how to determine a biquadratic form is positive-definite A biquadratic form $\sum_{i,j,k,l}b_{i,j,k,l}x_{i}x_{j}y_{k}y_{l}$，
how to determine whether it is positive-definite？
A  necessary and sufficient condition？
In fact, I have a matrix $B=\sum_{1\leq i,j\leq n}A_{i,j}z_{i}z_{j}$. $A_{i,j}$ are $n\times n$ matrix, $z$ is n-dimension vector. I want to prove that B is positive-definite. I know $A_{i,j}$ are positive-definite, but the big matrix  $\{A_{i,j}\}$ is not positive-definite. How can I prove that B is positive-definite. 
If there is not a general conclusion, how about $n=2$?
 A: In general one doesn't expect to have nice necessary and sufficient conditions for checking positivity of a biquadratic form.  The sum-of-squares methods outlined in these course notes provide an efficient way of checking whether a given biquadratic form can be written as a sum of squares of bilinear forms.  However, not all positive semidefinite biquadratic forms are sums of squares of bilinear forms as shown by Choi.  Choi cites references that positivity is equivalent to being a sum of squares of of bilinear terms for $n=1,2$ and gives an explicit example showing that this characterization fails for $n\geq 3$.
The sum-of-squares machinery gives a hierarchy of increasingly refined conditions which in the limit cover the interior of the cone of positive semidefinite biquadratic forms, so even if your form of interest is not a sum of squares of bilinear forms you may still be able to prove positivity by these methods, but you may not be able to do so efficiently.
Finally, note that the question of positivity of a biquadratic form is a first order statement over the reals and so is algorithmically decidable by quantifier elimination per Tarski, but the corresponding algorithms are exponential.
