3 by 3 by 3 Tensors

We now study the case of 3\times 3 \times 3 tensors over the real and complex numbers. Our goals are

  • to determine the maximum separation rank r of such tensors and
  • to explore the geometry of S_r for some r less than the maximum.

In principle one can never determine the maximum separation rank r using a numerical routine such as this, since one could be unlucky and miss it. Generally one can only hope to determine the typical separation rank.

Visualizations over the Real numbers

In [KRUSKA1989], Kruskal claims to have shown rank r\le 5, but his results were not published. Jos ten Berge says that he saw this 20 page proof but discarded it when Roberto Rocci provided a 4 page proof in 1993, which is also unpublished but is available. A full proof is published in [BRE-HU2013].

A Random Example

We choose T_1, T_2, and T_3 randomly in S_3. Since these three tensors are in S_3, any tensor on the line connecting any two of them is in S_6, and a tensor in the plane is generically in S_9, which we suppose is large enough to capture general 3\times 3 \times 3 tensors.

We first produce a visualization of S_4 on [-1,2]\times[-1,2], and obtain

_images/3x3x3pr4random.jpg

[data file 3x3x3pr4random.dat] There are only a few scattered black points. Thus we conclude that the maximum separation rank of a 3\times 3 \times 3 tensor over the real numbers is more than 4.

Next, using the same set of random T_1, T_2, and T_3, we produce a visualization of S_5, and obtain

_images/3x3x3pr5random.jpg

[data file 3x3x3pr5random.dat] Black points are distributed over the whole plane, with no apparent voids. We interpret this as validating the result that the maximum rank is 5.

Finally, using the same set of random T_1, T_2, and T_3, we first produce a visualization for S_6, expecting it to be solid black. Since the line connecting any two T_i is in S_6, these lines appear in the visualization, and help to locate the T_i. We obtain the visualization

_images/3x3x3pr6random.jpg

[data file 3x3x3pr6random.dat] The occasional lighter point is attributed to failure in the routine that tries to fit a tensor on the plane with a tensor in S_6.

A Specific Example

We now consider a specific example that was suggested as possibly interesting. The target tensor, which has nominal rank 5, is

X_5 &= [1,0,0]\otimes[1,0,0]\otimes[1,0,0]
+[1,0,0]\otimes[0,0,1]\otimes[0,0,1]\\
&+[0,1,0]\otimes[1,0,0]\otimes[0,1,0]
+[0,1,0]\otimes[0,1,0]\otimes[0,0,1]\\
&+[0,0,1]\otimes[1,0,0]\otimes[0,0,1]
\,,

which can also be viewed as

X_5 = [1,0,0]\otimes\left[\begin{array}{ccc}
1&0&0\\0&0&0\\0&0&1\end{array}\right]
+ [0,1,0]\otimes\left[\begin{array}{ccc}
0&1&0\\0&0&1\\0&0&0\end{array}\right]
+ [0,0,1]\otimes\left[\begin{array}{ccc}
0&0&1\\0&0&0\\0&0&0\end{array}\right]
\,.

Using the plane defined by the three tensors

T_1&= [1,0,0]\otimes[1,0,0]\otimes[1,0,0]
+[1,0,0]\otimes[0,0,1]\otimes[0,0,1]\\
T_2&=   [0,1,0]\otimes[1,0,0]\otimes[0,1,0]
+[0,1,0]\otimes[0,1,0]\otimes[0,0,1]
\quad\text{and}\\
T_3&=   [0,0,1]\otimes[1,0,0]\otimes[0,0,1]
\,,

the point X_5 is in their center.

We first produce a visualization of S_3 on [-1,2]\times[-1,2], and obtain

_images/3x3x3pr3X5.jpg

[data file 3x3x3pr3X5.dat] Since the region in the vicinity of X_5 has no black points, we conclude it is not rank 3. We next produce a visualization of S_4 and obtain

_images/3x3x3pr4X5.jpg

[data file 3x3x3pr4X5.dat] A large number of test points were needed to produce this visualization. We used more points near the center to try to get better resolution there. Although there are not that many black points, they are spread throughout the visualization with no apparent voids. We also tried zooming in on a relatively light region near the center and adding many more points there, and were then able to find dark points. Based on this behavior, we conclude that X_5 is probably of rank 5 but reachable as a limit of rank 4 tensors.

Visualizations over the Complex numbers

The rank over the complex numbers is at most the rank over the real numbers, so we now investigate whether or not the maximum rank is strictly smaller for 3\times 3 \times 3 tensors.

A Random Example

We choose T_1 and T_2 randomly in S_3, so that a tensor in the plane is generically in S_6, which we know is large enough to capture general 3\times 3 \times 3 tensors. We then produce a visualization of S_4 and obtain

_images/3x3x3pr4randomC.jpg

[data file 3x3x3pr4randomC.dat] Since there are few black points, we conclude the maximum rank over the complex numbers is more than 4, and hence is 5. As an additional check, we use the same T_1 and T_2 and produce a visualization of S_5, and obtain

_images/3x3x3pr5randomC.jpg

[data file 3x3x3pr5randomC.dat]

A Specific Example

We now reconsider the tensor X_5, which we studied in the real case. We use the complex line defined by

T_1&= [1,0,0]\otimes[1,0,0]\otimes[1,0,0]
+[1,0,0]\otimes[0,0,1]\otimes[0,0,1]\quad\text{and}\\
T_2&=   [0,1,0]\otimes[1,0,0]\otimes[0,1,0]
+[0,1,0]\otimes[0,1,0]\otimes[0,0,1]
+[0,0,1]\otimes[1,0,0]\otimes[0,0,1]
\,.

We first produce a visualization of S_3 on [-1,2]\times[-i,i], and obtain

_images/3x3x3pr3X5C.jpg

[data file 3x3x3pr3X5C.dat] Since there are essentially no black points, we then produce a visualization of S_4 and obtain

_images/3x3x3pr4X5C.jpg

[data file 3x3x3pr4X5C.dat] This visualization required quite a lot of points and effort. The scattered dark blue points indicate that rank 4 points are present (or nearby) but that they are hard to construct. We zoomed in to [0.4,0.6]\times[-0.1i,0.1i] and added points near X_5, and obtain

_images/3x3x3pr4X5Czoom.jpg

Based on this behavior, we again conclude that X_5 is probably of rank 5 but reachable as a limit of rank 4 tensors.