Accelerate utility-scale development with Qiskit Functions

Functions are abstracted services, designed to accelerate algorithm discovery and application prototyping. Premium Plan members can get started with the IBM Circuit function, or purchase licenses from partners.

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Application functions

Integrate quantum into your application workflows, with domain-familiar classical inputs and outputs.
Calculate the ground state energy of molecules and generate the corresponding statevector.
Solve utility-scale optimization problems by inputting a high-level problem definition, and the solver will take care of the rest.

Circuit functions

Accelerate utility-scale algorithm and application discovery, with transpilation, error suppression, and error mitigation managed out-of-the-box.
Compute accurate expectation values on QPUs, with AI-powered circuit optimization, and advanced error mitigation methods.

Singularity Machine Learning

Multiverse Computing

With the Singularity Machine Learning function, you can solve real-world classification problems on quantum hardware without requiring quantum expertise. This function, based on ensemble methods, is a hybrid classifier which combines classical methods like boosting for ensemble training with quantum methods like quantum approximate optimization (QAOA) for optimizing the trained ensemble for maximum diversity, and generalization. Unlike other quantum machine learning solutions, this function is capable of handling large-scale datasets with millions of examples and features without being limited by the number of qubits. It is also highly flexible, and can be used to solve classification problems across a wide range of domains, including finance, healthcare, and cybersecurity.

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Features and benefits

  • Integrate seamlessly into existing ML workflows

    This function integrates seamlessly into existing ML pipelines, allowing users to incorporate quantum-enhanced capabilities without disrupting their current workflows.

  • Outperforms classical algorithms, providing superior model accuracy.

    These are the best QPU results Multiverse Computing has observed using QML in the literature so far.

  • Tackle complex and large-scale problems with ease

    Unlike other QML products, this function is capable of handling large-scale datasets with millions of examples and features without being limited by the number of qubits in the target QPU.

  • Easy to use & flexible – no quantum experience required

    This function is designed with user-friendliness in mind, featuring an intuitive interface that allows you to create the classifier, train it, and start predicting without needing any prior quantum computing knowledge. Its flexibility ensures that it can be applied across various domains, making advanced QML accessible to everyone.

Related papers

Scientific papers related to or supporting this function.

Testimonials

1.5-year PoC studies on the valuation of financial products, and the assessment of credit risks

Ali El Hamidi, Deputy Head Capital Markets Funding - Crédit Agricole CIB

"These two Proofs of Concept demonstrated the potential and reality of quantum computing for finance, despite these technologies still being in their infancy. We took advantage of this initiative to start developing the internal skills to prepare for a technological breakthrough which, if it happens, will have a direct and decisive impact on competitiveness in our sector."

MBA students use Singularity Machine Learning to solve a real-world problem from the financial crisis of 2008

Roberto García-Castro, Professor - IESE Business School

"Multiverse Computing’s tools allowed students to see the power of this emerging technology without needing any prior quantum experience."