Qiskit addons

Qiskit addons are a collection of research capabilities for enabling algorithm discovery at the utility scale. These capabilities build on Qiskit's performant foundation of tools for creating and running quantum algorithms. They are provided as modular software components that can plug into a workflow to scale or design new quantum algorithms.

Addons for mapping

Approximate quantum compilation with tensor networks

Approximate quantum compilation with tensor networks (AQC-Tensor) enables the construction of high-fidelity circuits with reduced depth.

• Visit the GitHub repository.
• Read the documentation.
• Read the tutorial on using AQC to improve Trotterized time evolution.

Multi-product formulas

Multi-product formulas (MPF) reduce the Trotter error of Hamiltonian dynamics through a weighted combination of several circuit executions.

• Visit the GitHub repository.
• Read the documentation.

Addons for optimizing

Operator backpropagation

Operator backpropagation (OBP) reduces circuit depth by trimming operations from the end at the cost of more operator measurements.

• Visit the GitHub repository.
• Read the documentation.
• Read the tutorial on using OBP to improve expectation values.

Circuit cutting

Circuit cutting reduces the depth of transpiled circuits by decomposing entangling gates between non-adjacent qubits.

• Visit the GitHub repository.
• Read the documentation.

Addons for post-processing

Sample-based quantum diagonalization

Sample-based quantum diagonalization (SQD) classically post-processes noisy quantum samples to yield more accurate eigenvalue estimations of quantum system Hamiltonians, for example in chemistry applications.

• Visit the GitHub repository.
• Read the documentation.
• Read the tutorial on improving energy estimation with SQD.