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    Completed Consortium

    QPINN: Quantum Physics Informed Neural Networks for Derivative Pricing

    OQC and Citi tested whether quantum-compressed neural networks can price financial derivatives.

    Project data last updated 11 October 2026

    About this project

    Oxford Quantum Circuits led the project with Citi, the Quantum Software Lab and the NQCC. The team used quantum circuits to compress layers of physics-informed neural networks used to price derivatives.

    OQC reported that a key layer needed far fewer parameters while pricing stayed broadly close to a classical model in many test cases. The work was part of the NQCC SparQ proof of concept projects for 2025-26.

    Who leads it

    • Gerald Mullally

      Chief Executive Officer, Oxford Quantum Circuits

      Oxford Quantum Circuits

    Lead organisation

    Oxford Quantum Circuits

    Company · Reading

    Reading-based maker of superconducting quantum computers (Toshiko, GENESIS), backed by a £260m Series C in June 2026.

    Partners (3)

    Funders

    • NQCC

      Research organisation · Harwell

    In the news

    Quantum Zeitgeist articles naming the lead organisation or partners. They may not be about this project.

    All news for this project and its partners

    Sources

    1. NQCC: Quantum Physics Informed Neural Networks for Derivative Pricing (nqcc.ac.uk)
    2. NQCC: Collaborative R&D (SparQ proof of concept projects) (nqcc.ac.uk)
    3. OQC: Exploring quantum AI for financial modelling (oqc.tech)
    4. Quantum Zeitgeist: OQC, Citi and NQCC find quantum-AI cuts data needs for finance (quantumzeitgeist.com)