Yes, there are two reasons that python is an ideal tool for quantum computing libraries at the moment. - In the NISQ era [1], circuits have limited depth and s

Yes, there are two reasons that python is an ideal tool for quantum computing libraries at the moment. - In the NISQ era [1], circuits have limited depth and size. It doesn't matter so much which language (or even algorithm!) you use when N<1000. - Simulating a circuit is expensive, but all the heavy lifting can be delegated to highly optimized C code. The most expensive part of Cirq's simulation is (or soon will be) a call to `numpy.einsum` [2]. 1: https://arxiv.org/abs/1801.00862 https://arxiv.org/abs/1801.00862 2: https://github.com/quantumlib/Cirq/blob/24638f234704686c4bb6e365613259813fe58571/cirq/linalg/transformations.py#L140 https://github.com/quantumlib/Cirq/blob/24638f234704686c4bb6...