Machine learning has made real inroads in cancer detection, diagnosis, and treatment, but cancer is a formidably complex disease, and that complexity pushes traditional models to their limits. Cancer involves a huge number of interacting biological variables: genetic...
Blog
Research Themes
Discretization-Aware Fine-Tuning for Quantum Machine Learning
When Quantum Machine Learning Fails Before the Quantum Circuit Even Starts Quantum machine learning (QML) research often emphasizes quantum circuit design, entanglement, and the scaling of available qubits. However, an important challenge appears much earlier in the...
Estimating Quantum Resources for Machine Learning Problems
Machine learning has emerged as a powerful tool for analyzing complex datasets across diverse fields. By learning patterns directly from data, machine learning can uncover relationships and make predictions that are difficult to capture using traditional statistical...
How many qubits does a machine learning problem require?
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...
A Hierarchy of Contexts
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...
Quantum Software for Accelerating Application Design
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...
Foundations for Scalable Quantum Machine Learning
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...
Quantum Programming Abstractions
What does it mean to program a quantum computer? Why are we still stuck specifying individual qubit gates by hand? And what would a true quantum programming language look like? Right now, programming quantum computers is done through quantum circuits—specifying how...