Stay up to date with the latest Boulder Opal release notes

Boulder Opal 19.7.1

November 22, 2022

Bug fix

  • We've updated the qctrl-toolkit version to fix an import error.

Boulder Opal 19.7.0

November 18, 2022

What's new

  • We've built a new graph-based gradient-free optimization function. It provides an alternative to gradient-based optimization when the gradient is inaccessible or very costly to compute.
  • We've added three new graph operations:
  • The Q-CTRL Visualizer function plot_filter_functions now also accepts filter functions as exported from graph calculations.

Boulder Opal 19.6.2

October 27, 2022

What's new

  • Upgraded gql package version to 3.4.0.

Boulder Opal 19.6.1

October 24, 2022

What's new

  • Added organization property to Qctrl session.

Boulder Opal 19.6.0

October 20, 2022

Breaking changes

  • We've improved the usability of the Q-CTRL Visualizer through a few changes:
    • The figure parameter for all functions is now an optional keyword-only argument. This means you can omit it when calling, for instance, plot_controls, and just pass the dictionary with your controls: plot_controls(controls). You can still pass a figure for the function to place the plot in it, using its keyword: plot_controls(controls, figure=your_figure).
    • The default value of y_axis_log in plot_cost_history has been changed from True to False.
    • The parameter seq of plot_sequences has been renamed to sequences.

What's new

  • We've added a new ions toolkit to streamline the workflow of performing calculations trapped ions systems in Boulder Opal. Find out more in the new tutorial and the reference documentation for the ions toolkit namespace.
  • We've added new graph operations to create displacement operators and squeeze operators in Fock spaces.
  • We've added a seed parameter to the calculate_optimization and calculate_stochastic_optimization functions. You can use it to obtain deterministic results from the initial values of optimizable graph nodes. Note that if your graph contains random operations, you need to set seeds for them as well for the optimization to be fully deterministic.
  • We've added a cost_tolerance parameter to the calculate_optimization function. You can use it to set an early stop condition for the optimizer, halting the optimization when the relative cost improvement over an iteration is smaller than the tolerance. See the reference documentation for more information.
  • We've added two parameters to the superconducting toolkit optimize function:
    • max_iteration_count: You can use this to set an early stop condition for the optimizer, halting the optimization if these many iterations have been taken.
    • cost_history: You can use this to retrieve the history of the cost function at each iteration during the optimization.
    • See the reference documentation for more information.
  • We've improved the performance of the neural network closed-loop optimizer up to 3X speed-up, especially for large test points, by introducing early stopping threshold and parallelizing training.
  • We've made changes to the layout of the documentation in order to improve accessibility and ease of navigation. You can see them in the Boulder Opal documentation.
  • We've added a new user guide on obtaining optimized controls using a Hann basis.

Boulder Opal 19.5.0

September 19, 2022

What's new

Boulder Opal 19.4.0

September 2, 2022

What's new

Boulder Opal 19.3.0

August 18, 2022

What's new

  • You can now mute and unmute status messages when running calculations. See an example in this user guide.
  • We have added a function that makes it easier for you to cite Boulder Opal in papers and other works. See an example in this user guide.

Boulder Opal 19.2.0

August 9, 2022

What's new

  • We've added the Q-CTRL Visualizer package as a dependency of the Q-CTRL Python package. Now you can keep up-to-date with the Visualizer's latest features without having to install or upgrade it separately.

Boulder Opal 19.1.0

August 8, 2022

What's new