Linear Algebra partitioned matrix and vector theoretical question

In summary, the conversation discusses the task of finding a non-zero vector q that satisfies Bq=0, where B is a partitioned matrix with X and I as its elements. The vector p is defined as the sum of 2011 unit vectors, and q is also a 4022 X 1 vector. The solution may involve expressing q in terms of p using partitioned matrix notation, but the exact calculation to find q is unclear. Further assistance is needed to solve the problem.
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Homework Statement



Let X be an invertible 2011 X 2011 matrix, let I be the 2011 identity matrix.

Let B=[[X,I],[I,X-1]] and let p=e1+e2+e3+...+e2011.

(The terms in the square brackets represent the rows of the matrix, so [X,I] is the first row)

Find a non-zero vector q, such that Bq=0.

Use partitioned matrix notation to write q explicitly in terms of p , and to display the calculation which shows that Bq=0.

The Attempt at a Solution



None. I have no idea what to do. The only thing that stands out to me is that
q is a 4022 X 1 vector and that p is a 2011 X 1 vector, so q must look something like:

q=([tp],[sp]) where t and s are real numbers
 
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  • #2
. I'm not sure what to do with this information, or how to proceed with the calculation. Any help would be greatly appreciated. Thank you!
 

1. What is a partitioned matrix in linear algebra?

A partitioned matrix is a matrix that is divided into smaller sub-matrices. These smaller sub-matrices can be arranged in rows or columns and can contain any number of elements. Partitioned matrices are useful for organizing and solving systems of linear equations.

2. How do you perform operations on partitioned matrices?

To perform operations on partitioned matrices, the same operations are applied to each individual sub-matrix. For example, to add two partitioned matrices, you would add each corresponding sub-matrix. Similarly, to multiply two partitioned matrices, you would multiply each corresponding sub-matrix and then sum the results.

3. What is the purpose of partitioning a matrix or vector in linear algebra?

Partitioning a matrix or vector can make it easier to solve complex systems of linear equations. It can also help with organizing and visualizing data in a more manageable way. Partitioning can also make certain operations, such as matrix multiplication, more efficient.

4. Can you partition a matrix or vector in any way?

Yes, you can partition a matrix or vector in any way that makes sense for the problem at hand. However, it is important to note that the dimensions of the sub-matrices or sub-vectors must match in order to perform operations on them.

5. Are there any limitations or drawbacks to using partitioned matrices in linear algebra?

One limitation of using partitioned matrices is that they can become more complicated and difficult to work with as the number of partitions increases. Additionally, partitioning a matrix or vector may not always result in a more efficient or accurate solution, so it is important to consider if partitioning is necessary for the problem at hand.

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