficients or check for linear dependence among real positive numbers over rational numbers. It also raises the question of whether there is a similar method for more than two numbers.
  • #1
kyryk
4
0
Hi,
Assume that the real positive numbers x_1,x_2,...,x_n are linearly dependent over the rational numbers, i.e. there are q_1,...,q_n in Q such that x_1*q_1+...+x_n*q_n=0. Is there an algorithm to calculate the coefficients q_i? Is there an algorithm to even check if the x_i's are linearly dependent over Q? In a finite dimensional space, we have the Gauss elimination algorithm, is there something similar?

For example, if we only have two numbers x and y, both >0, then we can start subtracting the smaller one from the larger one. This process terminates until one of them is zero, and that happens in a finite amount of steps if and only if their ratio is a rational number.
Is there anything similar to this for more than two numbers?
 
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  • #2
kyryk said:
Hi,
Assume that the real positive numbers x_1,x_2,...,x_n are linearly dependent over the rational numbers, i.e. there are q_1,...,q_n in Q such that x_1*q_1+...+x_n*q_n=0.
This is incorrect. If the numbers x1, x2, ..., xn are linearly dependent, there are numbers q1, q2, ..., qn, not all of which are zero, for which x1q1 + x2q2 + ... + xnqn = 0.
kyryk said:
Is there an algorithm to calculate the coefficients q_i? Is there an algorithm to even check if the x_i's are linearly dependent over Q? In a finite dimensional space, we have the Gauss elimination algorithm, is there something similar?

For example, if we only have two numbers x and y, both >0, then we can start subtracting the smaller one from the larger one. This process terminates until one of them is zero, and that happens in a finite amount of steps if and only if their ratio is a rational number.
Is there anything similar to this for more than two numbers?
 
  • #3
Sure, it is part of the definition of linearly dependent, thanks for clarifying it though.

However, I still need an answer/suggestions to my actual question.
 

FAQ: Linearly dependent numbers over the rationals

1. What does it mean for numbers to be "linearly dependent" over the rationals?

Linear dependence refers to a mathematical relationship between two or more numbers where one number can be written as a linear combination of the others. In the context of the rationals, this means that one rational number can be expressed as a multiple of another rational number.

2. How can I determine if a set of numbers is linearly dependent over the rationals?

To determine if a set of numbers is linearly dependent over the rationals, you can use the method of Gaussian elimination. This involves writing the numbers as a matrix and performing row operations to reduce the matrix to row-echelon form. If the resulting matrix has a row of zeros, then the numbers are linearly dependent.

3. Can linearly dependent numbers over the rationals ever be linearly independent?

No, linearly dependent numbers over the rationals can never be linearly independent. This is because if one number can be expressed as a linear combination of the others, then it is not possible for them to be linearly independent.

4. How is linear dependence related to the concept of linear independence?

Linear dependence and linear independence are opposite concepts. Linear dependence refers to a relationship between numbers where one can be expressed as a linear combination of the others, while linear independence refers to a set of numbers that cannot be written as a linear combination of each other.

5. Are linearly dependent numbers over the rationals important in any specific field of study?

Yes, linearly dependent numbers over the rationals are important in many fields, including linear algebra, number theory, and cryptography. They can also be used to solve systems of linear equations and to study the structure of vector spaces.

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