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- University of TorontoCA13 papers
- University of WaterlooCA11 papers
- Massachusetts Institute of TechnologyUS7 papers
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- Freie Universität BerlinDE6 papers
- Institute of Photonic SciencesES6 papers
- Perimeter InstituteCA6 papers
- University of CologneDE6 papers
- Barcelona Institute of Science and TechnologyES5 papers
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8 papers · 1 filter
Riemannian optimization of photonic quantum circuits in phase and Fock space
Yuan Yao, Filippo Miatto, Nicolás Quesada
We propose a framework to design and optimize generic photonic quantum circuits composed of Gaussian objects (pure and mixed Gaussian states, Gaussian unitaries, Gaussian channels,…
Generalization despite overfitting in quantum machine learning models
Evan Peters, Maria Schuld
The widespread success of deep neural networks has revealed a surprise in classical machine learning: very complex models often generalize well while simultaneously overfitting tra…
Fast quantum circuit cutting with randomized measurements
Angus Lowe, Matija Medvidović, Anthony Hayes +4
We propose a new method to extend the size of a quantum computation beyond the number of physical qubits available on a single device. This is accomplished by randomly inserting me…
Variational Quantum Optimization of Nonlocality in Noisy Quantum Networks
Brian Doolittle, Tom Bromley, Nathan Killoran +1
The inherent noise and complexity of quantum communication networks leads to challenges in designing quantum network protocols using classical methods. To address this issue, we de…
Simulating key properties of lithium-ion batteries with a fault-tolerant quantum computer
Alain Delgado, Pablo A. M. Casares, Roberto dos Reis +9
There is a pressing need to develop new rechargeable battery technologies that can offer higher energy storage, faster charging, and lower costs. Despite the success of existing me…
Is quantum advantage the right goal for quantum machine learning?
Maria Schuld, Nathan Killoran
Machine learning is frequently listed among the most promising applications for quantum computing. This is in fact a curious choice: Today's machine learning algorithms are notorio…