In his lecture on quantum computing, Scott Aaronson describes polynomial-size quantum circuits,
Now, once we fix a universal set (any universal set) of quantum gates, we'll be interested in those circuits consisting of at most p(n) gates from our set, where p is a polynomial, and n is the number of bits of the problem instance we want to solve. We call these the polynomial-size quantum circuits.
and then using this goes on to give a practical definition of $\sf BQP$:
$\sf BQP$ is the class of languages $L\subseteq\{0, 1\}^*$ for which there exists a uniform family of polynomial-size quantum circuits, $\{C_n\}$, such that for all $x\in\{0, 1\}^n$:
- If $x\in L$ then $C_n$ accepts input $|x\rangle|0\cdots0\rangle$ with probability at least 2/3.
- If $x\notin L$ then $C_n$ accepts input $|x\rangle|0\cdots0\rangle$ with probability at most 1/3.
Now, take $G$ to be any standard universal gate set (e.g. the Clifford+$\rm T$ set), and let $L$ be a language that can be computed on $n$ qubits only by using (polynomially many copies of) some general $SU(2^n)$ gate $\rm U$, whose decomposition requires exponentially (in $n$) many gates from the set $G$. Seemingly $L\notin\sf BQP$ as the circuit implementing $\rm U$ is not a polynomial circuit.
Then, let $G'=G\cup\{\rm U\}$. Clearly, $G'$ is still a universal gate set. However, computing $L$ requires polynomially many gates from $G'$, which would indicate $L\in\sf BQP$.
This seems like a contradiction. Or more profoundly, the definition of $\sf BQP$ seems to depend on the choice of the gate set. What exactly is going wrong here? And is $L$ an element of $\sf BQP$ or not?