John Jasper
South Dakota State University
Theorem. If \(\Delta\) is a right triangle with side lengths \(c\geq b\geq a\), then \[a^{2}+b^{2}=c^{2}.\]
\(a\)
\(b\)
\(c\)
Theorem. If \(v\) and \(w\) are orthogonal vectors, then \[\|v\|^2 + \|w\|^2 = \|v+w\|^2.\]
\(v\)
\(w\)
\(v+w\)
Theorem. If \(v_{1},v_{2},\ldots,v_{k}\) are pairwise orthogonal vectors, then
\[\|v_{1}\|^2 + \|v_{2}\|^2 + \cdots + \|v_{k}\|^{2} = \|v_{1}+v_{2}+\cdots+v_{k}\|^2.\]
Similar Triangles!
\[\|(I-P)e_{2}\| = \|Pe_{1}\|\]
\[\|Pe_{1}\|^{2} + \|Pe_{2}\|^{2} = 1\]
Theorem. If \(P\) is an orthogonal projection onto a \(1\)-dimensional subspace \(V\), and \(\{e_{1},e_{2},\ldots,e_{n}\}\) is an orthonormal basis, then
\[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = 1.\]
Proof.
\(\Box\)
If \(P\) is an orthogonal projection onto a subspace \(V\), and \((e_{i})_{i=1}^{n}\) is an orthonormal basis, then
\[\|Pe_{i}\|^{2} = \langle Pe_{i},Pe_{i}\rangle = \langle P^{\ast}Pe_{i},e_{i}\rangle = \langle P^{2}e_{i},e_{i}\rangle = \langle Pe_{i},e_{i}\rangle\]
\[ = \left[\begin{array}{cccc} \|Pe_{1}\|^{2} & \ast & \cdots & \ast\\ \overline{\ast} & \|Pe_{2}\|^{2} & & \vdots\\ \vdots & & \ddots & \vdots\\ \overline{\ast} & \cdots & \cdots & \|Pe_{n}\|^{2}\end{array}\right] \]
\[P= \left[\begin{array}{cccc} \langle Pe_{1},e_{1}\rangle & \langle Pe_{2},e_{1}\rangle & \cdots & \langle Pe_{n},e_{1}\rangle \\ \langle Pe_{1},e_{2}\rangle & \langle Pe_{2},e_{2}\rangle & & \vdots\\ \vdots & & \ddots & \vdots\\ \langle Pe_{1},e_{n}\rangle & \cdots & \cdots & \langle Pe_{n},e_{n}\rangle \end{array}\right]\]
Theorem. If \(P\) is an orthogonal projection onto a \(1\)-dimensional subspace \(V\), and \(\{e_{1},e_{2},\ldots,e_{n}\}\) is an orthonormal basis, then
\[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = 1.\]
Proof. \[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = \text{tr}(P) = \dim V = 1.\]
\(\Box\)
Theorem. If \(P\) is an orthogonal projection onto a \(k\)-dimensional subspace \(V\), and \(\{e_{1},e_{2},\ldots,e_{n}\}\) is an orthonormal basis, then
\[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = k.\]
Proof. \[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = \text{tr}(P) = \dim V = k.\]
\(\Box\)
Theorem. If \(P\) is an orthogonal projection onto a \(k\)-dimensional subspace \(V\), and \(\{e_{1},e_{2},\ldots,e_{n}\}\) is an orthonormal basis, then
\[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = k.\]
Proof. \[\sum_{i=1}^{n}\|Pe_{i}\|^{2} = \text{tr}(P) = \dim V = k.\]
\(\Box\)
Corollary. If \(P\) is an orthogonal projection matrix onto a \(k\)-dimensional subspace, and \((d_{i})_{i=1}^{n}\) is the sequence on the diagonal of \(P\), then
\(d_{i}\in[0,1]\) for each \(i\), and
\[\sum_{i=1}^{n}d_{i} \in\Z\]
Theorem. If \(\Delta\) is a triangle with side lengths \(c\geq b\geq a\), such that
\(a^{2}+b^{2}=c^{2},\) then \(\Delta\) is a right triangle.
\(a\)
\(b\)
\(c\)
Proof. Law of cosines
\[c^2=a^2+b^2-2ab\cos(\theta).\]
\(\theta\)
Theorem. If \(v\) and \(w\) are vectors in a real Hilbert space such that
\(\|v\|^2 + \|w\|^2 = \|v+w\|^2,\) then \(\langle v,w\rangle = 0.\)
Proof.
\[\|v+w\|^2 = \langle v+w,v+w\rangle = \|v\|^2+2\langle v,w\rangle + \|w\|^{2}\]
\[\|v+w\|^2=\|v\|^2+\|w\|^2 \quad \Rightarrow\quad 2\langle v,w\rangle = 0. \quad \Box\]
Theorem. If \(d_{1},d_{2}\) are two numbers in \([0,1]\) such that \(d_{1}+d_{2} = 1,\) then there is a projection \(P\) such that \(d_{1} = \|Pe_{1}\|^2\) and \(d_{2} = \|Pe_{2}\|^2\), that is,
\[P = \begin{bmatrix} d_{1} & \alpha\\ \overline{\alpha} & d_{2}\end{bmatrix}.\]
Proof.
Theorem. If \((d_{i})_{i=1}^{n}\) is a sequence of numbers in \([0,1]\) such that \[\sum_{i=1}^{n}d_{i}\in\N\cup\{0\},\] then there is an \(n\times n\) projection \(P\) such that \[\|Pe_{i}\|^{2} = d_{i} \quad\text{for}\quad i=1,\ldots,n.\]
\[\langle Pe_{i},e_{i}\rangle = \]
Note that this means that the sequence on the diagonal of the matrix \(P\) is \((d_{i})_{i=1}^{n}\).
Example. Consider the sequence
\[\left(\frac{5}{7},\frac{5}{7},\frac{3}{7},\frac{1}{7}\right).\]
\[\left[\begin{array}{rrrr}\frac{5}{7} & -\frac{\sqrt{15}}{21} & -\frac{\sqrt{30}}{21} & \frac{\sqrt{5}}{7}\\[1ex] -\frac{\sqrt{15}}{21} & \frac{5}{7} & -\frac{2\sqrt{2}}{7} & -\frac{\sqrt{3}}{21}\\[1ex] -\frac{\sqrt{30}}{21} & -\frac{2\sqrt{2}}{7} & \frac{3}{7} & -\frac{\sqrt{6}}{21}\\[1ex] \frac{\sqrt{5}}{7} & -\frac{\sqrt{3}}{21} & -\frac{\sqrt{6}}{21} & \frac{1}{7}\end{array}\right]\]
Challenge: Construct a \(4\times 4\) projection with this diagonal.
Theorem. Assume \((d_{i})_{i=1}^{n}\) is a sequence of numbers in \([0,1].\) There is an \(n\times n\) projection \(P\) with diagonal \((d_{i})_{i=1}^{n}\) if and only if
\[\sum_{i=1}^{n}d_{i} \in\N\cup\{0\}.\]
Definition. Given an operator \(E\) on a Hilbert space, a sequence \((d_{i})_{i\in I}\) is a diagonal of \(E\) if there is an orthonormal basis \((e_{i})_{i\in I}\) such that
\[d_{i} = \langle Ee_{i},e_{i}\rangle \quad\text{for all }i\in I.\]
The problem: Given an operator \(E\), characterize the set of diagonals of \(E\), that is, the set
\[\big\{(\langle Ee_{i},e_{i}\rangle )_{i\in I} : (e_{i})_{i\in I}\text{ is an orthonormal basis}\big\}\]
In particular, we want a characterization in terms of linear inequalities between the diagonal sequences and the spectral information of \(E\).
Note: If we fix an orthonormal basis \((f_{i})_{i\in I}\), then the set of diagonals of \(E\) is also
\[\big\{(\langle UEU^{\ast}f_{i},f_{i}\rangle )_{i\in I} : U\text{ is unitary}\big\}\]
Examples. Let \((e_{i})_{i=1}^{\infty}\) be an orthonormal basis.
Set \(\displaystyle{v = \sum_{i=1}^{\infty}\sqrt{\frac{1}{2^{i}}}e_{i}},\) then
\[I-P = \begin{bmatrix} \frac{1}{2} & -\frac{1}{2^{3/2}} & -\frac{1}{2^{2}} & \cdots \\[1ex] -\frac{1}{2^{3/2}} & \frac{3}{4} & -\frac{1}{2^{5/2}} & \cdots\\[1ex] -\frac{1}{2^{2}} & -\frac{1}{2^{5/2}} & \frac{7}{8} & \cdots\\ \vdots & \vdots & \vdots & \ddots\end{bmatrix}\]
\[P = \langle \cdot,v\rangle v = \begin{bmatrix} \frac{1}{2} & \frac{1}{2^{3/2}} & \frac{1}{2^{2}} & \cdots \\[1ex] \frac{1}{2^{3/2}} & \frac{1}{4} & \frac{1}{2^{5/2}} & \cdots\\[1ex] \frac{1}{2^{2}} & \frac{1}{2^{5/2}} & \frac{1}{8} & \cdots\\[1ex] \vdots & \vdots & \vdots & \ddots\end{bmatrix}\]
Corank 1 projection
Diagonal: \(\displaystyle{\left(\frac{1}{2},\frac{3}{4},\frac{7}{8},\ldots\right)}\)
Rank 1 projection
Diagonal: \(\displaystyle{\left(\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots\right)}\)
Examples.
\[\frac{1}{2}J_{2} = \begin{bmatrix} \frac{1}{2} & \frac{1}{2}\\[1ex] \frac{1}{2} & \frac{1}{2}\end{bmatrix}\]
\[Q = \bigoplus_{i=1}^{\infty}\frac{1}{2}J_{2} = \begin{bmatrix} \frac{1}{2}J_{2} & \mathbf{0} & \mathbf{0} & \cdots\\ \mathbf{0} & \frac{1}{2}J_{2} & \mathbf{0} & \cdots\\ \mathbf{0} & \mathbf{0} & \frac{1}{2}J_{2} & \\ \vdots & \vdots & & \ddots\end{bmatrix}\]
\(\infty\)-rank and \(\infty\)-corank
Diagonal: \(\displaystyle{\left(\frac{1}{2},\frac{1}{2},\frac{1}{2},\ldots\right)}\)
\(\infty\)-rank and \(\infty\)-corank
Diagonal: \(\displaystyle{\left(\ldots,\frac{1}{8},\frac{1}{4},\frac{1}{2},\frac{1}{2},\frac{3}{4},\frac{7}{8},\ldots\right)}\)
\[P\oplus (I-P)\]
Theorem. Assume \((d_{i})_{i=1}^{n}\) is a sequence of numbers in \([0,1].\) There is an \(n\times n\) projection \(P\) with diagonal \((d_{i})_{i=1}^{n}\) if and only if
\[\sum_{i=1}^{n}d_{i} \in\N\cup\{0\}.\]
\[\sum_{i=1}^{k}d_{i} - \sum_{i=k+1}^{n}(1-d_{i})\in\Z\]
\[\Updownarrow\]
Theorem. Assume \((d_{i})_{i=1}^{n}\) is a sequence of numbers in \([0,1].\) There is an \(n\times n\) projection \(P\) with diagonal \((d_{i})_{i=1}^{n}\) if and only if
\[\sum_{i=1}^{k}d_{i} - \sum_{i=k+1}^{n}(1-d_{i})\in\Z.\]
Theorem (Kadison '02). Assume \((d_{i})_{i=1}^{\infty}\) is a sequence of numbers in \([0,1],\) and set
\[a=\sum_{d_{i}<\frac{1}{2}}d_{i}\quad\text{and}\quad b=\sum_{d_{i}\geq \frac{1}{2}}(1-d_{i})\]
There is a projection \(P\) with diagonal \((d_{i})_{i=1}^{\infty}\) if and only if one of the following holds:
Examples.
Up to unitary equivalence \(E=\begin{bmatrix} \lambda_{1} & 0\\ 0 & \lambda_{2}\end{bmatrix}\), with \(\lambda_{1}\geq \lambda_{2}\).
\[\begin{bmatrix}\cos\theta & -\sin\theta\\ \sin\theta & \cos\theta\end{bmatrix}\begin{bmatrix} \lambda_{1} & 0\\ 0 & \lambda_{2}\end{bmatrix}\begin{bmatrix}\cos\theta & \sin\theta\\ -\sin\theta & \cos\theta\end{bmatrix}\]
\[= \begin{bmatrix}\alpha\lambda_{1}+(1-\alpha)\lambda_{2} & \ast\\ \overline{\ast} & (1-\alpha)\lambda_{1} + \alpha\lambda_{2} \end{bmatrix},\quad (\alpha = \cos^{2}\theta)\]
Hence \((d_{1},d_{2})\), with \(d_{1}\geq d_{2}\), is a diagonal of \(E\) if and only if
and
\[\lambda_{1}+\lambda_{2}=d_{1}+d_{2}\].
\(\lambda_{2}\leq d_{1}\leq\lambda_{1}\)
\[d_{1}\in\operatorname{conv}(\{\lambda_{1},\lambda_{2}\})\]
\( d_{1}\leq\lambda_{1}\)
\[\begin{bmatrix}\cos\theta & -\sin\theta & 0\\ \sin\theta & \cos\theta & 0\\ 0 & 0 & 1\end{bmatrix}\begin{bmatrix} \lambda_{1} & 0 & 0\\ 0 & \lambda_{2} & 0\\ 0 & 0 & \lambda_{3}\end{bmatrix}\begin{bmatrix}\cos\theta & \sin\theta & 0\\ -\sin\theta & \cos\theta & 0\\ 0 & 0 & 1\end{bmatrix}\]
\[= \begin{bmatrix}\alpha\lambda_{1}+(1-\alpha)\lambda_{2} & \ast & 0\\ \overline{\ast} & (1-\alpha)\lambda_{1} + \alpha\lambda_{2} & 0\\ 0 & 0 & \lambda_{3}\end{bmatrix},\quad (\alpha = \cos^{2}\theta)\]
Suppose \(E = \left[\begin{smallmatrix} \lambda_{1} & 0 & 0\\ 0 & \lambda_{2} & 0\\ 0 & 0 & \lambda_{3}\end{smallmatrix}\right]\) with \(\lambda_{1}\geq \lambda_{2}\geq\lambda_{3}\)
\[\begin{bmatrix}\cos\theta & 0 & -\sin\theta\\ 0 & 1 & 0\\ \sin\theta & 0 & \cos\theta\end{bmatrix}\begin{bmatrix} \mu_{1} & \ast & 0\\ \overline{\ast} & \mu_{2} & 0\\ 0 & 0 & \mu_{3}\end{bmatrix}\begin{bmatrix}\cos\theta & 0 & \sin\theta\\ 0 & 1 & 0\\ -\sin\theta & 0 & \cos\theta\end{bmatrix}\]
\[= \begin{bmatrix}\alpha\mu_{1}+(1-\alpha)\lambda_{3} & \ast & \ast\\ \overline{\ast} & \mu_{2} & \ast\\ \overline{\ast} & \overline{\ast} & (1-\alpha)\mu_{1} + \alpha\mu_{3}\end{bmatrix},\quad (\alpha = \cos^{2}\theta)\]
Suppose \(E = \left[\begin{smallmatrix} \lambda_{1} & 0 & 0\\ 0 & \lambda_{2} & 0\\ 0 & 0 & \lambda_{3}\end{smallmatrix}\right]\) with \(\lambda_{1}\geq \lambda_{2}\geq\lambda_{3}\)
Then \((d_{1},d_{2},d_{3})\), with \(d_{1}\geq d_{2}\geq d_{3}\) is a diagonal of \(E\) if and only if
\[d_{i}\in\operatorname{conv}\{\lambda_{1},\lambda_{2},\lambda_{3}\}\quad\forall\,i\]
and
\[d_{1}+d_{2}+d_{3}=\lambda_{1}+\lambda_{2}+\lambda_{3}.\]
However, \((7,6,1,1)\) is not a diagonal of \(E = \left[\begin{matrix} 8 & 0 & 0 & 0\\ 0 & 4 & 0 & 0\\ 0 & 0 & 2 & 0\\ 0 & 0 & 0 & 1\end{matrix}\right]\)
\(d_{1}\leq \lambda_{1}\), \(d_{1}+d_{2}\leq \lambda_{1}+\lambda_{2}\),
Even though \[7,6,1\in\operatorname{conv}(\{8,4,2,1\})=[1,8]\]
and \[7+6+1+1=15=8+4+2+1\]
\(7+6=13\not\leq 12=8+4\)
Theorem (Schur '23, Horn '54). Let \((d_{i})_{i=1}^{n}\) and \((\lambda_{i})_{i=1}^{n}\) be nonincreasing sequences. There is a self-adjoint matrix \(E\) with diagonal \((d_{i})_{i=1}^{n}\) and eigenvalues \((\lambda_{i})_{i=1}^{n}\) if and only if
\[\sum_{i=1}^{k}d_{i}\leq \sum_{i=1}^{k}\lambda_{i}\quad\text{for}\quad k=1,2,\ldots,n-1\]
and
\[\sum_{i=1}^{n}d_{i} = \sum_{i=1}^{n}\lambda_{i}.\]
(1)
(2)
If (1) and (2) hold, then we say that \((\lambda_{i})_{i=1}^{n}\) majorizes \((d_{i})_{i=1}^{n}\), and we write \((\lambda_{i})_{i=1}^{n}\succeq (d_{i})_{i=1}^{n}\)
\((\lambda_{i})_{i=1}^{n}\succeq (d_{i})_{i=1}^{n}\) is equivalent to saying that \((d_{i})_{i=1}^{n}\) is in the convex hull of the permutations of \((\lambda_{i})_{i=1}^{n}\).
Theorem (Arveson, Kadison '06, Kaftal, Weiss '10). Let \((\lambda_{i})_{i=1}^{\infty}\) be a positive nonincreasing sequence, and let \((d_{i})_{i=1}^{\infty}\) be a nonnegative nonincreasing sequence. There exists a positive compact operator with positive eigenvalues \((\lambda_{i})_{i=1}^{\infty}\) and diagonal \((d_{i})_{i=1}^{\infty}\) if and only if
\[\sum_{i=1}^{k}d_{i}\leq \sum_{i=1}^{k}\lambda_{i}\quad\text{for all}\quad k\in\N\]
and
\[\sum_{i=1}^{\infty}d_{i} = \sum_{i=1}^{\infty}\lambda_{i}.\]
Open question: What are the diagonals of positive compact operators with positive eigenvalues
\[\left(1,\frac{1}{2},\frac{1}{3},\ldots\right)\] and a \(1\)-dimensional kernel.
Example. Consider the diagonal matrix \(E = \operatorname{diag}(-1,1,\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots)\)
\[\begin{bmatrix} -1 & 0 & 0 & 0 & \cdots\\ 0 & 1 & 0 & 0 & \cdots\\ 0 & 0 & \frac{1}{2} & 0 & \cdots\\ 0 & 0 & 0 & \frac{1}{4}\\ \vdots & \vdots & \vdots & & \ddots\end{bmatrix} \simeq \begin{bmatrix} -\frac{1}{2} & \ast & 0 & 0 & \cdots\\ \overline{\ast} & \frac{1}{2} & 0 & 0 & \cdots\\ 0 & 0 & \frac{1}{2} & 0 & \cdots\\ 0 & 0 & 0 & \frac{1}{4}\\ \vdots & \vdots & \vdots & & \ddots\end{bmatrix} \simeq \begin{bmatrix} -\frac{1}{4} & \ast & \ast & 0 & \cdots\\ \overline{\ast} & \frac{1}{2} & \ast & 0 & \cdots\\ \overline{\ast} & \overline{\ast} & \frac{1}{4} & 0 & \cdots\\ 0 & 0 & 0 & \frac{1}{4}\\ \vdots & \vdots & \vdots & & \ddots\end{bmatrix}\]
\[\simeq\cdots\simeq \begin{bmatrix} 0 & \ast & \ast & \ast & \cdots\\ \overline{\ast} & \frac{1}{2} & \ast & \ast & \cdots\\ \overline{\ast} & \overline{\ast} & \frac{1}{4} & \ast & \cdots\\ \overline{\ast} & \overline{\ast} & \overline{\ast} & \frac{1}{8}\\ \vdots & \vdots & \vdots & & \ddots\end{bmatrix}\]
Hence, \((0,\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots)\) is a diagonal of \(E\).
Definition. Let \(\boldsymbol\lambda =\{\lambda_i\}_{i\in I}\in c_0\). Define its positive part \(\boldsymbol\lambda_+ =\{\lambda^{+}_i\}_{i\in I}\) by \(\lambda^+_i=\max(\lambda_i,0)\). The negative part is defined as \(\boldsymbol\lambda_-=(-\boldsymbol \lambda)_+.\)
If \(\boldsymbol\lambda \in c_0^+\), then define its decreasing rearrangement \(\boldsymbol\lambda^{\downarrow} =\{\lambda^{\downarrow}_i\}_{i\in \N}\) by taking \(\lambda^{\downarrow}_i\) to be the \(i\)th largest term of \(\boldsymbol \lambda.\) For the sake of brevity, we will denote the \(i\)th term of \((\boldsymbol\lambda_{+})^{\downarrow}\) by \(\lambda_{i}^{+\downarrow}\), and similarly for \((\boldsymbol\lambda_{-})^{\downarrow}\).
\[-\lambda^{-\downarrow}_{1}\leq -\lambda^{-\downarrow}_{2}\leq-\lambda^{-\downarrow}_{3}\leq\cdots\leq 0\leq\cdots\leq \lambda^{+\downarrow}_{3}\leq \lambda^{+\downarrow}_{2}\leq \lambda^{+\downarrow}_{1}\]
Hence, we have "rearranged" the sequence \(\boldsymbol\lambda\) as follows:
Note:
If \(\boldsymbol\lambda\) has infinitely many positive terms, then \(\boldsymbol\lambda_{+}\) has no zeros.
If \(\boldsymbol\lambda\) has finitely many positive terms, then \(\boldsymbol\lambda_{+}\) has infinitely many zeros.
Given a compact self-adjoint operator \(E\) with eigenvalue list \(\boldsymbol\lambda\), it is straightforward to show that if \(\boldsymbol{d}\in c_{0}\) is a diagonal of \(E\), then
\[\sum_{i=1}^n \lambda_i^{+ \downarrow} \geq \sum_{i=1}^n d_i^{+ \downarrow} \quad\text{and }\quad \sum_{i=1}^n \lambda_i^{- \downarrow} \ge \sum_{i=1}^n d_i^{- \downarrow} \qquad\text{for all }k\in \N,\]
But it is not true that
\[\sum_{i=1}^\infty d_{i}^{+} = \sum_{i=1}^{\infty}\lambda_{i}^{+}\quad\text{and}\quad \sum_{i=1}^\infty d_{i}^{-} = \sum_{i=1}^{\infty}\lambda_{i}^{-}\]
Indeed, \((0,\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots)\) is a diagonal of an operator with eigenvalue list \((-1,1,\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots)\).
We need to keep track of how much "mass" was moved across zero:
\[\sigma_{+} = \liminf_{n\to\infty} \sum_{i=1}^n (\lambda_i^{+ \downarrow} - d_i^{+ \downarrow})\quad\text{and}\quad \sigma_{-} = \liminf_{n\to\infty} \sum_{i=1}^n (\lambda_i^{- \downarrow} - d_i^{- \downarrow})\]
\[\sigma_{+} = \sum_{i=1}^n (\lambda_i^{+ \downarrow} - d_i^{+ \downarrow})\quad\text{and}\quad \sigma_{-} = \sum_{i=1}^n (\lambda_i^{- \downarrow} - d_i^{- \downarrow})\]
Theorem (Bownik, J '22) Let \(\boldsymbol\lambda,\boldsymbol{d}\in c_{0}\). Set
\[\sigma_{+} = \liminf_{n\to\infty} \sum_{i=1}^n (\lambda_i^{+ \downarrow} - d_i^{+ \downarrow})\quad\text{and}\quad \sigma_{-} = \liminf_{n\to\infty} \sum_{i=1}^n (\lambda_i^{- \downarrow} - d_i^{- \downarrow})\]
Let \(A\) be a compact self-adjoint operator with eigenvalue list \(\boldsymbol\lambda.\)
The sequence \(\boldsymbol d\) is a diagonal of an operator \(B\) such that \(A\oplus \boldsymbol 0\) and
\(B \oplus \boldsymbol 0\) are unitarily equivalent, where \(\boldsymbol 0\) denotes the zero operator on an infinite dimensional Hilbert space, if and only if the following four conditions hold:
\[\sum_{i=1}^n \lambda_i^{+ \downarrow} \geq \sum_{i=1}^n d_i^{+ \downarrow} \quad\text{and }\quad \sum_{i=1}^n \lambda_i^{- \downarrow} \ge \sum_{i=1}^n d_i^{- \downarrow} \qquad\text{for all }k\in \N,\]
\[\boldsymbol d_+ \in \ell^1 \quad \implies\quad \sigma_{-}\geq \sigma_{+}.\]
\[\boldsymbol d_- \in \ell^1 \quad \implies\quad \sigma_{+}\geq \sigma_{-}\]
Note: If \(\boldsymbol d\in\ell^{1}\) (\(A\) is trace class), then \(\sigma_{-} = \sigma_{+}\). That is \(\sum d_{i} = \sum\lambda_{i}\).
Theorem (Bownik, J '22) Let \(\boldsymbol\lambda,\boldsymbol{d}\in c_{0}\). Let \(A\) be a compact self-adjoint operator with eigenvalue list \(\boldsymbol\lambda.\) If
\[\sum_{i=1}^n \lambda_i^{+ \downarrow} \geq \sum_{i=1}^n d_i^{+ \downarrow} \quad\text{and }\quad \sum_{i=1}^n \lambda_i^{- \downarrow} \ge \sum_{i=1}^n d_i^{- \downarrow} \qquad\text{for all }k\in \N,\]
and
\[\sigma_{+}=\sigma_{-}\in(0,\infty).\]
then, the sequence \(\boldsymbol d\) is a diagonal of \(A\).
In some special cases we can get a stronger sufficiency result:
Not some operator with a different sized kernel.
Example. Set \[\boldsymbol\lambda = \left(-1,1,\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots\right)\] and \[\boldsymbol{d} =\left (\frac{1}{2},\frac{1}{4},\frac{1}{8},\ldots\right)\]
Then \[\sigma_{+}=\sigma_{-}=1\in(0,\infty),\] and clearly
\[\sum_{i=1}^n \lambda_i^{+ \downarrow} \geq \sum_{i=1}^n d_i^{+ \downarrow} \quad\text{and }\quad \sum_{i=1}^n \lambda_i^{- \downarrow} \ge \sum_{i=1}^n d_i^{- \downarrow} \qquad\text{for all }k\in \N,\]
So, \((0,\frac{1}{2},\frac{1}{4},\frac{1}{8},\cdots)\) and \((\frac{1}{2},\frac{1}{4},\frac{1}{8},\cdots)\) are diagonals of \(E=\operatorname{diag}(\boldsymbol\lambda)\).