Proving an Inequality with Elementary Methods

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Homework Help Overview

The problem involves proving an inequality related to a product of terms defined by real numbers \(x_1, x_2, \ldots, x_n\) that are constrained by the conditions \(0 \leq x_1 \leq x_2 \leq \ldots \leq x_n\) and \(x_1 + x_2 + \ldots + x_n = 1\). The inequality to be proven is \((1+x_1^2 1^2)(1+x_2^2 2^2) \ldots (1 + x_n^2 n^2) \geq \frac{2n^2+9n+1}{6n}\).

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation, Assumption checking

Approaches and Questions Raised

  • Participants discuss various methods to approach the problem, including the use of known inequalities like the Cauchy-Schwarz inequality and the arithmetic-geometric mean inequality. Some participants suggest numerical optimization methods and explore the implications of equal distributions of \(x_i\). Others question the assumptions about the values of \(x_i\) and their implications for the inequality.

Discussion Status

The discussion is ongoing, with participants exploring different lines of reasoning and mathematical approaches. Some have proposed potential lower bounds for the product, while others are questioning the validity of certain assumptions and interpretations. There is no explicit consensus on a single approach yet, but several productive directions have been identified.

Contextual Notes

Participants note that all \(x_i\) are non-negative and that the problem is situated within a precalculus context, which influences the methods considered appropriate for solving it. There is also mention of constraints regarding the values of \(x_i\) and their relationships to one another.

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Homework Statement



Let 0 ≤ x_1 ≤ x_2 ≤ ... ≤ x_n and x_1 + x_2 + ... + x_n = 1 , All the 'x' are real and n is a natural number. Prove the following:

(1+x_1^21^2)(1+x_2^22^2)...(1 + x_n^2n^2) ≥ \frac{2n^2+9n+1}{6n}


Homework Equations




The Attempt at a Solution



Well...all I managed to do was to "check the field a little". First of all, the right member of the inequality somehow reminds me of the sum:

1^2 + 2^2 + ... + n^2 = \frac{n(n+1)(2n+1)}{6} = \frac{(n+1)(2n^2 + 3n + 1)}{6}

I know from experience that we can solve this type of exercises by using some well-know inequalities such as the one that relates the average mean with the geometric one, or the Cauchy-Buniakowski-Schwarz ( C-B-S ). So:

1 ≥\frac{1}{n} ≥ \sqrt[n]{x_1x_2...x_n} , so it follows immediately that : x_1x_2...x_n ≤ 1

That's all I could do. Could you help me continue, please? This exercise has been stuck in my head for two weeks already. I can't solve it alone, and I would like that somebody could guide me to the solution. Thank you!
 
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DorelXD said:

Homework Statement



Let x_1 ≤ x_2 ≤ ... ≤ x_n and x_1 + x_2 + ... + x_n = 1 , All the 'x' are real and n is a natural number. Prove the following:

(1+x_1^21^2)(1+x_2^22^2)...(1 + x_n^2n^2) ≥ \frac{2n^2+9n+1}{6n}


Homework Equations




The Attempt at a Solution



Well...all I managed to do was to "check the field a little". First of all, the right member of the inequality somehow reminds me of the sum:

1^2 + 2^2 + ... + n^2 = \frac{n(n+1)(2n+1)}{6} = \frac{(n+1)(2n^2 + 3n + 1)}{6}

I know from experience that we can solve this type of exercises by using some well-know inequalities such as the one that relates the average mean with the geometric one, or the Cauchy-Buniakowski-Schwarz ( C-B-S ). So:

1 ≥\frac{1}{n} ≥ \sqrt[n]{x_1x_2...x_n} , so it follows immediately that : x_1x_2...x_n ≤ 1

That's all I could do. Could you help me continue, please? This exercise has been stuck in my head for two weeks already. I can't solve it alone, and I would like that somebody could guide me to the solution. Thank you!

Are all the ##x_i \geq 0?##
 
Yes, they are. I also modified the first post, by adding this fact.
 
Can you help me ? Do you have any idea :D ?
 
This is under precalculus. If calculus methods are permitted I would use Lagrange multipliers.
 
You can make elementary (non calculus) arguments that the left side of the inequality is ≥ (1+n). Then, you can get the rest by algebra.
 
DorelXD said:
Yes, they are. I also modified the first post, by adding this fact.

One can solve the optimization problem
\min \sum_{i-1}^n \log(1 + i^2 x_i^2) \\<br /> \text{subject to}\\<br /> x_1 + x_2 + \cdots + x_n = 1 \\<br /> 0 \leq x_1 \leq x_2 \leq \cdots \leq x_n
using a numerical optimization package for various small to medium values of n (3 ≤ n ≤ 10). In all cases I tried the optimal solution is ##x_1 = x_2 = \cdots = x_n = 1/n##. Furthermore, this can be shown to be a so-called Kuhn-Tucker point for the problem with general n. The minimization objective is pseudo-convex and the constraint set is convex, so satisfying the Karush-Kuhn-Tucker conditions is, I believe, sufficient for a (global) minimum.

In other words, we have
(1+1^2 x_1^2)(1 + 2^2 x_2^2) \cdots (1+ n^2 x_n^2) <br /> \geq (1 + (1/n)^2)(1+(2/n)^2) \cdots (1 + (n/n)^2)
for all feasible x. Maybe that can be manipulated further to give the desired result.
 
PAllen said:
This can be really simple. You have a product of terms. Are they all ≥ 1 even for xi=0? Can the nth x term value ever be < 1/n, given the other constraints? This is enough to prove the product ≥ (1+n). Then the rest follows by algebra. This is a pre-calculus problem not expected to be solved with software packages. Let's not kill a mosquito with canon.
This is confusing. 'n' is the number of terms, so the nth term means just the last term. Certainly xn >= 1/n, so the last term is at least 2. I don't see how you get it's at least 1+n.
If you meant a more generic n, I still don't see it. xj need not be ≥ 1/j, nor 1/n. Every xj except xn could be zero.
 
haruspex said:
This is confusing. 'n' is the number of terms, so the nth term means just the last term. Certainly xn >= 1/n, so the last term is at least 2. I don't see how you get it's at least 1+n.
If you meant a more generic n, I still don't see it. xj need not be ≥ 1/j, nor 1/n. Every xj except xn could be zero.

Sorry, I realized my mistake as soon as finished, and was working on deleting my post. I missed that the x's were squared as well as the i's. Oops.
 
  • #10
Ray Vickson said:
In all cases I tried the optimal solution is ##x_1 = x_2 = \cdots = x_n = 1/n##.

Suppose xj < xj+1 for some j < n. It might be straightforward to show that substituting xj' = xj+1' = (xj + xj+1)/2 produces a lower product. (Calculus by the back door.)
 
  • #11
PAllen said:
Sorry, I realized my mistake as soon as finished, and was working on deleting my post. I missed that the x's were squared as well as the i's. Oops.
Yeah, I've been there - a frantic dash to delete a regretted post, only to find it's already been read:redface:.
 
  • #12
haruspex said:
Suppose xj < xj+1 for some j < n. It might be straightforward to show that substituting xj' = xj+1' = (xj + xj+1)/2 produces a lower product. (Calculus by the back door.)

Unfortunately, this is not true. The substitution produces a larger product. Larger by the difference between xj and its successor, over 2, squared.
 
  • #13
PAllen said:
Unfortunately, this is not true. The substitution produces a larger product. Larger by the difference between xj and its successor, over 2, squared.
Hmm.. I just tried it and it worked for me. I ended up needing that 1 > j(j+1)xjxj+1, which is clearly true.
 
  • #14
haruspex said:
Hmm.. I just tried it and it worked for me. I ended up needing that 1 > j(j+1)xjxj+1, which is clearly true.

A much easier way to get a lower bound is to note that for positive ##y_i = i^2 x_i^2## we have
(1+y_1)(1+y_2) \cdots (1+y_n) &gt; 1 + \sum_{i=1}^n y_i,
because the RHS is just the first two terms in the expansion of the product, and all the omitted terms are > 0. Therefore, we can get a lower bound by solving the relatively simple problem
\min \sum_{i=1}^n i^2 x_i \:\:\:\leftarrow \sum_{i=1}^n y_i\\<br /> \text{subject to}\\<br /> \sum_{i=1}^n x_i = 1\\<br /> 0 \leq x_1 \leq x_2 \leq \cdots \leq x_n
This problem has the optimal solution ##x_1 = x_2 = \cdots = x_n = 1/n##, so we have
(1+1^2 x_1^2)(1+2^2 x_2^2) \cdots (1 + n^2 x_n^2) &gt; 1 + \sum_{i=1}^n i^2/n^2
for all feasible ##x_1, x_2, \ldots x_n##.
 
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  • #15
haruspex said:
Hmm.. I just tried it and it worked for me. I ended up needing that 1 > j(j+1)xjxj+1, which is clearly true.

I keep forgetting the squaring.
 
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  • #16
Ray Vickson said:
A much easier way to get a lower bound is to note that for positive ##y_i = i^2 x_i^2## we have
(1+y_1)(1+y_2) \cdots (1+y_n) &gt; 1 + \sum_{i=1}^n y_i,
because the RHS is just the first two terms in the expansion of the product, and all the omitted terms are > 0. Therefore, we can get a lower bound by solving the relatively simple problem
\min \sum_{i=1}^n i^2 x_i \:\:\:\leftarrow \sum_{i=1}^n y_i\\<br /> \text{subject to}\\<br /> \sum_{i=1}^n x_i = 1\\<br /> 0 \leq x_1 \leq x_2 \leq \cdots \leq x_n
This problem has the optimal solution ##x_1 = x_2 = \cdots = x_n = 1/n##, so we have
(1+1^2 x_1^2)(1+2^2 x_2^2) \cdots (1 + n^2 x_n^2) &gt; 1 + \sum_{i=1}^n i^2/n^2
for all feasible ##x_1, x_2, \ldots x_n##.

This seems promising. This lower bound appears to equal the RHS. If this could be proven (along with the rest), you'd be done.
 
  • #17
Ray Vickson said:
A much easier way to get a lower bound is to note that for positive ##y_i = i^2 x_i^2## we have
(1+y_1)(1+y_2) \cdots (1+y_n) &gt; 1 + \sum_{i=1}^n y_i,
because the RHS is just the first two terms in the expansion of the product, and all the omitted terms are > 0. Therefore, we can get a lower bound by solving the relatively simple problem
\min \sum_{i=1}^n i^2 x_i \:\:\:\leftarrow \sum_{i=1}^n y_i\\<br /> \text{subject to}\\<br /> \sum_{i=1}^n x_i = 1\\<br /> 0 \leq x_1 \leq x_2 \leq \cdots \leq x_n
This problem has the optimal solution ##x_1 = x_2 = \cdots = x_n = 1/n##, so we have
(1+1^2 x_1^2)(1+2^2 x_2^2) \cdots (1 + n^2 x_n^2) &gt; 1 + \sum_{i=1}^n i^2/n^2
for all feasible ##x_1, x_2, \ldots x_n##.

We need the proof for this in elementary terms.
If this is proven, the problem is basically solved.

Edit: I just saw that the x_i had to be positive. Then, the proof is obviously very easy.
The sum \displaystyle \sum_{i=1}^n i^2/n^2 has closed form \displaystyle \frac{(n+1)(2n+1)}{6n}. The inequality then follows from the optimal solution.
 
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