What if you could examine a dataset and quickly calculate how many qubits you’d need to model it on a quantum computer? For quantum machine learning, that kind of clarity has been missing. And as a result, researchers and companies have been left guessing about when...
In this post, we describe an important aspect of constructing and compiling complex quantum operators—specifically, how large operators built from many smaller pieces can be represented and resolved. Let’s say we want to create a unitary operator acting on a large...
In this post, we'll walk through our architectural approach — a structure designed to make quantum computing more accessible, modular, and scalable. Building for the Quantum User At the top of the stack, we find the hardware-independent layers. These are the tools and...
In this post, we will walk through this recent paper that outlines a strategy for training large quantum models for the problem of classification. In this problem, we are given a labeled dataset — for example, images of handwritten digits where each image is paired...