Deliver 100X hardware enhancements with advanced infrastructure software

Leverage the most advanced capabilities in quantum control to accelerate past the competition. Discover all the features of BOULDER OPAL for quantum computing and quantum sensing with our code-based User Guides.

Explore our user guides
Noise characterization

Hardware characterization

Signal synthesis

Noise-robust control design

Automation

Automated and scaleable tuneup

Expert hardware knowledge

Performance benchmarking


Move faster with managed compute resources

Q-CTRL offers our solutions as a cloud-based offering meaning you can leverage low-cost cloud hardware (CPUs, GPUs, memory) in order to achieve HPC-like performance without the need to establish or operate a local cluster. Execution of all calculations occurs invisibly based on a simple python interface.

clock illustration

10X reductions in time to solution
for large Hilbert spaces


Who should be using BOULDER OPAL

We have been using Q-CTRL's BOULDER OPAL for half a year and it has quickly become an essential tool in our research.

Christophe Valahu

Christophe Valahu

Trapped-ion Quantum Computing

University of Sussex


Go from signup to experiments in minutes

BOULDER OPAL integrates easily with experimental hardware

Quantum Machines IBM Qiskit Rigetti Quil
Learn more about integrations

I am very happy we decided to use your software and would recommend it to anyone wanting to use optimized pulses.

Marina Kudra

Marina Kudra

Chalmers University

  1. Sign up
  2. Download executable python application notes
  3. Format outputs for your hardware (or use our integration packages)
  4. Deploy solutions in the lab or in the cloud
BOULDER OPAL journey – illustration

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Don't wait to take control of your quantum future with Q-CTRL.
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BLACK OPAL®

BOULDER OPAL logo

Optimize your quantum hardware

  • Python SDK including Cloud API access for computationally intensive tasks
  • Optimize controls in high-dimensional systems and circuits. Account for leakage levels and dissipation.
  • Evaluate quasistatic and time-dependent noise-susceptibility of quantum gates and circuits
  • Simulate algorithm performance in realistic laboratory environments
  • Characterize noise in complex multidimensional systems
  • Integrate directly with hardware for full automation, including hardware calibration routines