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January 2026
v0.3.0
This release introduces updates across SDK, Experiment Tracking, Dashboard, Credits & Pricing, and User Guides documentation (Jupyter Notebooks) with improvements to usability, reliability, and observability.

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1. Pricing and credits management

We set up two pricing models:pricing_modelsEarly access includes 1 hour of execution time to explore our SDK and Dashboard features. A credits usage progress bar is displayed on the Dashboard. Users receive updates about future releases and deployments through a popup message on the main Dashboard screen.credits_tracking

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2. Experiment Tracking: Reports

Experiment reports support LaTeX-style Markdown for scientific formatting and allow users to add artifacts via drag-and-drop, making it easy to compose structured, shareable experiment summaries.Users can log Matplotlib plots as experiment artifacts, which appear in the Dashboard as part of the experiment history. Execution result tables can also be logged as artifacts. Supported tables include: Circuit core metrics, Circuit advanced metrics, Circuit all metrics, and Circuit comparison tables.experiment report

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3. Security and Privacy

Haiqu is ISO/IEC 27001 compliant and uses IAM-based controls to ensure customer data is handled with strong, auditable security practices. Access is granted only on a need-to-know basis, and clear records of who accessed what and when, supporting both compliance requirements and operational transparency, are maintained.To further reduce insider risk, production access is exception-based and support access is temporary and approved, with all activity logged and monitored. When needed, we can also provide access logs to help customers investigate incidents and meet internal governance standards.Security and PrivacyImage: Haiqu’s security and privacy practices as well as ISO certifications are documented our trust center webpage.

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4. Method haiqu.postprocess()

  • What does it do? Applies classical heuristics (e.g., bit-flip search) to measured bitstrings to find a better solution to the QUBO problem.
  • How do I use it? Pass counts or probability distribution obtained by running circuits on any backend, and pass the corresponding QUBO problem object, then call postprocess().
post_processing method resultsTable: Experiments result to compare a raw quantum results and post-processed results on a 120-qubit optimization problem

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Dashboard—Experiment Tracking

  • Plot logging Users can now log Matplotlib (MPL) plots as experiment artifacts using the haiqu.log() method. Logged plots appear in the Dashboard as part of the experiment history.
  • Logging of tables as artifacts Users can now include notebook-generated tables and visual outputs as artifacts in experiment reports. Added logging support for:
    • Circuit core metrics
    • Circuit advanced metrics
    • Circuit all metrics
    • Circuit comparison tables
  • Reports in experiment tracking
    • LaTeX-style Markdown support (UX)
    • Ability to insert artifacts into reports by drag and drop
  • Job deletion support

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Dashboard—Pricing Model

  • Pricing and access management
    • Defined two pricing packages
    • Added a Credits Request form and Pricing panel in the Dashboard
    • Enabled contacting support via Slack
    • Designed credits expiration flow in the SDK
    • Added Admin Panel UI for manual credit allocation
  • Credits management
    • Account creation now includes allocated credits (1h of execution time)
    • Added a credits usage progress bar on the Dashboard
    • Implemented credits consumption mechanics
    • Added SDK error messaging when credits are exhausted
    • Allows already-started jobs to finish even if credits expire during execution

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SDK—Execution

Renamed the run method argument (backend_name → device_id) for clarity and consistency when selecting execution devices.

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SDK—Postprocessing

Updated the haiqu.postprocess and haiqu.solve_qubo methods:
  • Improved QUBO problem definition and solution using a non-iterative method
  • Enhanced results postprocessing pipeline
  • Added detailed documentation explaining the updated workflow

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Jupyter Notebooks

Released an updated set of Jupyter notebooks in our Jupyter Lab env to help users get started with the Haiqu SDK, reflecting the latest APIs, workflows, and examples.
  • IonQ transpilation fix: Fixed a transpilation error for IonQ devices by updating the equivalence library in the transpilation worker to support IonQ-specific gates.
  • Aer simulator transpilation fix: Fixed a transpilation failure caused by a missing operation_names attribute when using aer_simulator.