Non-square linear systems with exterior product

In summary, the conversation discusses the calculation of the general solution of a system of linear equations, specifically for non-square systems. The speaker mentions a book on linear algebra via exterior products that they find difficult to understand. They mention using Cramer's rule to calculate the solution, and someone else mentions using a maximal nonzero exterior product to calculate the homogeneous solution. The speaker asks for clarification on this method and provides an example of a non-square system. The conversation then shifts to discussing another example without providing an explanation for the general solution. The speaker expresses confusion and asks for clarification on the pattern.
  • #1
JonnyMaddox
74
1
Hi, how can I compute the general solution of a system of linear equations? Non-square systems for example. I have the book Linear Algebra via exterior products, but it is the worst book in the history of math books, I think I'll burn it somehow, whatever. I can calculate the solution with the exterior product easily with Cramer's rule. For non-square systems, or systems with infinite many solutions Winitzki talks gibberish about a maximal non-zero exterior product between the vectors of the matrix and then does some magic with it to calculate the homogeneous solution. Can someone explain this to me in a clear way? I think one should calculate it by first finding the non-zero exterior product between the vectors of the matrix (which should be a subspace) and then somehow express the remaining vectors in terms of the non-zero set? But that doesn't make sense. hm
 
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  • #2
Can someone help me with this? I give an example of the book:

Let's say the vectors a,b,c are not a basis in the vectorspace V, then there exists a maximal nonzero exterior product (which should also tell you what the rank is) of a linear independent subset of a,b,c Take an example

[itex]2x+y=1[/itex]

[itex]2x+2y+z=4[/itex]

[itex]y+z=3[/itex]

Now
[itex]a=(2,2,0)[/itex],
[itex]b=(1,2,1)[/itex],
[itex]c=(0,1,1)[/itex],
[itex]p=(1,4,3)[/itex]

We see that [itex]a \wedge b \wedge c=0[/itex]. And the maximal nonzero exterior product can be written as [itex]\omega =a \wedge b[/itex] (which is not equal to zero.
Now we can check if [itex]p[/itex] is a subset of the span [itex]{a,b}[/itex] with [itex]\omega \wedge p=0[/itex] so [itex]p[/itex] can be expressed with [itex]a,b[/itex]. We can find the coefficients with Cramer's rule

[itex]\alpha = \frac{p\wedge b}{a\wedge b}=-1[/itex]

[itex]\beta = \frac{a\wedge p}{a\wedge b}= 3[/itex]

Therefore [itex]p=-a+3b[/itex] so the inhomogeneous solution is [itex]x^{1}= (-1,3,0)[/itex] Now to determine the space of homogeneous solutions, the vector [itex]c[/itex] get's decomposed into a linear combination of [itex]a[/itex] and [itex]b[/itex] again by Cramer's rule. This gives [itex]c=-\frac{1}{2}a+b[/itex] And the space of homogeneous solutions is given by the span of [itex]x_{i}^{(0)(1)}=(-\frac{1}{2},1,-1)[/itex]. So the general solution is

[itex]x_{i}=x_{i}^{1}+ \beta x_{i}^{(0)(1)}= (-1-\frac{1}{2}\beta, 3+\beta, -\beta)[/itex]

Then he gives another example with a non-square system

[itex]x+y=1[/itex]

[itex]y+z=1[/itex]

And the general solution is [itex]x_{i}=(1,0,1)+\alpha (1,-1,1)[/itex] (with no explanation).

I don't see a pattern here. What is going on?
 

1. What is a non-square linear system with exterior product?

A non-square linear system with exterior product is a mathematical system that involves multiple linear equations with multiple variables, where the number of equations does not equal the number of variables. The exterior product refers to the use of the wedge product, a geometric operation that combines two vectors to create a new vector.

2. How is a non-square linear system with exterior product different from a square linear system?

A square linear system has the same number of equations and variables, making it easier to solve. In contrast, a non-square linear system with exterior product is more complex and requires different methods, such as using the exterior product, to solve.

3. What are some applications of non-square linear systems with exterior product?

Non-square linear systems with exterior product are commonly used in engineering, physics, and computer science to model complex systems and solve optimization problems. They can also be used in geometric calculations and in the study of vector spaces.

4. What are the challenges of solving non-square linear systems with exterior product?

Solving non-square linear systems with exterior product can be challenging because they require different techniques and methods compared to square linear systems. Additionally, the use of the exterior product can result in larger matrices and more complex calculations, making it more difficult to find a solution.

5. Are there any specific techniques or algorithms for solving non-square linear systems with exterior product?

Yes, there are various techniques and algorithms for solving non-square linear systems with exterior product, such as the Gauss-Jordan elimination method, the QR decomposition method, and the Cholesky decomposition method. These methods involve transforming the system into an equivalent form that is easier to solve.

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