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Let $\ell$ be a positive integer greater than 1. The problem is to find a set of $n$ real positive numbers $x_i$ and $n+1$ numbers $y_i$ such that $$\sum_{i=1}^n x_i^k= \sum_{i=1}^{n+1} y_i^k$$ for $k=\ell,\cdots,2\ell-1$. These $2n+1$ numbers need to be upper/lower bounded by a constant independent of $\ell$ [thus $x_i,y_i=\Theta(1)$] and also I suspect that it is possible to do so with just $n=\ell$ or $n=O(\ell)$. [$\ell$ equations with $2\ell$ unknowns, why not!] An existential proof suffices but a constructive proof or a recipe would be really nice.

For me it is useful to find a bounded from below solution that scales in polynomially in the following sense: There exist positive $c$, and $s$ such that $c\le x_i,y_i$ and $$\sum_i x_i+\sum_i y_i=O(\ell^s)$$.

The problem is related to a follow up on this paper of mine: arxiv:0908.1526 .

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  • $\begingroup$ Can you provide some motivation? $\endgroup$ Commented Nov 16, 2009 at 6:42
  • $\begingroup$ Are you aware that n+1 consecutive power sums uniquely determine n+1 numbers up to permutation? $\endgroup$ Commented Nov 16, 2009 at 7:08
  • $\begingroup$ I also don't understand which variables you want to make large and which you want to keep fixed, nor do I understand the extent to which you don't want x_i = y_i, y_{n+1} = 0 to be a valid solution. $\endgroup$ Commented Nov 16, 2009 at 7:22
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    $\begingroup$ I guess the question is "Do there exist C, 0 < C_1 < C_2 such that for every l, there exists n < Cl and C_1 < x_i, y_i < C_2 such that ..." $\endgroup$ Commented Nov 16, 2009 at 7:35
  • $\begingroup$ Thanks for the comments: I am not sure about n+1 consecutive power sums uniquely determining n+1 numbers. I guess it depends on the number of variables in the sum, right? The number of variables is n+1 on one side and n on the other side. I want to keep all of them neither too small nor too large, preferably between 1 and 2! I think Reid got it right, with his quantifier statement. The number of them will have to scale nicely with the number of equations [the powers l to 2l-1]. $\endgroup$ Commented Nov 16, 2009 at 8:37

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Actually Darsh gave an almost full solution. Let me fill in the minor technical details.

1) We need the following quantitative form of the inverse function theorem. Suppose that $F:\mathbb R^n\to \mathbb R^n$. Assume also that $\|DF(X)^{-1}\|\le C_1$, that $\max_{Y\in B(X, \delta)}\|D^2F(Y)\|\le C_2$, and that $C_1C_2\delta\le\frac 12$. Then $F(B(X,\delta))\supset B(F(X),\frac{\delta}{2C_1})$.

2) Take $n=2\ell-1$ and consider the mapping $F:\mathbb R^n\to \mathbb R^n$ given by $F(y_1,\dots,y_n)_k=\sum_{j=1}^n y_j^k$ where $k=1,2,\dots,n$. Take $X=(x_1,\dots,x_n)$ where $x_j=\frac{n+j}{n}$ for $j=1,\dots,n$.

3) Note that in $B(X,1)$, we have $\|D^2F\|\le A^n$ for some absolute $A>1$.

4) Note also that $DF(X)^*$ is the linear operator that maps the vector $(c_1,\dots,c_n)$ to the vector $p(x_1),\ldots,p(x_n)$ consisting of the values of the polynomial $p(x)=\sum_{k=1}^n c_k kx^{k-1}$. The inverse operator is given by the standard interpolation formula, which allows us to estimate its norm by $B^n$ with some absolute $B>1$.

5) Thus, taking $\delta=2^{-1}(AB)^{-n}$, we conclude that the image of the ball $B(X,\delta)$ contains a ball of radius $\frac\delta{2A^n}\ge C^{-n}$ with some absolute $C>2$.

6) In particular, it contains two points with the difference $(0,0,\dots,0,D^{-\ell},D^{-(\ell+1)},\dots,D^{-(2\ell-1)})$ with some absolute $D>1$, which is equivalent to what we need.

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    $\begingroup$ Nice solution! And I think that working out those bounds were more than technical details. $\endgroup$ Commented Nov 23, 2009 at 16:12
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    $\begingroup$ To see whether I understand this: This solution produces xs and ys inside some fixed interval, as in the original problem? And it's essentially that the power sums we want to be equal start at Ω(n) and not at 1, as shown by David's argument? $\endgroup$ Commented Nov 23, 2009 at 20:24
  • $\begingroup$ @Reid: Yes, both points you made are correct. $\endgroup$
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  • $\begingroup$ @fedja and the rest: I am convinced that you solved the problem and your answer is not only very nice but also very instructive. Is there a way to appreciate your work in what I will be writing up later? The context is an open loop (quantum or classical) control problem for which I required the existence of these numbers as a step in a recipe. I could acknowledge mathoverflow.net but that won't be sufficient in this case, I think. $\endgroup$ Commented Nov 24, 2009 at 19:08
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Maybe the following is useful: first pick arbitrary distinct positive numbers $y\_1,\ldots,y\_n$. Note that $(y\_1,\ldots,y\_n,y\_1,\ldots,y\_n,0)$ is a solution to your system for all $l$; however, the last component is zero, so it doesn't fit your constraints. To remedy this, fix $l=n$ and define $F:\mathbb{R}^{n+1}\to\mathbb{R}^n$ by $$F(a_1,\ldots,a\_n,b)\_k = \sum\_{i=1}^n(a\_i + y\_i)^{k+n-1} - b^{k+n-1} - \sum\_{i=1}^n y\_i^{k+n-1}.$$ Note that $F(0) = 0$ and $$\frac{\partial F\_k}{\partial a\_i} = (k+n-1)(a\_i+y\_i)^{k+n-2},$$ so $$ \begin{align*}\frac{\partial F\_k}{\partial a} &= \begin{bmatrix}n(a\_1 + y\_1)^{n-1} & \cdots & n(a\_n + y\_n)^{n-1} \\\\ \vdots & \ddots & \vdots \\\\ (2n-1)(a\_1 + y\_1)^{2n-2} & \cdots & (2n-1)(a\_n + y\_n)^{2n-2}\end{bmatrix} \\\\ &= \begin{bmatrix}n & & \\\\ & \ddots & \\\\ & & 2n-1\end{bmatrix} \begin{bmatrix}1 & \cdots & 1 \\\\ \vdots & \ddots & \vdots \\\\ (a\_1 + y\_1)^{n-1} & \cdots & (a\_n + y\_n)^{n-1}\end{bmatrix} \begin{bmatrix}(a\_1 + y\_1)^{n-1} & & \\\\ & \ddots & \\\\ & & (a\_n + y\_n)^{n-1}\end{bmatrix} \\\\ &= D\_1V(a\_1+y\_1,\ldots,a\_n+y\_n)D\_2, \end{align*}$$ where $D\_1$ and $D\_2$ are nonsingular diagonal matrices and $V(a\_1+y\_1,\ldots,a\_n+y\_n)$ is a Vandermonde matrix, which is nonsingular for all $(a\_1,\ldots,a\_n)$ sufficiently close to zero since $y\_1,\ldots,y\_n$ are distinct. Thus, by the implicit function theorem, for all $b$ sufficiently close to zero, there is a solution $(y\_1+a\_1,\ldots,y\_n+a\_n,y\_1,\ldots,y\_n,b)$ to your system. It should be easy to derive the bounds you require. Morally, though, taking $n=l$ gives you way too many degrees of freedom; you should be able to get away with much smaller $n$.

Afterthoughts: The problem with the above is that $b$ might need to be taken arbitrarily close to zero as $l$ increases. Since $n=l$ in this argument, if the points $x\_i$ and $y\_i$ also need to be bounded, then this means all the points can't be bounded away from one another as $l$ grows, and the Vandermonde matrix will become increasingly badly conditioned. (I didn't check that rigorously, but the heuristic argument seems pretty convincing.) I don't know how much any of that depends on how $y\_1,\ldots,y\_n$ are chosen. I've made this a community wiki post in case someone can fix the argument or prove that it doesn't work.

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  • $\begingroup$ It seems to me that what you are suggesting might work. Let me give it some more thought in the bright hours. I would really be interested in getting those $\ell$ equations using less than $O(\log(\ell))$ variables but I doubt that it would work. I understand though, if there was no requirement for them to be positive then there would be always be a trivial solution with just 1+2 variables total, $\endgroup$ Commented Nov 16, 2009 at 8:39
  • $\begingroup$ Thanks again, Darsh. I checked the details one more time and I think the implicit function theorem gives me intervals so I can make sure that $y_i+a_i$ and $b$ are all positive. In fact, I was looking at $n=2$ case [I have a bunch of numerical solutions] with $x_1=a,x_2=a,x_3=1$ for which determines $y_1,y_2$ uniquely and looked at the behavior of the solutions. In that case the space was indeed too degenerate but still I could see that $(y_1,y_2)$ turned out to be a continuous function of $a$. $\endgroup$ Commented Nov 16, 2009 at 18:35
  • $\begingroup$ I see that you've accepted this answer. Did you get the bounds you needed? After I looked at it again, it didn't look so straightforward, especially since as $l$ increases, you're going to be picking more and more numbers from some bounded region, so they can't all be far apart from one another. That might force you to make the "$b$" variable pretty close to zero, and I don't know how to tell how close without actually doing the calculations. $\endgroup$ Commented Nov 16, 2009 at 18:38
  • $\begingroup$ I could always scale the whole set so if I have a positive solution, I can make it as large as I want... Actually keeping them bounded both ways is harder. So, I would have to upper bound a_i first ... I don't think we need to have all of the numbers distinct, in fact I just need the derivative matrix to have nonzero rank, I think. If that is indeed the case, maybe I can lower \ell while I keep the rank nonzero, or something like that. I did mark it as resolved, because it provides the existential argument, which is sufficient for supporting a claim... $\endgroup$ Commented Nov 16, 2009 at 19:24
  • $\begingroup$ I don't follow how this is supposed to work. The variable b has to be close to 0 for the implicit function theorem to apply, and we were asked to make b be Theta(1). Of course, we can scale b up to be 1, but then the other numbers will be too big. $\endgroup$ Commented Nov 16, 2009 at 19:56
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It is not possible to solve these equations/inequalities. EDIT: I am analyzing the version where the power sums start at $k=1$, not the original where they start al $k=\ell$. Thanks to Greg Kuperberg and Reid Barton for pointing this out.

Lemma: There is a constant $A>0$, and a sequence of polynomials $T_d(x)$ of degree $d$, such that $|T_d(x)| \leq 1$ on $[C_1, C_2]$, and $|T_d(0)| \geq e^{Ad}$.

Proof: The easiest proof is to take $T_d(x) = \lambda(x)^d$, where $\lambda$ is the linear function such that $\lambda(C_1) =1$ and $\lambda(C_2) = -1$. I think you'll get slightly tighter bounds if you take $T_d(x)$ to be an appropriately normalized Chebyshev polynomial. ❚

Now, suppose we had $2n+1$ numbers in $[C_1, C_2]$ such that $\sum x_i^k = \sum y_i^k$ for $1 \leq k \leq d$. Consider $$\sum_{i=1}^{n+1} T(x_i) - \sum_{i=1}^n T(y_i) \quad (*).$$

On the one hand, $(*)$ is a sum of $2n+1$ terms, each of which are $O(1)$, so it is $O(n)$.

On the other hand, if we write out $T_d$ as a polynomial and group terms of like degree, everything cancels but the constant term. So $(*)$ is $$(n+1) T(0) - n T(0) = T(0) \leq e^{Ad}$$.

So $e^{Ad} = O(n)$ and $d = O(\log n)$. Thus, we can only hope to get $\log n$ many power sums to match up.

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    $\begingroup$ But the exponents begin at $k = \ell$, not at $k = 1$. $\endgroup$ Commented Nov 18, 2009 at 5:57
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    $\begingroup$ That is for your modification of the problem right? For the original problem I need polynomials T_l which only have coefficients of 1 and x^j, l <= j <= 2l-1? $\endgroup$ Commented Nov 18, 2009 at 6:11
  • $\begingroup$ Thanks, you are both right. If I have time later today, I'll think about making the polynomial have the coefficients in question. $\endgroup$ Commented Nov 18, 2009 at 12:57
  • $\begingroup$ I have a simple idea that I am just sharing: Consider $f(p)=\sum_i x_i^p-\sum_i y_i^p$. Obviously $f(p)$ will eventually blow up or down for large enough p. Can we size the region [in $p$'s] over which this does not occur, if $x,y,z=\Theta(1)$ and prove that it is logarithmically small with respect to $n$? This would imply that the range of integers $k$ in those ranges of $p$ will also be limited by $log(n)$? $\endgroup$ Commented Nov 18, 2009 at 17:43
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I thought about this a bit and didn't get anywhere. I'm just posting to point out that the following problem appears to contain the fundamental difficulties of the original, while eliminating some of the irritating details:

Do there exist $0 &lt;r &lt; 1$ and $0 &lt; c &lt; 1$ such that, for every (or infinitely many) $n$, there are $n-1$ complex numbers $u\_1$, $u\_2$, ..., $u\_{n-1}$ and $n$ other complex numbers $v\_1$, $v\_2$, ..., $v\_n$, with $|u\_i|$, $|v\_i| &lt; r$ and $$1+\sum_i u\_i^k = \sum\_i v\_i^k \quad (*)$$ for $0 \leq k \leq cn$?

This problem is easier in that we are allowed to use complex numbers rather than real ones. It is harder in that $(*)$ has to hold for all sufficiently small values of $k$, rather than $\ell \leq k \leq 2 \ell-1$. Therefore, there is no direct reduction either way.

There is also an aesthetic change (improvement, to my mind). I made the change of variables $u\_i = 1-x\_i$ and $v\_i = 1-y\_i$. This made the extra $1$ appear on the left hand side: conceptually, it is $(1-0)^k$. As a result, I now am asking for my solutions to be in a disc around $0$, and $(*)$ is valid for $k=0$.

My bet is that the answer is "no". But I'd like to see a proof.

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  • $\begingroup$ Thanks David for the new problem! It does seem like a tight problem now that I have spent about a week on it. I might try tweaking my setup to see either I can get something more general to disprove or something more specific to get the solutions on. In general, I just need x_i,y_i, and their sum [and thus their number] to be bounded from below independent of \ell and from above by a polynomial in \ell. This will still give me the semi-super-exponential improvements that I am looking for in my original problem. I might look at alternative solution to the original as well. $\endgroup$ Commented Nov 17, 2009 at 15:00
  • $\begingroup$ David, if you take the original power sum setting for n and n+1 variables, then if you have all the equations for 1<k<\ell then you can reduce them to equalities about roots of two polynomials of degrees n and n+1 [as people pointed out above, using Newton's identities] and subsequently two polynomials with common coefficients except one having one degree higher with roots that are all larger in modulus than 1 ... $\endgroup$ Commented Nov 17, 2009 at 16:13
  • $\begingroup$ Right. And it is convenient to multiply one polynomial by x, so that they have the same degree. So another version of the problem is: do there exist r and c such that, for every n, there are polynomials f and g, of degree n, such that f(1)=0, all the roots of f(z)/(z-1) and of g(z) lie in |z| &lt; 1, and f-g has degree cn. $\endgroup$ Commented Nov 17, 2009 at 16:17

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