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Tackling an eigenvalue inequality

The International Mathematics Competition for University Students (IMC) is an annual competition generally hosted in Bulgaria. The paper consists of 10 problems, split between two sessions. This year, problem 8 was an inequality involving the eigenvalues of a real symmetric matrix. The statement reads as follows:

Problem 8. Let n5n \geq 5, and suppose that A=(aij)A=\left(a_{i j}\right) is a real symmetric n×nn \times n matrix such that

aii=0 and aij{1,1} for ij.a_{i i}=0 \quad \text { and } \quad a_{i j} \in\{-1,1\} \text { for } i \neq j .

Assume that the scalar products of any two distinct rows of AA have the same value. Let λ1,,λn\lambda_1, \ldots, \lambda_n be the eigenvalues of AA. Prove that

i=1nλi2n2\sum_{i=1}^n\left|\lambda_i\right| \geq 2 n-2

and determine all matrices for which equality holds.

At first glance, the problem looked quite approachable, especially for me, who needs to brush up on linear algebra. Here's my thought process.

Solution. Well, the diagonal entries are nil, which means that the trace of AA is zero. At least we know that the sum of the eigenvalues is zero. The condition on the scalar product of any two distinct rows did not appear immediately clear to me, until I realized that it implies that:

AA=[n1kkkn1kkkn1]A'A = \begin{bmatrix} n-1 & k & \cdots & k \\ k & n-1 & \cdots & k \\ \vdots & \vdots & \ddots & \vdots \\ k & k & \cdots & n-1 \end{bmatrix}

where kk is the common value of the scalar products of any two distinct rows of AA. Note that the diagonal elements are equal to n1n-1 since aii=0a_{ii}=0 and aij2=1a_{ij}^2=1 for iji\neq j. Also, it has to be the case that kn2k\leq n-2, since different rows have exactly one zero element in different positions. The matrix AAA'A looks nice, so I guessed that there should be an explicit formula for its determinant and we could infer its eigenvalues, which end up being the squares of the eigenvalues of AA! This is the core of the steps below.

Claim 1. The eigenvalues of AAA'A are (n1)(k+1)(n-1)(k+1) with multiplicity 1 and nk1n-k-1 with multiplicity n1n-1.

Proof. A sort of brute force to verify this is to find the characteristic polynomial inductively. Let us simplify the problem a bit. Consider the matrix:

Bm×m=[a111a111a]B_{m \times m}= \begin{bmatrix} a & 1 & \cdots & 1 \\ 1 & a & \cdots & 1 \\ \vdots & \vdots & \ddots & \vdots \\ 1 & 1 & \cdots & a \end{bmatrix}

and we prove by induction on mm that detB=(a1)m1(a+m1)\det B = (a-1)^{m-1}(a+m-1). The base cases follow straightforwardly when we set m=2m=2 and m=3m=3. As inductive hypothesis, assume the expression above is true and we prove it also holds for m+1m+1. This is not hard, as we can use the Laplace expansion on the first row of BB:

B=a(a1)m1(a+m1)+i=2m+1C1i|B|= a(a-1)^{m-1}(a+m-1) + \sum_{i=2}^{m+1}C_{1i}

where C1iC_{1i} is the cofactor of the ii-th element on the first row of BB. However, we realize that all these cofactors are equal to (a1)m1-(a-1)^{m-1} because the submatrices they are determinants of are row permutations of each other. As a result:

B=a(a1)m1(a+m1)m(a1)m1=(a1)m1(a(a+m1)m)=(a1)m1(a+m)(a1)=(a1)m(a+m)\begin{align*} |B| &= a(a-1)^{m-1}(a+m-1) - m (a-1)^{m-1}\\ &= (a-1)^{m-1}(a(a+m-1)-m)\\ &= (a-1)^{m-1}(a+m)(a-1)\\ &= (a-1)^{m}(a+m) \end{align*}

as desired. Now, we can use this result to find the eigenvalues of AAA'A. Setting a=n1ka=\frac{n-1}{k} and m=nm=n, we get after rescaling accordingly:

det(AAλIn)=(1)n(λ(n1)(k+1))(λ(nk1))n1\det{(A'A-\lambda I_n)} = (-1)^n(\lambda - (n-1)(k+1))(\lambda - (n-k-1))^{n-1}

which implies the required assertion. \square

The above proof is correct and all, but it is not the most elegant one, if you ask me. A cleaner one can be found if we note that AAA'A can be expressed as AA=(nk1)In+kJnA'A=(n-k-1)I_{n} + k J_{n} where JnJ_n is the all-ones matrix. The eigenvalues of kJnkJ_n are 00 with multiplicity n1n-1 and knkn with multiplicity 1. Shifting these values by nk1n-k-1 gives us the eigenvalues of AAA'A, as required. Short and beautiful, isn't it?

Anyway, the problem reduces to proving the inequality for the eigenvalues, which we now know. Using our Claim 1, we learn that

i=1nλi=(n1)(k+1)+(n1)nk12(n1)3/2[(nk1)(k+1)]1/22(n1)\begin{align*} \sum_{i=1}^n|\lambda_i| &= \sqrt{(n-1)(k+1)} + (n-1)\sqrt{n-k-1} \\ &\geq 2 \sqrt{(n-1)^{3/2}\left[(n-k-1)(k+1)\right]^{1/2}} \\ &\geq 2(n-1) \end{align*}

where the inequality in the second row follows from the celebrated AM-GM inequality, and the third line comes from the fact that for 0kn20 \leq k \leq n-2, we have (nk1)(k+1)n1(n-k-1)(k+1) \geq n-1. (Note that since AAA'A is positive semi-definite, its eigenvalues are non-negative, so k1k \geq -1. In the edge case where k=1k=-1, the sum of absolute eigenvalues is (n1)n(n-1)\sqrt{n}, which is strictly greater than 2(n1)2(n-1) for n5n \geq 5). We are so done!

Not so fast, my friend! We need to find all the matrices for which the equality holds. The AM-GM inequality gives an equality if and only if both terms are equal, that is, (n1)(k+1)=(n1)nk1\sqrt{(n-1)(k+1)} = (n-1)\sqrt{n-k-1}. Squaring both sides and dividing by n1n-1 (since n5n \geq 5) yields k+1=(n1)(nk1)k+1 = (n-1)(n-k-1), which simplifies to n(nk2)=0n(n-k-2) = 0. This implies equality holds exactly when k=n2k=n-2.

What does a matrix with k=n2k=n-2 look like? The scalar product of any two distinct rows ii and jj is the sum of n2n-2 terms of the form aimajma_{im}a_{jm} (since aii=ajj=0a_{ii}=a_{jj}=0). Because aij{1,1}a_{ij} \in \{-1, 1\}, the only way this sum can reach n2n-2 is if aimajm=1a_{im}a_{jm} = 1 for all mi,jm \neq i,j, meaning aim=ajma_{im} = a_{jm}. Using the symmetry of AA, this forces all off-diagonal entries of AA to be identical. Hence, the only matrices for which equality holds are A=JnInA = J_n - I_n and A=(JnIn)A = -(J_n - I_n). \square

Interested in more problems? You can find the full paper for IMC 2026 and other years here (opens in a new tab). {: .prompt-tip }