Minimise this (if you can)!

Algebra Level 5

3 x 2 + 3 y 2 + 3 z 2 + 2 x y + 4 x z + 6 y z + 3 x + 2 y + z + 1 3x^2+3y^2+3z^2+2xy+4xz+6yz+3x+2y+z+1

Find the minimal value of the function f ( x , y , z ) f(x,y,z) above, where x , y x,y and z z are real numbers. Round your answer to three significant figures.

If you come to the conclusion that no such minimum exists, enter 0.666

This is an Algebra problem; Calculus solutions are frowned upon.


The answer is 0.666.

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2 solutions

Otto Bretscher
Mar 19, 2016

Let's write the function in standard form as f ( v ) = v T Q v + b T v + c f(\mathbf{v})=\mathbf{v}^TQ\mathbf{v}+\mathbf{b}^T\mathbf{v}+c , where Q = [ 3 1 2 1 3 3 2 3 3 ] Q=\begin{bmatrix} 3 & 1 & 2 \\ 1 & 3 & 3\\2 & 3 & 3\end{bmatrix} , b T = [ 3 2 1 ] \mathbf{b}^T=[3\enspace 2 \enspace 1] , and c = 1 c=1 . Now det ( Q ) = 3 < 0 \det(Q)=-3<0 , so that Q Q has a negative eigenvalue λ \lambda ; let x \mathbf{x} be a unit eigenvector with eigenvalue λ \lambda . Then f ( k x ) = λ k 2 + ( b T x ) k + c f(k\mathbf{x})=\lambda k^2+(\mathbf{b}^T\mathbf{x})k+c , a quadratic function in k k with negative leading coefficient, so that f f fails to be bounded below. The answer is 0.666 \boxed{0.666} .

Moderator note:

When faced with a quadratic inequality, conversion into a matrix form will (eventually) yield the relevant sum of squares to consider.

My personal preference is to treat this as an inequality in the 4 variables x , y , z , 1 x, y, z, 1 , which allows us to use a 4 × 4 4 \times 4 matrix directly.

IE The expression is equal to

( x y z 1 ) ( 3 1 2 3 2 1 3 3 1 2 3 3 1 2 3 2 1 1 2 1 ) ( x y z 1 ) \begin{pmatrix} x & y & z & 1 \end{pmatrix} \begin{pmatrix} 3 & 1 & 2 & \frac{3}{2} \\ 1 & 3 & 3 & 1 \\ 2 & 3 & 3 & \frac{1}{2} \\ \frac{3}{2} & 1 & \frac{1}{2} & 1 \\ \end{pmatrix} \begin{pmatrix} x \\ y \\ z \\ 1 \\ \end{pmatrix}

We then need to find the eigenvectors/values of the center matrix.

Calvin Lin Staff - 5 years, 2 months ago

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A minor of this 4x4 matrix (as highlighted in red below) is equal to 3 ( 3 3 3 3 ) 1 ( 1 3 2 3 ) + 2 ( 1 3 2 3 ) = 3 < 0 3(3\cdot3 - 3\cdot3) - 1(1\cdot3 - 2\cdot3) + 2(1\cdot3-2\cdot3) =-3 < 0 , which is negative, then by Slyvester's criterion, there is no minimum value for this function. Am I right? Comrade @Otto Bretscher ( 3 1 2 3 2 1 3 3 1 2 3 3 1 2 3 2 1 1 2 1 ) \begin{pmatrix} \color{#D61F06}3 & \color{#D61F06}1 & \color{#D61F06}2 & \frac{3}{2} \\ \color{#D61F06}1 &\color{#D61F06}3 & \color{#D61F06}3 & 1 \\ \color{#D61F06}2 & \color{#D61F06}3 & \color{#D61F06}3 & \frac{1}{2} \\ \frac{3}{2} & 1 & \frac{1}{2} & 1 \\ \end{pmatrix}

Pi Han Goh - 5 years, 2 months ago

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Yes, exactly, Comrade... that's what I use in my solution. You can invoke Sylvester's criterion or just point out that there is a negative eigenvalue.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Please post another type of this question! I wanna practice on it! Thankssssss

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh Just take any quadratic inequality (without restrictions).

Calvin Lin Staff - 5 years, 2 months ago

@Pi Han Goh Ok I posted something.... I'm eagerly awaiting your solution, Comrade! ;)

Otto Bretscher - 5 years, 2 months ago
Pi Han Goh
Mar 18, 2016

This is a hyperboloid of two sheets. So it has no minimum value. See reference .

There is no equation (only a function), so, where is the hyperboloid? ;)

Otto Bretscher - 5 years, 2 months ago

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Compare 3 x 2 + 3 y 2 + 3 z 2 + 2 x y + 4 x z + 6 y z + 3 x + 2 y + z + 1 3x^2+3y^2+3z^2+2xy+4xz+6yz+3x+2y+z+1 with a x 2 + b y 2 + c z 2 + 2 f y z + 2 g z x + 2 h x y + 2 p x + 2 q y + 2 r z + d = 0 ax^2 + by^2 + cz^2 + 2fyz + 2gzx + 2hxy+ 2px + 2qy + 2rz + d = 0

find e, E, rank e, rank E, det E, roots of determinant ((a-x,h,g),(h,b-x,f), (g,f,c-x)) = 0

we get rho3 = 3, rho4 = 4, sgn(Delta) = -1, k = 0

Pi Han Goh - 5 years, 2 months ago

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Sure! I was just giving you a hard time since we don't have an equation "=0" in the problem.

So, now that we know that the surface f ( x , y , z ) = 0 f(x,y,z)=0 forms a hyperboloid... how does that prove that f ( x , y , z ) f(x,y,z) isn't bounded below?

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Set f(x,y,z) = that expression + some constant, do the same calculation, that constant cancelled out in calculation.

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh Are you saying that the level surface f ( x , y , z ) = k f(x,y,z)=k is a hyperboloid of two sheets for all constants k k ?

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Doesn't it?

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh I don't think so. But it does not really matter. All we need to know is that the surface f ( x , y , z ) = k f(x,y,z)=k is non-empty for all k k : The range of f f is R \mathbb{R} and there is no minimum.

It's getting late for me... I'll be back tomorrow. To be continued, Comrade!

Here is a more philosophical question: Do we trust your reference, or do we want to prove things ourselves, from first principles? It seems to me that the relevant fact is the following: If the matrix of the quadratic form (the first six terms of f f ) has a negative eigenvalue, then f f will not be bounded below.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher I would have proven them all myself and write it up on some wiki page on this site, and I will just reference it when I write a solution.

But given that I'm still a newbie in matrices and quadratic forms, I don't think I will do a good job on it as of now.

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh I wrote a brief solution... please let me know whether it makes any sense, Comrade @Pi Han Goh

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Haha!? What?! you're the expert here. I'm already lost in your f ( v ) = f(\mathbf v) = \ldots .

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh I'm just writing the input vector x , y , z x,y,z as v \mathbf{v} , a column vector.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher No idea. You literally need to spoodfeed me information at this point.

I still got much to learn...

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh Well, write v = [ x y z ] \mathbf{v}=\begin{bmatrix} x \\ y \\ z \end{bmatrix} and compute v T Q v + b T v + c \mathbf{v}^TQ\mathbf{v}+\mathbf{b}^T\mathbf{v}+c .... you will see that you end up with f ( x , y , z ) f(x,y,z)

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher I know that. I mean,

why you need to write it in that form? or more accurately, how do you know that f(v) = .... ?
Why does det(Q) < 0 implies that it has negative eigenvalues
What is " let x be a unit eigenvector with eigenvalue " for?
etc


I got so many questions here.

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh (a) We write it in this form to make the computation easier (more compact) (b) The determinant is the product of the eigenvalues (c) For λ \lambda to be an eigenvalue means that there exist nonzero vectors w \mathbf{w} such that Q w = λ w Q\mathbf{w}=\lambda \mathbf{w} ... those are the eigenvectors. We can pick a unit eigenvector to simplify computation.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Exercise Question : Find the minimum/maximum value of W ( x , y , z ) = 2 x 2 + 4 y 2 + 6 z 2 + 8 x y + 10 x z + 12 y z + 14 x + 16 y + 18 z + 20 W(x,y,z) = 2x^2 + 4y^2 + 6z^2 + 8xy + 10xz + 12yz + 14x + 16y + 18z + 20 (if it exists).


Your method : To prove that it has no maximum value

Let W ( v ) = v T Q v + b T v + c W (\mathbf v) = \mathbf v ^T Q\mathbf v + \mathbf b^T \mathbf v + c , where Q = [ 2 4 5 4 4 6 5 6 6 ] Q = \begin{bmatrix} 2 & 4 & 5 \\ 4 & 4 & 6 \\ 5 & 6 & 6 \end{bmatrix} , b T = [ 14 16 18 ] \mathbf b^T = [14 \enspace 16 \enspace 18 ] and c = 20 c=20 .

Because det ( Q ) = 2 ( 4 6 6 6 ) 4 ( 4 6 6 5 ) + 5 ( 4 6 4 5 ) = 20 > 0 \det(Q) = 2(4\cdot6 - 6\cdot6) - 4(4\cdot6 - 6\cdot5) + 5(4\cdot6 - 4\cdot5) = 20 > 0 , so that Q Q has a positive eigenvalue; let x \mathbf x be a unit leading eigenvector with eigenvalue λ \lambda . Then W ( k x ) = λ k 2 + ( b T x ) k + c W(k x) = \lambda k^2 + (\mathbf b^T \mathbf x)k + c is quadratic function of k k with a positive leading coefficient, so W ( x , y , z ) W(x,y,z) fails to be bounded above. In other words, there is no maximum value of W ( x , y , z ) W(x,y,z) .


My method : To prove that is has no minimum value either.

Let's find the type of second-order algebraic surface , referencing this, we have

e = Q = 20 > 0 , Δ E = [ 2 4 5 7 4 4 6 8 5 6 6 9 7 8 9 20 ] = 140 , ρ 3 = rank e = 3 , ρ 4 = rank E = 4 e = Q = 20 > 0 , \quad \Delta E = \begin{bmatrix} 2&4&5&7 \\ 4&4&6&8 \\ 5 &6&6&9 \\ 7 & 8 & 9 & 20 \end{bmatrix} = 140, \rho_3 = \text{rank } e = 3, \rho_4 = \text{rank } E = 4

To find the roots of k 1 , k 2 , k 3 k_1,k_2,k_3 of [ 2 x 4 5 4 4 x 6 5 6 6 x ] = 0 \begin{bmatrix} 2-x & 4 & 5 \\ 4 & 4 -x & 6 \\ 5 & 6 & 6-x \end{bmatrix} = 0 so that we can determine the value of k k such that k : = { 1 if the signs of non-zero k ’s are the same 0 otherwise k := \begin{cases} 1 \quad \text{ if the signs of non-zero }k\text{'s are the same} \\ 0 \quad \text{ otherwise} \end{cases} .

and the roots to the equation below satisfy the condition x 3 + 12 x 2 + 33 x + 20 = 0 -x^3+12 x^2+33 x+20 = 0 . By Descartes' rule of signs , there is exactly one positive root to this cubic equation only (or just use WolframAlpha ). So k = 0 k = 0 . Comparing it with value in the Mathworld link as given above , we have

ρ 3 = 3 , ρ 4 = 4 , Δ E = 140 > 0 sgn Δ ( E ) + , k = 0 \rho_3 = 3 ,\quad \rho_4 = 4, \quad \quad \Delta E = 140 > 0 \Rightarrow \text{sgn} \Delta(E) \equiv + ,\quad \quad k = 0

to get a hyperboloid of one sheet. So both the domain and range of W ( x , y , z ) W(x,y,z) is R 3 \mathbb R^3 . Thus, there is no maximum nor minimum value for this function.


Follow-up questions :

( 1 ) Is my method correct too? (This is a rhetorical question)

( 2 ) Using your method, how do you prove that W ( x , y , z ) W(x,y,z) has no minimum value either?

( 3 ) Is it possible to use partial derivatives to show that W ( x , y , z ) W(x,y,z) has no minimum nor maximum value too? Because I know how to solve it for 2-dimensional functions , but I don't know any method for 3-dimensional functions or higher. If I recall correctly, there is something to do with Hessian matrix , but I'm not sure how to proceed. Thoughts? (Don't ask me to read that wikipedia page, it explains nothing to me)

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh Just a few quick remarks; I have limited time now (but will have more time later tonight).

I think the main point to make is that all the three methods ("yours", "mine", and the Hessian) are essentially the same: In each case we care about the eigenvalues of the same matrix (your values k 1 , k 2 , k 3 k_1,k_2,k_3 ). The Hessian is twice the matrix of the quadratic form. If that matrix has a negative eigenvalue, then the function fails to be bounded below, as I show in my solution.

The maximum of the function is not an issue. Just let y = z = 0 y=z=0 and you are left with 2 x 2 + 14 x + 20 2x^2+14x+20 , which fails to be bounded above.

Please let me know where you want to go from here.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Uggghhhh! I should have thought about y = z = 0 y=z=0 .

I̶'̶v̶e̶ ̶s̶p̶e̶n̶t̶ ̶w̶a̶y̶ ̶t̶o̶o̶ ̶m̶u̶c̶h̶ ̶t̶i̶m̶e̶ ̶t̶h̶i̶n̶k̶i̶n̶g̶ ̶a̶b̶o̶u̶t̶ ̶w̶r̶i̶t̶i̶n̶g̶ ̶u̶p̶ ̶a̶ ̶g̶o̶o̶d̶ ̶s̶o̶l̶u̶t̶i̶o̶n̶ ̶a̶n̶d̶ ̶y̶o̶u̶ ̶b̶e̶a̶t̶ ̶m̶e̶ ̶s̶o̶ ̶e̶a̶s̶i̶l̶y̶.̶

Y U SO SMART?!!?!?

If that matrix has a negative eigenvalue, then the function fails to be bounded below.

How do you prove this statement? Is the converse and/or inverse of this statement true as well?

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh The proof of "If that matrix has a negative eigenvalue, then the function fails to be bounded below" is in my solution: "Let x \mathbf{x} be a unit eigenvector with negative eigenvalue λ \lambda . Then f ( k x ) = λ k 2 + ( b T x ) k + c f(k\mathbf{x})=\lambda k^2+(\mathbf{b}^T\mathbf{x})k+c , a quadratic function in k k with negative leading coefficient, so that f f fails to be bounded below.

When all eigenvalues are positive, then we do indeed have a minimum, but when the smallest eigenvalue is 0 then it could go either way.

Given your youthful age, you are doing very well understanding this stuff, and you are making enormous progress. It took me a while to get it (more or less), and I'm still learning. Writing my linear algebra text made me really think about these things.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher

Let x \mathbf{x} be a unit eigenvector with negative eigenvalue λ \lambda .

Then f ( k x ) = λ k 2 + ( b T x ) k + c f(k\mathbf{x})=\lambda k^2+(\mathbf{b}^T\mathbf{x})k+c , a quadratic function in k k with negative leading coefficient, so that f f fails to be bounded below.

How does the first paragraph implies the second paragraph? I'm dumbfounded here...

Ditto this statement as well:

When all eigenvalues are positive, then we do indeed have a minimum, but when the smallest eigenvalue is 0 then it could go either way.

Pi Han Goh - 5 years, 2 months ago

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@Pi Han Goh Here is one way to think about it: After a change of coordinates, we can write the function as λ 1 ( u a ) 2 + λ 2 ( v b ) 2 + λ 3 ( w c ) 2 + d \lambda_1(u-a)^2+\lambda_2(v-b)^2+\lambda_3(w-c)^2+d , as long as none of the eigenvalues is 0. If all the eigenvalues are positive, then d d is the minimal value. But if one of them is negative, say λ 1 \lambda_1 , then we can make v = b v=b and w = c w=c to see that the function fails to be bounded below.

Otto Bretscher - 5 years, 2 months ago

@Pi Han Goh Another important point that makes life easier: We don't actually have to find the characteristic polynomial and the eigenvalues, thanks to Sylvester's Criterion : If there is a negative principal minor, then there will be a negative eigenvalue. In our case we can use the 2 x 2 minor in the top left, which is -8. We can also see this directly: If we let y = x y=-x and z = 0 z=0 , the function becomes 2 x 2 + -2x^2+ (lower terms), which fails to be bounded below.

Otto Bretscher - 5 years, 2 months ago

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@Otto Bretscher Great! I learned something new todayyyyyy Thankyouuuuu

Pi Han Goh - 5 years, 2 months ago

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