Find the determinant of each of those matrices and eventually you'll notice the relationship in a characteristic equation:
[tex]A = \left(\begin{array}{abcdef}<br />
1-\lambda & 1 & 1\\<br />
1 & 1-\lambda & 1\\<br />
1 & 1 & 1-\lambda<br />
\end{array}\right)[/tex]
[tex]det(A) = -\lambda^3+3\lambda^2=0[/tex]
Similarly for [tex]A_{2x2}, det(A)=\lambda^2-2\lambda=0[/tex]
[tex]A_{4x4}, det(A)=\lambda^4-4\lambda^3=0[/tex]
[tex]A_{5x5}, det(A)=-\lambda^5+5\lambda^4=0[/tex]
The [tex]\lambda[/tex] is the eigenvalue. You can find your associated eigenvector by solving for this equation:
[tex]Av=\lambda v[/tex]
Where A is the matrix with all entries 1, v is the eigenvector, and [tex]\lambda[/tex] is the eigenvalue.
For example:
[tex]A_{2x2}:[/tex]
[tex]A = \left(\begin{array}{abcdef}<br />
1-\lambda & 1\\<br />
1 & 1-\lambda\\<br />
\end{array}\right)[/tex]
[tex]det(A) = (1-\lambda)(1-\lambda)-1=0[/tex]
Solving for [tex]\lambda[/tex] we get: [tex]\lambda=0, 2[/tex]
Now find associated eigenvectors for each eigenvalue:
[tex]Since Av=\lambda v[/tex]
[tex]Av-\lambda v=0[/tex]
[tex](A-\lambda)v=0[/tex]
v is your eigenvector
So for [tex]\lambda=0:[/tex]
[tex]A = \left(\begin{array}{abcdef}<br />
1-0 & 1 \\<br />
1 & 1-0 \\<br />
\end{array}\right)[/tex]
[tex]A = \left(\begin{array}{abcdef}<br />
1 & 1 \\<br />
1 & 1 \\<br />
\end{array}\right)[/tex]
Your eigenvector is of the form [tex]v = \left(\begin{array}{abcdef}<br />
v_1 \\<br />
v_2 \\<br />
\end{array}\right)[/tex]
Multiplying out with vector v and equationg to 0 you get:
[tex]1v_1 + 1v_2 = 0[/tex]
[tex]1v_1 + 1v_2 = 0[/tex]
Therefore in this particular case [tex]1v_1 = -1v_2[/tex] you can pick any number for [tex]v_2[/tex], i'd go with [tex]v_2=1[/tex]. So your eigenvector for [tex]\lambda=0[/tex] is:
[tex]v = \left(\begin{array}{abcdef}<br />
-1 \\<br />
1 \\<br />
\end{array}\right)[/tex]
You can check your eigenvalues and eigenvector simply by multiplying them out, since [tex]Av=\lambda v[/tex]
Check:
[tex]\left(\begin{array}{abcdef}<br />
1 & 1 \\<br />
1 & 1 \\<br />
\end{array}\right)[/tex][tex]\left(\begin{array}{abcdef}<br />
-1 \\<br />
1 \\<br />
\end{array}\right)[/tex][tex]=0*\left(\begin{array}{abcdef}<br />
-1\\<br />
1 \\<br />
\end{array}\right)[/tex]
However to answer your question for [tex]A_{nxn}[/tex] matrices..
since det(A)=0 for all such matrices and trace(A)=n you may notice that for every [tex]A_{nxn}[/tex] matrix you get n eigenvalues, but only one of them is an real number eigenvalue, [tex]\lambda=n[/tex]. In other words, for [tex]A_{2x2}, \lambda=2,0; A_{3x3}, \lambda=3,0,0; A_{4x4}, \lambda=4,0,0,0[/tex] --- you get the idea.