Current and future workspaces
Workspaces are interfaces tailored to the control task at hand. In the early public releases BLACK OPAL will give you access to the following four workspaces:
- Noise characterization
As we add new feature sets look out for them appearing as new workspaces on the landing page. You’ll see below that we’ve even begun planning for feature releases by indicating the expected version release (vX.X) for certain features. Our current Public Release is (v1.1).
By default, you will see the Visualizations workspace. The active workspace is indicated in the main navigation as seen in the image below.
For more detailed capability please see BOULDER OPAL, which permits dramatically expanded functionality through a python interface.
This workspace permits you to analyze the performance of error-robust non-trivial single qubit operations (driven rotations, v1.1 Public), as well as error-robust memory (dynamic decoupling, v1.x). These two broad classes of operations may be implemented in the presence of non-commuting noise, with performance analysis performed in the filter function framework. Controls may also be optimized to provide error-robust solutions using our in house machine learning toolkit.
Q-CTRL has extended the filter function framework for calculating the noise susceptibility of nontrivial quantum logic operations to multiqubit gates. In this workspace you can analyze technology-specific control solutions tailored to both the Parametrically Driven (v1.1) and Cross-Resonance (v1.x) gates for superconducting circuits, and the Molmer-Sorensen gate for trapped ions (v1.1). In all settings you can choose from our library of custom controls, upload your own control waveforms for analysis, or create optimized controls (v1.1) based on the dominant noise processes in your hardware.
Get actionable information about noise and decoherence sources in your hardware with the control and data processing tools found in this workspace - then directly use this information to optimize controls. Define simple parameters about the noise process you wish to probe, output control operations to be measured, and upload the measurement results to BLACK OPAL for data fusion and spectrum reconstruction. Use either pulsed dynamic decoupling (v1.1) or provably optimal Slepian-shaped controls (v1.1) depending on the capabilities of your experimental hardware. We will also soon release our own machine-learning based technique to improve spectral reconstruction (v1.x).
Learn about the dynamic evolution of arbitrary single-qubit states on the Bloch sphere, or discover the meaning of non-classical correlations within a pair of qubits (v1.1). Our tools are fully interactive and allow you to explore various common quantum logic operations and gain intuition for complex concepts. Even entanglement is distilled to a simple visual representation of quantum correlations helping you explore how controls work within quantum circuits. We include tools to build and edit circuits and to incorporate error processes into visualization. Soon we will release export tools permitting you to embed these visualizations within your own presentations or webpages (v1.x).