Accelerating quantum algorithms with resource states

We often analyze the computational complexity of a quantum algorithm in terms of the total amount of time and space required. In some cases, however, it is natural to allow a quantum algorithm access to a pre-prepared pool of resource states. In this talk, I consider an alternative cost model that neglects the cost of preparing (but not storing) such a pool of resource states. I argue that this cost model might be appropriate for thinking about real-world quantum advantage for certain algorithms. I also show that a quadratic improvement in the space-time volume for certain families of circuits can be obtained under this cost model.