Advanced techniques - Qiskit addons
Qiskit addons are a collection of research capabilities for enabling algorithm discovery at the utility scale. These modular software components build upon Qiskit’s performant foundation and can plug into a workflow to scale or design new quantum algorithms.
Map domain problems
These capabilities specialize in mapping domain problems into quantum operators and circuits for execution on a quantum computer.
Model optimization problems and map them down into representations that can be understood by a quantum computer.
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Model fermionic quantum systems and map their representation to qubit operators and circuits.
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Approximate quantum compilation with tensor networks (AQC-Tensor) enables the construction of high-fidelity circuits with reduced depth.
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Multi-product formulas (MPF) reduce the Trotter error of Hamiltonian dynamics through a weighted combination of several circuit executions.
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Optimize circuits for hardware execution
These capabilities are useful for reducing circuit depth and typically come with an increased sampling overhead.
Operator backpropagation (OBP) reduces circuit depth by trimming operations from the end at the cost of more operator measurements.
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Circuit cutting reduces the depth of transpiled circuits by decomposing entangling gates between non-adjacent qubits.
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Manage noise for expectation value estimation
Use the following addons to manage noise when building quantum workloads that estimate expectation values of observables.
Propagated noise absorption (PNA) uses Pauli propagation to absorb information from a noise model into a target observable. Measuring this modified observable has the effect of mitigating the noise as represented by the model.
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The shaded lightcones (SLC) addon uses Pauli propagation to reduce the number of error terms in a noise model that need to be mitigated. This has the effect of reducing the sampling overhead for probabilistic error cancellation (PEC) workflows.
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Manage noise for sampling results
Manage noise when sampling results with the following addons.
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.
Overview
This addon is an HPC-ready implementation of the SQD addon. It is written in modern C++17 standards and is designed to create a single compiled binary for use with MPI.
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Incorporate measurement post selection transpiler passes to filter out non-Markovian noise in your circuits with the utilities addon.
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Matrix-free Measurement Mitigation
Matrix-free Measurement Mitigation (M3) is a package for scalable quantum measurement error mitigation that can be computed in parallel.
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Supplemental addons
This set of functions can be used to support and compose your workflows that leverage other addons.
This package, which supplements workflows involving one or more Qiskit addons, contains functions to create Hamiltonians, generate Trotter time evolution circuits, and slice and combine quantum circuits in time-wise partitions.
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