Is a Matrix Invertible and Have Integer Entries If Its Determinant is 1 or -1?

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In summary, we can prove that a matrix $A$ with integer entries is invertible and has an inverse with integer entries if and only if its determinant is equal to 1 or -1. This can be shown by considering the properties of the determinant and the adjugate matrix, which contains all integer entries for $A$. If the determinant is not equal to 1 or -1, then the inverse of $A$ will contain fractional entries, contradicting the assumption that $A$ has only integer entries. Conversely, if the determinant is equal to 1 or -1, then the inverse of $A$ will also have only integer entries, as shown by the properties of the adjugate matrix.
  • #1
Dethrone
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Let $A$ be a matrix each of whose entries are integers. Prove that $A$ is invertible and $A^{-1}$ having integer entries if and only if $\text{det}A=1$ or $-1$.

What I have so far is this:
Suppose $A$ is invertible, then $AA^{-1}=I$ and $\text{det}A\cdot \text{det}A^{-1}=1$.
I am not sure how to proceed.
 
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  • #2
I think I figured it out, but I'm too lazy to type out the formal proof with latex. The forward direction can be proven directly by seeing that if $A$ has integer entries, then the adjugate/adjoint will have integer entries. Furthermore, since $A^{-1}$ has integer entries, $\text{det}A$ must either be 1 or -1. Approaching this by contrapositive, we can see that if $\text{det}A$ is not 1 or -1, then $A^{-1}$ has fractional entries. A contradiction.
The backward direction is just reverse logic. Is that correct?
 
  • #3
I agree with the forward direction. \(\displaystyle A^{-1}=\frac{1}{\text{det }(A)} \text{adj }(A)\) and $\text{adj }(A)$ will contain all integers for this particular $A$ (might need to justify this depending on how in depth your prof likes you to go), so clearly \(\displaystyle \frac{1}{\text{det }(A)}\) must be an integer in order for the $A^{-1}$ to contain only integers, and the result follows.

For the backward direction, you are suggesting starting with $\displaystyle {\text{det }(A)}= \pm 1 \implies \frac{1}{\text{det }(A)} \text{adj }(A) $ contains all integer entries $\implies A^{-1}$ contains all integer entries. Right?

I think this proof is solid but saying some words about the adjunct matrix containing all integers would be good because it is a major part of your argument in both directions. :)
 
  • #4
Yep, that is precisely what I wanted to say. On paper, I like to be really rigorous and thorough with my explanation, but having to use \text{} each time was too much for me to handle. :p Thanks Jameson!
 
  • #5
$\DeclareMathOperator{\adj}{adj}$

Jameson said:
I agree with the forward direction. \(\displaystyle A^{-1}=\frac{1}{\text{det }(A)} \text{adj }(A)\) and $\text{adj }(A)$ will contain all integers for this particular $A$ (might need to justify this depending on how in depth your prof likes you to go), so clearly \(\displaystyle \frac{1}{\text{det }(A)}\) must be an integer in order for the $A^{-1}$ to contain only integers, and the result follows.

Rido12 said:
Yep, that is precisely what I wanted to say. On paper, I like to be really rigorous and thorough with my explanation, but having to use \text{} each time was too much for me to handle. :p Thanks Jameson!

Hey Rido! ;)

I don't think the proof is valid yet. What if $\adj A$ contains only even numbers and $\det A = 2$?

Btw, \det already is an operator name, and $\adj$ can be written as \operatorname{adj}, which takes care of proper spacing.
Alternatively, if you type \DeclareMathOperator{\adj}{adj} once (as I did in this post), you can use \adj in the remainder of the post. (Nerd)
(It might be a nice improvement if \adj was predefined in our forum.)Here's a different way to proceed, which does not require \text or \operatorname at all.
Suppose $\det A \ne \pm 1$.
Since $\det A \cdot \det A^{-1} = \det I = 1$, one of them must have a magnitude greater than 1, while the other one must be between 0 and 1.
Is that possible for integer matrices?
 
  • #6
Good catch, ILS. You're 100% correct. If all the terms contain a common factor then \(\displaystyle \frac{1}{\text{det }(A)}\) doesn't need to be 1.

Much better idea for the proof as well. :)
 
  • #7
Hi ILS! (Cool)

That makes sense! Indeed, since they have integer elements, the determinant must be larger than 1. It could be 0, but then that would violate the fact that $A$ is invertible, so that could not happen.
Seems like $\adj$ is predefined now...:D

It would also be nice if $\operatorname{col} A,\operatorname{row}A, \operatorname{span}A, \operatorname{rref}A$, etc could be predefined too...hehe. Not sure if that would take up too much necessary space, however.
 

1. What is invertibility in scientific terms?

Invertibility refers to the property of a mathematical function or system that allows it to be reversed or undone. In other words, an invertible function or system has a unique input-output relationship that can be reversed to find the initial input from a given output.

2. How does invertibility impact scientific research?

Invertibility is a crucial concept in scientific research as it allows for the validation and replication of findings. By being able to reverse a process or function, scientists can ensure that their results are accurate and reproducible.

3. Can all mathematical functions or systems be invertible?

No, not all mathematical functions or systems are invertible. A function must meet certain criteria, such as being one-to-one (each input has a unique output) and onto (every output has a corresponding input), to be considered invertible.

4. How is invertibility related to causality in scientific experiments?

Invertibility is closely tied to causality in scientific experiments. By being able to reverse a process or function, scientists can determine the cause of a particular outcome or result.

5. Are there any real-world applications of invertibility in science?

Yes, invertibility has many practical applications in science, including in fields such as signal processing, cryptography, and data compression. The ability to reverse a process or function is essential in these areas for accurate and efficient data analysis and communication.

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