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
\[\|v_{1}\|^2 + \|v_{2}\|^2 + \cdots + \|v_{k}\|^{2} = \|v_{1}+v_{2}+\cdots+v_{k}\|^2.\]
\[\|Pe_{1}\|^{2} + \|Pe_{2}\|^{2} = 1\]
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 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 \(E\).
Diagonals of projections in finite dimensions
Diagonals of projections in infinite dimensions
Diagonals of self-adjoint matrices in finite dimensions
Compact positive
Normal
self-adjoint finite spectrum
\(\mathrm{II}_{1}\) factors
W/ prescribed singular values
Normal
\(\infty\) dimensional path
Finite dimensional path
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.
Diagonals of projections in finite dimensions
Diagonals of projections in infinite dimensions
Diagonals of self-adjoint matrices in finite dimensions
Compact positive
Normal
self-adjoint finite spectrum
\(\mathrm{II}_{1}\) factors
W/ prescribed singular values
Normal
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 \((\lambda_{i})_{i=1}^{n}\).
Diagonals of projections in finite dimensions
Diagonals of projections in infinite dimensions
Diagonals of self-adjoint matrices in finite dimensions
Compact positive
Normal
self-adjoint finite spectrum
\(\mathrm{II}_{1}\) factors
W/ prescribed singular values
Normal
?
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 diagonal \((d_{i})_{i=1}^{\infty}\) and whose positive eigenvalues are \((\lambda_{i})_{i=1}^{\infty}\) 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.
Diagonals of projections in finite dimensions
Diagonals of projections in infinite dimensions
Diagonals of self-adjoint matrices in finite dimensions
Compact positive
Normal
self-adjoint finite spectrum
W/ prescribed singular values
Normal
?
\(\mathrm{II}_{1}\) factors
?
Theorem (JJ '13). Let \(0<\alpha<1\) and let \((d_{i})_{i=1}^{\infty}\) be a sequence in \([0,1]\). Define
\[c=\sum_{d_{i}<\alpha}d_{i}\quad\text{and}\quad d=\sum_{d_{i}\geq \alpha}(1-d_{i}).\]
There is a self-adjoint operator \(E\) with diagonal \((d_{i})_{i=1}^{\infty}\) and spectrum \(\{0,\alpha,1\}\) if and only if one of the following holds:
Notes:
\[E=\left(\begin{array}{ccccccc} 1/2 & \overline{\ast} & \overline{\ast} & \overline{\ast} & \overline{\ast} & \cdots\\ \ast & 1/4 & \overline{\ast} & \overline{\ast} & \overline{\ast} & \cdots\\ \ast & \ast & 3/4 & \overline{\ast} & \overline{\ast} & \cdots\\ \ast & \ast & \ast & 1/8 & \overline{\ast} & \cdots\\ \ast & \ast & \ast & \ast & 7/8 & \\ \vdots & \vdots & \vdots & \vdots & & \ddots\\ \end{array}\right)\]
Consider the self-adjoint operator
If the eigenvalues of \(E\) are \(\{0,\alpha,1\}\) with \(0<\alpha<1\), then what are the possible values of \(\alpha\)?
\[ \frac{1}{16},\frac{1}{14},\frac{1}{12},\frac{1}{10},\frac{1}{8},\frac{1}{6},\frac{1}{4},\frac{1}{2},\frac{3}{4},\frac{5}{6},\frac{7}{8},\frac{9}{10},\frac{11}{12},\frac{13}{14},\frac{15}{16}\]
Diagonals of projections in finite dimensions
Diagonals of projections in infinite dimensions
Diagonals of self-adjoint matrices in finite dimensions
Compact positive
Normal
self-adjoint finite spectrum
W/ prescribed singular values
Normal
?
\(\mathrm{II}_{1}\) factors
Infinite dimensions:
Finite dimensions: