IBM Quantum Compute client v0.50.0

September 2026

• The directed execution model offers new tools for inspecting and customizing error mitigation workflow — New tools have been built on top of the directed execution model framework, which was released earlier this year:

  Together with Samplomatic, they make up the directed execution model, which provides full transparency and control to fine-tune your error mitigation workflow. The Probabilistic error cancellation with shaded lightcones tutorial, for example, demonstrates how this model is used to combine advanced techniques, including shaded lightcones, probabilistic error cancellation (PEC), Twirled Readout Error eXtinction (TREX), and measurement-based postselection, to further improve the result quality.

  • qiskit-noise-learning is a toolkit for randomization-based quantum noise characterization. You can use it to construct a custom noise-learning experiment, validate it with local simulation, and analyze the raw results.

  • qiskit-mitigation is a package of quantum error mitigation methods for building mitigation pipelines with the new execution model. It includes implementations of well-known methods, including PEC, PEA, TREX, and gate-folding ZNE, as well as post-selection for filtering out non-Markovian errors.

  • qiskit-ibm-runtime v0.50.0 released new client-side implementations of Sampler and Estimator primitives that are built on top of this framework. These implementations allow you to inspect exactly how each error mitigation method is implemented and test them locally before running them on an actual QPU.

    How to upgrade to the new primitives: Upgrading to the new primitives is designed to be low-friction, so in most cases, you only need to change your import statements — not the body of your code. See the migration guide for full details.

  • New skills for agents — Whether you are migrating to the new client-side Sampler and Estimator, or migrating old notebooks that still use V1 primitives, the migrate-qiskit-ibm-runtime skill in the Qiskit/skills repository can simplify the task. This new open-source repository contains official, IBM-verified agent skills for building IBM Quantum and Qiskit workflows. We will be adding more skills to this repository in the near future.

  • Lastly, check out the PEC with logical noise models tutorial for an example of stacking error detection and mitigation methods using these new tools.

  The directed execution model, comprised of Samplomatic and Executor, exposes the error mitigation logic applied to your workloads so that you have full control over the logic without sacrificing performance.

To see the release notes for all versions, visit the IBM Quantum Compute client release notes.