Bringing AI to quantum - new automation and optimization capabilities to help the research community move faster
March 3, 2023
Quantum technology remains one of the most exciting and demanding fields around; in the everyday life of a researcher, it's easy to forget you're manipulating the quantum states of individual atoms, photons, and circuits!
Members of the community from diverse backgrounds share surprisingly common challenges in their research. When we engaged the quantum research and development community, we identified the following top priorities among researchers of all backgrounds:
These tasks consume a huge amount of time and resources for physicists and engineers who would rather focus on addressing totally new scientific and technical questions.
Fortunately, that's changing rapidly with exciting new features from Boulder Opal. We’re excited to unveil some big new capabilities for the APS March Meeting! 🚀
Boulder Opal provides everything you need to automate and optimize your critical quantum technology research tasks. It’s the best software in the market for deploying cutting-edge capabilities in quantum control, and now we’re expanding its capabilities and impact even further to offer a comprehensive AI toolkit for system bringup and calibration.
Users need to automate their experiments as systems become more complex. Now you can leverage Boulder Opal’s experiment scheduler to automate system-wide calibration according to user-defined decision flows, from simple periodic tasks to interdependent experiments. We’ve seen experimental teams save hours every day by replacing manual step-by-step tuneup with full automation!
We previously developed and released AI-driven routines to design and calibrate individual gates. Leveraging AI agents for the task in a closed-loop makes the process both better and more efficient, as we showed in published research. But the real power of AI comes in delivering autonomy to all processes needed in running a large, complex system.
We're now releasing an entirely new feature set that combines this "individual task" approach with full AI-driven scheduling of system tuneup and optimization.
Our new scheduler can autonomously bring up a large, interacting multi-qubit system from scratch. This process abstracts the specific hardware tasks in each step, and determines how and when each interrelated process should be executed, as well as what happens when something goes wrong. Tune up entire devices on a schedule, add dependencies, and handle exceptions with ease - and with no human intervention required.
And by leveraging the seamless compatibility with Boulder Opal’s best-in-class AI-based toolset for control design, calibration, and system identification, you can easily add complex measurement and optimization routines right into your scheduling workflows.
As qubit counts grow and device complexity increases AI automation is the only way to go!
Use AI to move your quantum research faster today 🚀 Get started with Boulder Opal for free to accelerate your research.
Cloud-compute resources give incredible performance boosts for model-based optimization, dynamic simulation, and control design in high-dimensional systems. Bringing AI to the edge is the next frontier in saving researchers time in tuning up their hardware.
We’re thrilled to offer a new ultra-low-latency hybrid solution for Boulder Opal Professional users. Now you can combine the best in cloud compute with local execution of AI-driven closed-loop optimization to reduce latencies to milliseconds, shaving hours off closed-loop optimizations for your devices. And by pushing the right AI computations to the edge you can even perform experimental online training as quick as simulation!
Whether you’re solving purely theoretical problems or seeking to integrate physics insight into an AI-driven process, model-based optimization is a critical tool in quantum research. But not every problem is easily amenable to standard “gradient-based” solvers. If the mathematical object called the gradient is difficult to calculate, most optimization engines simply fail.
Boulder Opal provides a range of best-in-class numerical techniques to help you design new optimal and noise-robust control that can boost device performance by up to 100x.
Now we’re excited to offer a new gradient-free optimizer that can be directly applied to model-based optimization for any arbitrary quantum system. This gradient-free optimizer opens up a range of problems that were previously inaccessible for state-of-the-art tools, and has the added benefit of being very efficient in its memory usage.
Find out what research opportunities are unlocked with this new capability!
Boulder Opal’s fully managed cloud acceleration helps you attack bigger, more complex, and more challenging problems. Have many interacting levels in a simulation or optimization? Cloud acceleration gives you access to the memory resources you just can’t find on a standard workstation.
And now we’re offering a major upgrade to our cloud compute engine! Users seeking more computational muscle and throughput can now upgrade to our higher-tier performance and professional plans, delivering easy access to more powerful cloud compute resources than ever before.
Head-to-head performance benchmarking tests have shown that leveraging our automatic CPU parallelization and GPU support can deliver an order-of-magnitude performance enhancement (reduced time to solution) over the best local tools.
With fully managed access to the power of the cloud, you can free up time and energy to focus on what matters.
These new capabilities are all designed to help empower researchers who are pushing the limits in quantum technology.
👉 Get started with Boulder Opal for free to accelerate your research.