Timeline
2022 - Present

The Problem
Quantum R&D required to bring quantum technologies to the commercial market demands extensive experimentation, diverse hardware and rigorous data collection + analysis. Performing these processes manually is slow and error prone – imagine physically adjusting dozens of knobs and switches in precise sequence for each experiment. Or if you had to create your own quantum data analysis tools without proper software engineering support. Without automation and reliable software tools research throughput is limited. If you want to win the quantum race efficient automation and robust analysis tools are essential!

Mission
Develop software infrastructure and packages that empower internal stakeholders to run quantum system experiments efficiently. By automating operations, data collection, and analysis we increase research throughput, improve reproducibility, and free researchers to focus on discovery.

Drivers for Hardware
Again, imagine if you had to physically go and turn a knob on a piece of hardware to output a signal in your experiment. Now imagine if you had 30 different pieces of hardware all with a special knob, switch, button that needed to be actioned. Please don’t imagine how reliable or repeatable this process would be. To help address this, the software team develops drivers that create interfaces to programmatically communicate with hardware. This enables repeatable experiment execution, consistent order of operations, and reliable configuration.

Experimentation Framework
There is lots opportunity to streamline hardware interactions through drivers. So what happens when you get over 100 of these drivers, and they’re being used by multiple teams of people? A common experimentation framework becomes essential. The framework provides standardized methods + workflows for building and running experiments. This ensures experiments are structured consistently and can be easily shared, understood, and reproduced across teams.

Data Collection
Now we’ve got teams of people running many experiments with the experiment framework, which creates lots of data. To manage this, we established standardized processes for formatting, collecting, and storing data. Automated pipelines relieve users from manual data collection, enforce common data formats, and ensures data is immediately ready for analysis.

Data Analysis
When it comes to quantum data analysis there are a lot of specialized tools and packages necessary for meaningful analysis. The software team develops and maintains tailored data analysis packages that help researchers draw accurate data driven conclusions.

Results
The software team has significantly increased the speed, reliability, and reproducibility of quantum R&D. From programmatic hardware control to automated workflows and robust analysis packages, we’ve built an integrated software ecosystem that supports our researchers and company goals. The work isn’t over, ongoing innovation continues to drive improvements and strengthen our position to bring quantum technologies to market.

Tech
Not disclosed.