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I have to find determinant of $$A := \begin{bmatrix}0 & 0 & 0 & ... &0 & a_0 \\ -1 & 0 & 0 & ... &0 & a_1\\ 0 & -1 & 0 & ... &0 & a_2 \\ 0 & 0 & -1 & ... &0 & a_3 \\ \vdots &\vdots &\vdots & \ddots &\vdots&\vdots \\0 & 0 & 0 & ... &-1 & a_{n-1} \end{bmatrix} + t I_{n \times n}$$

It is not a difficult thing to do. My method is as follows :

$$\begin{bmatrix}0 & 0 & 0 & ... &0 & a_0 \\ -1 & 0 & 0 & ... &0 & a_1\\ 0 & -1 & 0 & ... &0 & a_2 \\ 0 & 0 & -1 & ... &0 & a_3 \\ \vdots &\vdots &\vdots & \ddots &\vdots&\vdots \\0 & 0 & 0 & ... &-1 & a_{n-1} \end{bmatrix} + t I_{n \times n} = \begin{bmatrix}t & 0 & 0 & ... &0 & a_0 \\ -1 & t & 0 & ... &0 & a_1\\ 0 & -1 & t & ... &0 & a_2 \\ 0 & 0 & -1 & ... &0 & a_3 \\ \vdots &\vdots &\vdots & \ddots &\vdots&\vdots \\0 & 0 & 0 & ... &-1 & a_{n-1} + t \end{bmatrix} $$

Performing the row reduction of type $R_{k+1} \to R_{k+1} + \dfrac{1}{t}R_k$

I get an upper triangular matrix

$$\begin{bmatrix}t & 0 & 0 & ... &0 & a_0 \\ 0 & t & 0 & ... &0 & a_1 + \dfrac {a_0} t\\ 0 & 0 & t & ... &0 & a_2 + \dfrac{a_1}{t} + \dfrac {a_0} {t^2} \\ 0 & 0 & 0 & ... &0 & a_3 + \dfrac{a_2}{t} + \dfrac{a_1}{t^2} + \dfrac {a_0} {t^3} \\ \vdots &\vdots &\vdots & \ddots &\vdots&\vdots \\0 & 0 & 0 & ... &0 & a_{n-1} + t + \sum_{k=0}^{n-2} \dfrac{a_{k}}{t^{(n-1) - k }} \end{bmatrix} $$

Determinant of which is $t^n + \sum^{n-1}_{k = 1} a_k t^{k}$.

My friend says this is not a rigorous proof and that I have to use induction to prove $$\det A = t^n + \sum^{n-1}_{k = 1} a_k t^{k}$$ She says that I have only found a formula for $\det A$ and I can't be sure if it works for all $n\in \Bbb N$ without a proof. Is she correct?

user8277998
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  • Listen to your friend. I've a solid background in logic and she is absolutely correct here. If you don't believe her or me, please ask any professional logician instead of trying to judge between (sometimes wrong) answers from strangers online. – user21820 Nov 14 '17 at 04:58
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    @user21820 I didn't find any of the answers convincing, hence no green tick. Since you're a professional logician, will a proof that uses "dots" - like mine - accepted in academic papers ? Or you have to prove it using induction (or something else) every time ? – user8277998 Nov 14 '17 at 09:57
  • Mathematical papers do not usually give completely rigorous proofs, but they often give at least enough details to convince their intended audience (who could be experts in that field) that there exists some rigorous proof. But the authors should know how to do it rigorously. Modern mathematics is founded on formal systems and not intuition. In your case, it seems you do not quite know what is a rigorous proof, so if you learn basic logic you will understand what I mean. (Come to the Logic chat-room if you wish to further discuss!) – user21820 Nov 14 '17 at 10:06
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    @BCLC: Yes you are wrong. Anything that requires inductive or recursive definitions necessarily require induction, whether or not you notice it. For example, proving $\sum_{k=1}^n k = n·(n+1)/2$ requires induction even if you use the pairing trick. – user21820 Oct 25 '21 at 05:30
  • @user21820 thanks. how specifically am i wrong in my case please? perhaps i used induction but didn't even realise it? – BCLC Oct 25 '21 at 05:47
  • @BCLC: This is a foundational issue. You simply cannot make inductive definitions without some kind of usage of induction or recursion. Unfortunately, if you don't learn some specific foundational system, you won't be able to understand what is missing because you would rely on your intuition rather than rigorous proof. – user21820 Oct 25 '21 at 06:22

3 Answers3

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The argument can be made rigorous by the following identity: let $U$ be the final triangular matrix and let $D$ be the matrix containing only a subdiagonal of $1, \cdots, 1$. Then one has

$$ \left(I - \frac{1}{t} D\right) U = (A + t I) $$ hence $\det(A+tI)= \det(I - \frac{1}{t} D) \det (U) = \det(U)$

It means that this process is actually an $LU$ decomposition of $A+tI$.

For a complete calculation, let

$$\renewcommand{\arraystretch}{2} \begin{array}{rcl}{P}_{0}&=&0\\ {P}_{i}&=&\displaystyle \sum _{p = 0}^{i-1} {a}_{p} {t}^{p} \quad i \geqslant 1\\ L&=&{\left({{\delta}}_{i}^{j}-{t}^{{-1}} {{\delta}}_{i}^{j+1}\right)}_{i , j}\\ U&=&{\left(t {{\delta}}_{i}^{j}+{t}^{1-i} {P}_{i} {{\delta}}_{j}^{n}\right)}_{i , j} \end{array}$$

Then, using ${P}_{i}-{P}_{i-1} = {a}_{i-1} {t}^{i-1}$ for $i \geqslant 1$,

$$\renewcommand{\arraystretch}{2} \begin{array}{rcl}{\left(L U\right)}_{i , j}&=&\displaystyle \sum _{k = 1}^{n} \left({{\delta}}_{i}^{k}-{t}^{{-1}} {{\delta}}_{i}^{k+1}\right) \left(t {{\delta}}_{k}^{i}+{t}^{1-k} {P}_{k} {{\delta}}_{j}^{n}\right)\\ &=&t {{\delta}}_{i}^{j}+{t}^{1-i} {P}_{i} {{\delta}}_{j}^{n}-{{\delta}}_{i}^{j+1}-{t}^{1-i} {P}_{i-1} {{\delta}}_{j}^{n}\\ &=&t {{\delta}}_{i}^{j}-{{\delta}}_{i}^{j+1}+{a}_{j-1} {{\delta}}_{j}^{n}\\ &=&{\left(A+t I\right)}_{i , j} \end{array}$$

where $\delta_i^j$ is Kronecker's delta.

Gribouillis
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Yes, the method is completely rigorous, because here $t$ is, algebraically, an indeterminate.

If the coefficients of the matrix are supposed to be in a field $F$, then the computation you make takes place in the field $F(t)$ of rational functions in the indeterminate $t$. No problem here in considering $t^{-1}$, because $t$ is a nonzero element of the field.

To be picky, induction should be needed, but laying out the argument is very easy.

egreg
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    "To be picky, induction should be needed" Why so ? – user8277998 Nov 11 '17 at 22:13
  • @123 There are “dots” in the argument. But, as I said, the induction step is straightforward. – egreg Nov 11 '17 at 22:27
  • @egreg Does that matter? Is there a situation where using dots instead of induction will give an incorrect proof? – Duncan Ramage Nov 11 '17 at 23:00
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    @DuncanRamage That's why I said “to be picky”; just be aware that induction is being used (and its formalization in the present case is trivial). – egreg Nov 11 '17 at 23:08
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    @123 and DuncanRamage: "Performing the row reduction of type ..." is actually not a single row reduction, but $n-1$ row reductions applied in a row (no pun intended). And the order of these reductions matters. So, yes, there is a hidden induction in your proof, unless you replace the $n-1$ row reductions by a multiplication by some triangular matrix (recommended if you want to formalize the proof). – darij grinberg Nov 12 '17 at 06:38
  • @DuncanRamage: Um of course it matters. Dots are often hiding things... You are probably familiar with the common mistake of thinking that infinite series can be rearranged just like a finite sum, which is of course wrong. – user21820 Nov 12 '17 at 13:51
  • @user21820 Good point. How about "...when using dots to hide finitely many cases instead of induction..."? – Duncan Ramage Nov 13 '17 at 04:05
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    @DuncanRamage: I think that if you do it properly, you can avoid making mistakes. Nevertheless, using dots in place of precise statements always relies on pattern matching by the reader to figure out what the intended meaning is, so it can be useful in rough work but not in a rigorous proof. – user21820 Nov 13 '17 at 09:00
  • @user21820 I disagree. No pattern matching is required, as the last term explicitly states what the pattern is. – Duncan Ramage Nov 13 '17 at 18:42
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    @DuncanRamage: You're simply wrong. A reader needs to figure out the pattern involves the diagonal and the final column. If you still do not get it, you need to study formal systems. – user21820 Nov 13 '17 at 18:48
  • @user21820 I get it just fine; i'm just not a pedant. – Duncan Ramage Nov 13 '17 at 18:49
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    @DuncanRamage: The asker explicitly says "My friend says this is not a rigorous proof", so it's necessary to be pedantic to explain the situation fully to the asker. By avoiding the technical detail, you are not helping the asker at all. – user21820 Nov 13 '17 at 18:53
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    @user21820 I think this discussion is out of place here. These comments belong to the other answer or, better, to a chat. – egreg Nov 13 '17 at 18:56
  • egreg note: i didn't use induction! – BCLC Oct 25 '21 at 05:49
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$-A$ is the companion matrix for the polynomial $$p(x) = a_0 + a_1 x + \dots + a_{n-1} x^{n-1} + x^n.$$ Hence the eigenvalues of $-A$ are the roots $r_k$ of this polynomial. Since adding a multiple of the identity to a matrix just shifts eigenvalues, the eigenvalues of $A + tI$ are the quantities $t-r_k$. Hence, since the determinant of a matrix is the product of its eigenvalues, we have $$\det(A + tI) = (t - r_1)(t - r_2) \dots (t-r_n) = p(t)$$ as required.

Nick Alger
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