I tried running the following code:

```
A = [
1 0 0 1
0 0 0 0
0 0 0 0
1 0 0 1]
B = [
1 0 0 0 1 0 0 0 1
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
1 0 0 0 1 0 0 0 1
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
1 0 0 0 1 0 0 0 1]
cvx_begin SDP
variable p
expression C(4*4*9*9, 4*4*9*9)
C = p * Tensor(A, A, B, B) % Tensor() from QETLAB
subject to
p <= 1
C == semidefinite(4*4*9*9)
maximize p
cvx_end
```

When executed, I got the following output:

```
Calling SDPT3 4.0: 840457 variables, 1 equality constraint
For improved efficiency, SDPT3 is solving the dual problem.
------------------------------------------------------------
num. of constraints = 1
dim. of sdp var = 1296, num. of sdp blk = 1
dim. of linear var = 1
*******************************************************************
SDPT3: Infeasible path-following algorithms
*******************************************************************
version predcorr gam expon scale_data
HKM 1 0.000 1 0
it pstep dstep pinfeas dinfeas gap prim-obj dual-obj cputime
-------------------------------------------------------------------
0|0.000|0.000|6.4e+02|3.6e+01|3.4e+06| 1.296000e+03 0.000000e+00| 0:0:00| chol 1 1
1|1.000|0.989|1.0e-11|5.3e-01|4.9e+04| 7.224939e+00 -7.388049e-01| 0:0:02| chol 1 1
2|0.995|1.000|6.9e-14|4.5e-02|3.5e+03|-9.177506e-01 -9.785768e-01| 0:0:02| chol 1 1
3|1.000|1.000|9.7e-14|1.3e-02|5.2e+02|-9.765279e-01 -9.937538e-01| 0:0:02| chol 1 1
4|1.000|1.000|2.2e-13|4.0e-03|7.8e+01|-9.963402e-01 -9.981769e-01| 0:0:02| chol 1 1
5|1.000|1.000|1.4e-13|4.0e-04|6.3e+00|-9.999532e-01 -9.998184e-01| 0:0:02| chol 1 1
6|1.000|1.000|6.4e-14|4.0e-05|5.1e-01|-9.999959e-01 -9.999819e-01| 0:0:02| chol 1 1
7|1.000|1.000|9.0e-14|4.0e-06|4.2e-02|-9.999997e-01 -9.999982e-01| 0:0:02| chol 1 1
8|1.000|1.000|1.3e-13|4.0e-07|3.4e-03|-1.000000e+00 -9.999998e-01| 0:0:02| chol 1 1
9|1.000|1.000|8.0e-14|4.0e-08|2.7e-04|-1.000000e+00 -1.000000e+00| 0:0:02| chol 1 1
10|1.000|0.980|3.0e-14|7.9e-10|5.4e-06|-1.000000e+00 -1.000000e+00| 0:0:02| chol 1 1
11|1.000|0.980|9.3e-15|1.7e-11|1.2e-07|-1.000000e+00 -1.000000e+00| 0:0:02| chol 1 1
12|1.000|0.982|6.1e-15|3.4e-13|2.4e-09|-1.000000e+00 -1.000000e+00| 0:0:02|
stop: max(relative gap, infeasibilities) < 1.49e-08
-------------------------------------------------------------------
number of iterations = 12
primal objective value = -1.00000000e+00
dual objective value = -1.00000000e+00
gap := trace(XZ) = 2.36e-09
relative gap = 7.87e-10
actual relative gap = 3.68e-13
rel. primal infeas (scaled problem) = 6.05e-15
rel. dual " " " = 3.36e-13
rel. primal infeas (unscaled problem) = 0.00e+00
rel. dual " " " = 0.00e+00
norm(X), norm(y), norm(Z) = 9.7e+01, 1.0e+00, 1.0e+00
norm(A), norm(b), norm(C) = 7.2e+01, 2.0e+00, 7.2e+01
Total CPU time (secs) = 1.84
CPU time per iteration = 0.15
termination code = 0
DIMACS: 6.1e-15 0.0e+00 8.1e-12 0.0e+00 3.7e-13 7.9e-10
-------------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +1.70974e-14
```

However, this result seems incorrect because `C`

should be positive semidefinite for any positive real number `p`

, and thus the maximum value of `p`

should be 1.

What could be the cause of this issue, and how can it be fixed?