Project description
Breaking the qubit barrier: parametrically coupled superconducting quantum oscillators
Quantum computing with its qubits analogous to classical computing’s bits promises unprecedented computing capacity in both scale and computation time. Superconducting qubits are among the most popular platforms of interest, but increasing the number of physically coupled superconducting qubits to network sizes remains a challenge – the largest quantum computer to date has less than 500 qubits. The ERC-funded qDynnet project is planning a pioneering approach to overcome this barrier. Parametrically coupled superconducting quantum oscillators instead of physically coupled qubits will enable quantum neural networks of unprecedented size, connectivity and tuneability. The project will go beyond current simulations to experimentally realise dynamical quantum neural network architectures with millions of neurons and tuneable connections.
Objective
Quantum neural networks are a young research field, that has been rapidly expanding due to their potential to attain revolutionary computing capacities and the possibility to learn on quantum data, inaccessible to classical computers. However, despite impressive proof-of-concept results, currently existing approaches that rely on sparsely coupled qubits, are not scalable to network sizes and connectivities with tunable weights required for state-of-the art tasks. In qDynnet, I will adopt a completely new and unexplored approach that uses parametrically coupled superconducting quantum oscillators instead of physically coupled qubits, that will allow me to obtain quantum neural networks of unprecedented size, connectivity and tunability. To do this, I will shift the paradigm by implementing neurons as basis states of dynamically coupled multi-level quantum oscillators, and connections between neurons as transition rates obtained through different dynamical processes such as parametric coupling, resonant drives and dissipation. I will implement experimentally quantum neural network architectures that were only simulated until now and use them to demonstrate data classification with basis state neurons. In order to go towards more complex tasks, I will use parametric coupling to introduce tunable connections between neurons. I will develop new training methods that will allow me to tune connections in such dynamical quantum neural networks and use them to demonstrate learning to recognize quantum states. I will develop circuit geometries that will be scalable to large quantum neural networks with millions of neurons and tunable connections. The qDynnet project will provide understanding of physics, and methods for dynamical coupling and training, that will have a broad impact across quantum computing fields and serve as a foundation for a whole new family of large-scale dynamical quantum neural networks.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering computer hardware quantum computers
- natural sciences mathematics pure mathematics geometry
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2022-STG
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75794 PARIS
France
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