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Found 3 papers, 1 papers with code
Machine Learning for maximizing the memristivity of single and coupled quantum memristors
We propose machine learning (ML) methods to characterize the memristive properties of single and coupled quantum memristors.
Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation
We introduce a novel methodology that leverages the strength of Physics-Informed Neural Networks (PINNs) to address the counterdiabatic (CD) protocol in the optimization of quantum circuits comprised of systems with $N_{Q}$ qubits.
An approach to interfacing the brain with quantum computers: practical steps and caveats
At the time of writing, available quantum computing hardware and brain activity sensing technology are not sufficiently developed for real-time control of quantum states with the brain.
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